Eklund, P.; J. You; P. Deer, (2000). Mining remote sensing image data: an integration of fuzzy set theory and image understanding techniques for environmental change detection. Data Mining and Knowledge Discovery: Theory, Tools, and Technology II Orlando, FL, USA 24-25 April 2000
SPIE-Int. Soc. Opt. Eng
Proc. SPIE - Int. Soc. Opt. Eng. (USA), pp.265-72.
Keywords: Data mining; Feature extraction; Fuzzy set theory; Remote sensing; Remote sensing image data; Image understanding; Environmental change detection; Texture classification; Knowledge discovery; Remote image data ; B-spline based region representation
Original abstract: This paper presents an image understanding approach to mine remotely sensed image data from different source dates for environmental change detection. It is focused on the immediate needs for knowledge discovery from large sets of image data for environmental monitoring. In contrast to the traditional approaches for change detection, we introduce a wavelet-based hierarchical scheme which integrates fuzzy set theory and image understanding techniques for knowledge discovery of the remote image data. The proposed approach includes algorithms for hierarchical change detection, region representations and classification. The effectiveness of the proposed algorithms is demonstrated throughout the completion of three tasks, namely hierarchical detection of change by fuzzy post classification comparisons, localization of change by B-spline based region representation, and categorization of change by hierarchical texture classification.
 

El-Khattib, H. M.; N. M. El-Mowelhi; A. A. El-Salam, (1997). Desertification and land degradation using high resolution satellite data in the Nile Delta, Egypt. IGARSS'97. 1997 International Geoscience and Remote Sensing Symposium. Remote Sensing - A Scientific Vision for Sustainable Development (Cat. No.97CH36042) Singapore 3-8 Aug. 1997
New York, NY, USA IEEE, pp.197-9 vol.1.
Keywords: Agriculture; Geomorphology; Pollution; Remote sensing; Soil; North Africa; Rural area; Land surface; Arid region; Desert; Desertification; Land degradation; Nile Delta; Egypt; Remote sensing observations; Soil salinity; Agricultural land; Lake Manzala; ad 1992; ad 1995; Urban area; ad 1963; Salinization; Urbanization; Cultivated land ; Vegetation
Original abstract: Recently, recognition of the severity of the desertification problems in Egypt began to grow. Remote sensing data of different spectral, spatial and temporal resolutions and other ancillary data were used, including LANDSAT and SPOT images, topographic maps, soil survey studies conducted in 1963. Cases of land degradation and desertification in Egypt, especially soil salinity and urban desertification, are increasingly visible. The current investigation aims at studying desertification and soil degradation of agricultural lands in the north eastern part of the Nile Delta, adjacent to lake Manzala, Egypt. Modern techniques and most-up to date of satellite data using Multitemporal image processing analysis and the data were combined in CARIS GIS software for land degradation processes and calculations. Pedological, physiographic features and soil profiles were carefully studied with guidance of SPOT image for 1992 and LANDSAT TM for 1995. Soil samples were analyzed, maps of salinity and urban areas were carried out. The obtained results was compared with data collected on the same area in 1963 by the soil survey research department of the Soil, Water and Environment Research Institute (SWERI). Salinity and sodicity of soil was increased during the 1963-1992 period. Most of substantial changes in land degradation phenomenon in both soil salinization and urbanization are expected in the north eastern part of the Nile Delta in Egypt. Multitemporal images were processed for 12 settlements (villages and towns) for the period of 1952, 1963 and 1992, there were considerable 1952 urban expansion of using 40 years. The magnitude of increase in 1992 compared with 1952 was 1.1 to as high as 46 folds. Soil degradation and urban encroachment onto cultivated land are loss of productive lands as well as low values of NDVI are expected.
 

Elvidge, C. D.; Z. K. Chen; D. P. Groeneveld (1993). Detection of Trace Quantities of Green Vegetation in 1990 Aviris Data. Remote Sensing of Environment, V44, (N2-3): 271-279.
Keywords: AVIRIS , feature classification
 
 

Engdahl, M.; J. Hyyppa, (2000). Temporal averaging of multitemporal ERS-1/2 Tandem INSAR data. IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120) Honolulu, HI, USA 24-28 July 2000
Piscataway, NJ, USA IEEE, pp.2224-6 vol.5.
Keywords: Geophysical techniques; Remote sensing by radar; Spaceborne radar; Synthetic aperture radar; Terrain mapping; Geophysical measurement technique; Land surface; Land use; Radar remote sensing; Temporal averaging; Multitemporal; ers-2; ers-1; Tandem; insar; SAR interferometry; Classification ; Urban
Original abstract: In this study the potential of multitemporal ERS-1/2 SAR Tandem interferometry in land-use classification was investigated. Emphasis was on classifying land-use near urban centres, where the land-use features are typically small and high resolution is therefore desired. A high-quality orthorectified multitemporal interferometric dataset was created for further study. Temporal averaging, i.e. averaging over several intensity and coherence images reduces noise and increased the amount of discernible features without degrading the image resolution. At this stage of the study only visual classification has been done, temporal averaging was found to increase the number of visually discernible classes in the imagery.
 

Euisun, C.; L. Chulhee (2001). Optimizing feature extraction for multiclass problems. IEEE Transactions on Geoscience and Remote Sensing, 39, (3): 521-8.
Keywords: Feature extraction; Optimisation; Remote sensing; Feature extraction optimization; Multiclass problems; Pattern classification; Feature extraction method; Classification accuracies; Remotely sensed data ; Algorithm
Original Abstract: Feature extraction has been an important research topic in pattern classification and has been studied extensively by many researchers. Most of the conventional feature extraction methods are performed using a criterion function defined between two classes or a global function. Although these methods work relatively well in most cases, it is generally not optimal in any sense for multiclass problems. In order to address this problem, the authors propose a method to optimize feature extraction for multiclass problems. The authors first investigate the distribution of classification accuracies of multiclass problems in the feature space and find that there exist much better feature sets that the conventional feature extraction algorithms fail to find. Then the authors propose an algorithm that finds such features. Experiments with remotely sensed data show that the proposed algorithm consistently provides better performances compared with the conventional feature extraction algorithms.
 

Euisun, C.; L. Chulhee, (2000). Feature extraction based on the Bhattacharyya distance. IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120) Honolulu, HI, USA 24-28 July 2000
Piscataway, NJ, USA IEEE, pp.2146-8 vol.5.
Keywords: Feature extraction; Geophysical signal processing; Geophysical techniques; Image classification; Remote sensing; Terrain mapping; Geophysical measurement technique; Land surface; Image processing; Bhattacharyya distance; Classification error; Gaussian ML classifier; Feature vector ; Multiclass problem
Original abstract: The authors propose a feature extraction method based on the Bhattacharyya distance. Recently, it has been reported that an accurate estimation of classification error is possible using the Bhattacharyya distance. In the proposed method, the authors try to find feature vectors that minimize the estimated classification error of Gaussian ML classifier. In order to find such feature vectors, they start with arbitrary initial feature vectors and update them using two optimization techniques: sequential search and global search. Since they use the error estimation equation for updating feature vectors, the search time can be reduced significantly. They first apply the algorithm to two class problems and extend it to multiclass problems. Experimental results show that the proposed feature extraction algorithm compares favorably with conventional feature extraction algorithms.
 

Evans, T. P.; S. J. Walsh; B. Entwisle; R. R. Rindfuss, (1995). Testing model parameters of transportation network analyses in rural Thailand. GIS/LIS *95 Annual Conference and Exposition Proceedings of Geographic Information Systems/Land Information Systems Nashville, TN, USA 14-16 Nov. 1995
Bethesda, MD, USA American Soc. Photogrammetry & Remote Sensing & American Congress on Surveying & Mapping, pp.302-11 vol.1.
Keywords: Geographic information systems; Health care; Sensitivity analysis; Statistics; Transportation; Model parameter testing; Transportation network analyses; GIS environment; Geographic information system; Geographic accessibility; Family planning; Remote villages; Health care facilities; Thailand Nang Rong; Longitudinal survey data; Topographic maps; Road surface type; Passable seasons; Network routing model peformance; Travel assumptions; Travel speeds; Road closure; Flooding; Spatial interaction weighting schemes; Descriptive statistics; Euclidean distance ; Skewed travel time distribution
Original abstract: Network analysis techniques implemented within a GIS environment are used to assess the geographic accessibility of villages to health care facilities in Nang Rong district, Thailand. Data for the research consists of longitudinal survey data at the village level and transportation network data digitized from topographic maps that classify roads by surface type and seasons passable. A sensitivity analysis is used to determine the performance of the network routing model as a consequence of travel assumptions and scenarios. This work uses network analysis to measure the travel times between 51 rural villages and 42 health care centers in the study area. Various scenarios are used to test the sensitivity of the analysis to different model parameters including variations in travel speeds for different road types, closure of roads due to flooding, and spatial interaction weighting schemes. Descriptive statistics are used to evaluate the sensitivity of the network analysis to model parameters. Sensitivity analyses showed that Euclidean distance skewed the distribution of travel time to the closest health center, making remote villages appear more isolated. Network analysis was used to evaluate the nature of family planning accessibility by varying travel scenarios involving travel characteristics and road conditions. Information on road type, seasonality and mode of transportation are important considerations in modelling accessibility, particularly in the rural environment of Nang Rong.
 

Farison, J. B.; U. Vanjara; E. Merenyi, (2000). AVIRIS image compression with orthogonal projection and KL transforms. Proceedings of the IASTED International Conference. Signal and Image Processing Proceedings of 2000 Conference on Signal and Image Processing Las Vegas, NV, USA 19-23 Nov. 2000
Anaheim, CA, USA IASTED/ACTA Press, pp.52-7.
Keywords: Data compression; Feature extraction; Image coding; Image sequences; Infrared imaging; Infrared spectroscopy; Karhunen-Loeve transforms; Remote sensing; Visible spectroscopy; AVIRIS image compression; Airborne visible/infrared imaging spectrometer; Orthogonal projection transform; Karhunen-Loeve transform; Hyperspectral images; Feature separation; Spatially invariant image sequences; Linearly additive image sequences; Spatial distributions; Imaging signatures; Spectral signatures; Spatial distribution maps ; Optimal compression technique
Original abstract: The orthogonal projection (OP) transform has been applied to AVIRIS (airborne visible/infrared imaging spectrometer) hyperspectral images for feature separation. The method is based on a mathematical model for spatially invariant, linearly additive image sequences which describes the image sequence in terms of the spatial distributions and imaging signatures of the distinct features present in the image scene. The OP transform uses the spectral signatures of the image features to transform the original image sequence into the respective spatial distribution maps of the separate features, from which the original image sequence can be reconstructed. The Karhunen-Loeve transform (KLT) is an optimal compression technique based on the statistical variance of the data. The KLT is characterized by its ability to compact the information content in an image set into its first few principal components. However, it does not isolate the distinctive features of the image data. The focus of this paper is to compare the results of the two methods as applied to an AVIRIS image sequence.
 

Farrall, M. H.; M. Painho; L. T. Vasconcelos; M. R. Paiva, (1996). Spatial scale analysis of landscape fragmentation due to transport corridors. Geographical Information from Research to Application Through Cooperation. Second Joint European Conference and Exhibition Proceedings of Joint European Conference on Geographical Information Barcelona, Spain 27-29 March 1996
Amsterdam, Netherlands IOS Press, pp.602-10 vol.1.
Keywords: Ecology; Geographic information systems; Sensitivity analysis; Statistics; Town and country planning; Transportation; Spatial scale analysis; Landscape fragmentation; Transport corridors; Environmental problems; Europe; Linear features; Transport infrastructures; Ecosystem threats; Habitats; Species conservation; Geographic information system; Professional decisions; Landscape structure; Influence zone; Patch boundaries ; Natural areas
Original abstract: Landscape fragmentation has become one of the major environmental problems in Europe. Unfortunately, when assessing the spatial characteristics of a landscape, linear features like roads and railways are often not included in the analysis. The investment in transport infrastructures is now creating additional threats to existing ecosystems. Major consequences of transport corridor implementation include direct fragmentation of habitats and the subsequent alteration of the landscape structure. Due to differences in the scales at which organisms perceive the environment, responses to landscape patterns vary among species. Conservationists, ecological consultants and planners must usually rely on intuition to make decisions that could influence the survival of animal populations. With a GIS, it becomes easier to provide spatial information to guide the decisions of professionals working in the area of the environment. This study addresses the question of how incorporating transport corridors in the analysis affects landscape structure over a range of spatial scales. The computed landscape metrics included edge, shape, core area and contagion statistics. Sensitivity analysis was performed on two buffer areas-the transport corridor's influence zone and patch boundaries. A critical analysis was made, comparing the advantages and deficiencies of the utilized indices, due to variations inflicted by changes of these factors. This analysis specifically targets natural areas. A discussion of the behavior of indices according to the modification of several factors was conducted.
 

Farrand, W. H.; R. B. Singer; E. Merenyi (1994). Retrieval of Apparent Surface Reflectance from Aviris Data - a Comparison of Empirical Line, Radiative Transfer, and Spectral Mixture Methods. Remote Sensing of Environment, V47, (N3): 311-321.
Keywords:
 
 

Fayek, R. E.; A. K. C. Wong, (1996). Extracting buildings from aerial topographic maps. International Conference on Image Processing (Cat. No.96CH35919) Proceedings of 3rd IEEE International Conference on Image Processing Lausanne, Switzerland 16-19 Sept. 1996
New York, NY, USA IEEE, pp.401-4 vol.2.
Keywords: Building; Feature extraction; Image segmentation; Inference mechanisms; Mesh generation; Object recognition; Remote sensing; Aerial topographic maps; 2D information recovery; Intensity images; 3D information; Range images; 3D object recognition; Sensory data; Remote sensing aerial images; 2D intensity images; 3D data; Symbolic information extraction; 3D triangular mesh models; Symbolic reasoning; Generic object models ; Image regions
Original abstract: The recovery of 2D information from intensity images, and that of 3D information from range images are the major issues in 3D objects recognition from sensory data. The analysis and interpretation of remote sensing aerial images have important applications. This paper presents an efficient method for the analysis and modeling of such scenes based on range sensory data. Unlike methods using 2D intensity images, we exploit the rich 3D data. We extract symbolic information from the 3D triangular mesh models. These are used to recognize buildings using symbolic reasoning and generic object models.
 

Fern, A.; M. T. Musavi; J. Miranda (1998). Automatic extraction of drainage network from digital terrain elevation data: a local network approach. IEEE Transactions on Geoscience and Remote Sensing, 36, (3): 1007-11.
Keywords: Feature extraction; Geomorphology; Geophysical signal processing; Geophysical techniques; Geophysics computing; Hydrological techniques; Image processing; Rivers; Topography (Earth); Hydrology; Remote sensing; Automatic extraction; Drainage network; River; Digital terrain elevation data; Local network approach; Locally connected processing unit; Global problem ; Land surface topography
Original Abstract: A local network for the automatic extraction of drainage networks from elevation data is described. The methodology demonstrates how a large number of locally connected processing units can solve the global problem of drainage network extraction. The methodology has advantages over previous methods and is able to extract lakes as well as streams and rivers.
 

Ferretti, A.; F. Ferrucci; C. Prati; F. Rocca, (2000). SAR analysis of building collapse by means of the permanent scatterers technique. IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120) Honolulu, HI, USA 24-28 July 2000
Piscataway, NJ, USA IEEE, pp.3219-21 vol.7.
Keywords: Geophysical techniques; Remote sensing by radar; Surveying; Synthetic aperture radar; Terrain mapping; Geophysical measurement technique; Land surface; Building; Buildings; Collapse; Urban area; Town; City; Radar remote sensing; sar; Permanent scatterers technique; Deformation; DInSAR; Differential InSAR; Terrain motion; Line of sight; Camaiore; Milano; Milan; Paris; Precursory motion; Italy; Spain ; Precursor
Original abstract: As already shown in previous papers, detection of stable areas make it possible to use DInSAR techniques to get local measurements on a pixel-by-pixel basis. Reliable deformation measurements can then be obtained on a subset of image pixels, called Permanent Scatterers (PS). These points can be used as a "natural GPS network" to monitor terrain motion in the direction of the line of sight (LOS), analyzing the phase history of each one. In urban areas most of the PS correspond to single buildings whose deformation can be measured every 35 days with an accuracy better than one millimeter. Results obtained ERS SAR images are presented for 3 test sites: Camaiore (40 images), Milano (62 images) and Paris (64 images). Time series analysis of collapsed buildings in Camaiore are illustrated which show interesting precursory motions. Time series analysis of two metallic buildings in Milano and Paris are then used to validate the technique and to estimate its accuracy.
 

Ferretti, A.; C. Prati; F. Rocca, (2000). Nonlinear subsidence rate estimation using permanent scatterers in differential SAR interferometry. IEEE 1999 International Geoscience and Remote Sensing Symposium. IGARSS'99 Hamburg, Germany 28 June-2 July 1999
IEEE Trans. Geosci. Remote Sens. (USA), pp.2202-12.
Keywords: Geodesy; Geophysical techniques; Remote sensing by radar; Synthetic aperture radar; Tectonics; Terrain mapping; Uplift; Downlift; Geophysical measurement technique; Radar remote sensing; InSAR; Nonlinear subsidence rate estimation; Permanent scatterer; Differential SAR interferometry; Urban area; Absidence; Subsidence; Atmospheric phase contribution; Nonlinear motion ; Phase unwrapping
Original abstract: Discrete and temporarily stable natural reflectors or permanent scatterers (PS) can be identified from long temporal series of interferometric SAR images even with baselines larger than the so-called critical baseline. This subset of image pixels can be exploited successfully for high accuracy differential measurements. The authors discuss the use of PS in urban areas, like Pomona, CA, showing subsidence and absidence effects. A new approach to the estimation of the atmospheric phase contributions, and the local displacement field is proposed based on simple statistical assumptions. New solutions are presented in order to cope with nonlinear motion of the targets.
 

Finch, J.; A. Reid; G. Roberts (1989). The Application of Remote Sensing to Estimate Land Cover for Urban Drainage Catchment Modelling. Journal of the Institution of Water and Environmental Management, V3, (N6): 558-563.
Keywords:
 
 

Fischer, A.; T. H. Kolbe; F. Lang; A. B. Cremers; W. Forstner; L. Plumer; V. Steinhage (1998). Extracting buildings from aerial images using hierarchical aggregation in 2D and 3D. Computer Vision and Image Understanding, 72, (2): 185-203.
Keywords: Computer vision; Feature extraction; Image reconstruction; Logic programming; Object recognition; Remote sensing; Stereo image processing; Aerial images; Building extraction; Model-based method; 3D images; Data-driven process; Model-driven process; Multilevel aggregation hierarchy; Multiple image correspondence ; Constraint logic programming
Original Abstract: We propose a model-based approach to automated 3D extraction of buildings from aerial images. We focus on a reconstruction strategy that is not restricted to a small class of buildings. Therefore, we employ a generic modeling approach which relies on the well-defined combination of building part models. Building parts are classified by their roof type. Starting from low-level image features we combine data-driven and model-driven processes within a multilevel aggregation hierarchy, thereby using a tight coupling of 2D image and 3D object modeling and processing, ending up in complex 3D building estimations of shape and location. Due to the explicit representation of well-defined processing states in terms of model-based 2D and 3D descriptions at all levels of modeling and data aggregation, our approach reveals a great potential for reliable building extraction.
 

Fiset, R.; F. Cavayas (1997). Automatic comparison of a topographic map with remotely sensed images in a map updating perspective: The road network case. International Journal of Remote Sensing, V18, (N4): 991-1006.
Keywords:
Original Abstract: A map guided procedure to automatically extract the road network from SPOT-HRV panchromatic images is proposed in a topographic map revision perspective. This procedure allows highly accurate results to be obtained independently of the density and the shape of the road network. The procedure is described in detail, along with our conclusions concerning the optimal conditions of its application. Some preliminary results are also shown concerning the introduction of a back-propagation neural network to extract the road network. This approach is considered to eliminate the problems associated with the grey level value and edge intervals. In the proposed procedure these intervals are necessary to detect the roads and must be specified every time to adapt to the particular radiometric content of a new image.
 

Fiset, R.; F. Cavayas; M. C. Mouchot; B. Solaiman; R. Desjardins (1998). Map-image matching using a multi-layer perceptron: the case of the road network. Isprs Journal of Photogrammetry and Remote Sensing, V53, (N2): 76-84.
Keywords: map updating feature extraction, satellite imagery; road extraction; neural network; template matching; map updating
Synopsis: This article describes a method of automated map revision (scale 1:50,000) where new roads can be added to a map database. Roads are matched using a multi-layer perceptron (MLP) which corresponds segments from SPOT-HRV panchromatic images to segments in a map database. New roads can then be extracted from the images.
Original Abstract: To help automatize map revision at a scale of 1 : 50,000, a map-guided method is described to update the road network of a map database. This paper describes the essential first step of the procedure, which consists of matching the roads present on both the image and the map database. This matching has to be performed precisely in order to generate meaningful hypotheses on the location of new roads. The matching is conducted by using a multi-layer perceptron (MLP) trained to recognize road segments on the SPOT-HRV panchromatic image corresponding to the cartographic database being treated. Two template matching methods using the trained MLP weight matrix are developed. The first method locates all the road intersections on the image, while the second method locates the segments only. Both methods are not accurate enough to be used alone. However, combining both approaches gives results that are reliable enough to be used in the generation of the hypotheses needed to extract new roads.
 

Fiset, R.; F. Cavayas; M. C. Mouchot; B. Solaiman; R. Desjardins, (1996). An automatic road extraction method using a map-guided approach combined with neural networks for cartographic database validation purposes. IGARSS '96. 1996 International Geoscience and Remote Sensing Symposium. Remote Sensing for a Sustainable Future (Cat. No.96CH35875) Lincoln, NE, USA 27-31 May 1996
New York, NY, USA IEEE, pp.236-8 vol.1.
Keywords: Cartography; Feature extraction; Geophysical signal processing; Geophysical techniques; Geophysics computing; Neural nets; Geophysical measurement technique; Map-guided approach; Remote sensing; Terrain mapping; Automatic road extraction method; Image processing; Neural network; Neural net; Cartographic database validation; Road intersection; SPOT panchromatic image; Optical imaging; Planimetric accuracy; Land surface; Urban area ; Town city
Original abstract: A method is proposed to extract road intersections from a SPOT panchromatic image, using a map-guided approach combined with the application of a neural network. The results show an average increase of 36% of planimetric accuracy after applying the method instead of simply superimposing the roads on the geocoded image. Also, only 8 out 42 samples were previously correctly traced, compared to 27 after application of the algorithm.
 

Fletcher, E. J.; I. Busby; D. Wheatley, (1995). Intelligent support tools for the exploitation of a network referenced database system for urban highways. *Steps Forward'. Proceedings of the Second World Congress on Intelligent Transport Systems *95 Yokohama Proceedings of 2nd World Congress on Intelligent Transport Systems Yokohama, Japan 9-11 Nov. 1995
Tokyo, Japan Vehicle, Road & Traffic Intelligence Soc, pp.1652-6 vol.4.
Keywords: Data acquisition; Expert systems; Geographic information systems; Public administration; Traffic engineering computing; Transportation; Visual databases; Intelligent support tools; Network referenced database system; Urban highways; Sunderland; Highway data acquisition systems; Video surveying; GIS developments; Road surface macro texture; Skidding resistance assessment; Road sign detection; CityLIGHT ; CitySIGN
Original abstract: This paper reports on the experience of a local highway authority (The City of Sunderland) in association with the local University in developing a range of highway data acquisition systems, post survey processing techniques and data management tools. In particular the paper outlines work on video surveying and attempts to speed up the post survey processing using expert systems support, experiences with in house GIS developments, road surface macro texture and skidding resistance assessment and early work on automated road sign detection from video data. As an example of the management tools the CityLIGHT and CitySIGN software packages are discussed.
 

Foody, G. M. (1995). Land cover classification by an artificial neural network with ancillary information. International Journal of Geographical Information Systems, 9, (5): 527-42.
Keywords: Cartography; Geographic information systems; Neural nets; Remote sensing; Town and country planning; Land cover classification; Artificial neural network; Ancillary information; gis; Remotely-sensed data; Statistical classification; Fuzzy output; Class membership; Fuzzy classification; Mapping; Soil type ; Geographic information system
Original Abstract: Remote sensing is an important source of land cover data required by many GIS users. Land cover data are typically derived from remotely-sensed data through the application of a conventional statistical classification. Such classification techniques are not, however, always appropriate, particularly as they may make untenable assumptions about the data and their output is hard, comprising only the code of the most likely class of membership. Whilst some deviation from the assumptions may be tolerated and a fuzzy output may be derived, making more information on class membership properties available, alternative classification procedures are sometimes required. Artificial neural networks are an attractive alternative to the statistical classifiers and one is used to derive a fuzzy classification output from a remotely-sensed data set that may be post-processed with ancillary data available in a GIS to increase the accuracy with which land cover may be mapped. With the aid of ancillary information on soil type and prior knowledge of class occurrence the accuracy of an artificial neural network classification was increased by 29.93 to 77.37 per cent. An artificial neural network can therefore be used generate a fuzzy classification output that may be used with other data sets in a GIS, which may not have been available to the producer of the classification, to increase the accuracy with which land cover may be classified.
 

Ford, B. J.; D. K. Widner, (2000). Shared geography: building a common street centerline resource to service state and county governments. URISA 2000 Annual Conference and Exposition Proceedings of 37th Annual Conference of the Urban and Regional Information Systems Association Orlando, FL, USA 19-23 Aug. 2000
Park Ridge, IL, USA Urban & Regional Inf. Syst. Assoc
URISA Proceedings. Papers from the Annual Conference, pp.584-93.
Keywords: Cartography; Geographic information systems; Government data processing; Town and country planning; Transportation; Visual databases; Common street centerline resource; Government data; Roadway; Virginia Department of Transportation; Geocoding; Mapping products; gis; Street information; Complex data sets ; Geographic information system
Original abstract: Building and maintaining a common street centerline file to fill the needs of a county government and a state department of transportation is a unique and challenging task. The Virginia Department of Transportation (VDOT) and the Fairfax County Geographic Information Services Department have jointly decided to take on that task. Within the borders of Fairfax County, VA there are approximately 4000 miles of roadway. VDOT is responsible for the maintenance of over 2600 miles of this roadway. There are 300-400 new streets added to the system each year as well as hundreds of state and county projects each year that alter the current network. At a county level a street centerline must support the routing of emergency vehicles, school buses, maintenance crews, and hundreds of other inspectors and field personnel. The street centerline layer must be able to support other analysis applications such as geocoding. Further, the street layer must support the cartographic production of small and large scale mapping products. This paper should be of interest to GIS professionals responsible for maintaining street information or other complex data sets that could support multiple levels of government.
 

Ford, S. J.; D. Kalp; J. McGlone; D. M. McKeown, Jr., (1997). Preliminary results on the analysis of HYDICE data for information fusion in cartographic feature extraction. Integrating Photogrammetric Techniques with Scene Analysis and Machine Vision III Orlando, FL, USA 21-23 April 1997
SPIE-Int. Soc. Opt. Eng
Proc. SPIE - Int. Soc. Opt. Eng. (USA), pp.67-86.
Keywords: Cartography; Data analysis; Feature extraction; Geophysical signal processing; Image processing; Remote sensing; Sensor fusion; Spectral analysis; HYDICE data analysis; Information fusion; Cartographic feature extraction; Hyperspectral Digital Imagery Collection Experiment; Airborne hyperspectral imagery; Surface material attribution; Fort Hood; Texas; usa; Geopositioning; Multisensor registration; Surface material classification; 2 meter GSD; Hyperspectral dataset; Spatial resolution; Panchromatic mapping imagery; Urban scene analysis ; Spatial database population
Original abstract: This paper discusses ongoing research in the analysis of airborne hyperspectral imagery with application to cartographic feature extraction and surface material attribution. Preliminary results, based upon the processing and analysis of hyperspectral data acquired by the Naval Research Laboratory's (NRL) Hyperspectral Digital Imagery Collection Experiment (HYDICE) over Fort Hood, Texas in late 1995, are shown. Significant research issues in geopositioning, multisensor registration, spectral analysis, and surface material classification are discussed. The research goal is to measure the utility of hyperspectral imagery acquired with high spatial resolution (2 meter GSD) to support automated cartographic feature extraction. Our hypothesis is that the addition of a hyperspectral dataset, with spatial resolution comparable to panchromatic mapping imagery, enables opportunities to exploit the inherent spectral information of the hyperspectral imagery to aid in urban scene analysis for cartographic feature extraction and spatial database population. Test areas selected from the Fort Hood dataset will illustrate the process flow and serve to show current research results.
 

Ford, S. J.; J. C. McGlone; S. D. Cochran; J. A. Shufelt; W. A. Harvey; D. M. McKeown, Jr., (1998). Analysis of HYDICE data for information fusion in cartographic feature extraction. IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings. (Cat. No.98CH36174) Seattle, WA, USA 6-10 July 1998
New York, NY, USA IEEE, pp.2702-6 vol.5.
Keywords: Feature extraction; Geophysical signal processing; Geophysical techniques; Image classification; Image registration; Multidimensional signal processing; Remote sensing; Sensor fusion; Terrain mapping; Geophysical measurement technique; Land surface; Land use; Optical imaging; Multispectral remote sensing; Hyperspectral imaging; hydice; Information fusion; Cartography; Image processing; Hyperspectral Digital Imagery Collection Experiment; Fort Hood; United States; usa; Texas; Geopositioning ; Photogrammetric block adjustment
Original abstract: Late in 1995 the authors organized a hyperspectral data acquisition using the Naval Research Laboratory's Hyperspectral Digital Imagery Collection Experiment sensor system over Fort Hood, Texas. This acquisition resulted in hyperspectral data with a nominal 2 meter ground sample distance collected with 210 spectral samples per pixel. This paper describes current quantitative classification results for man-made and natural materials using 14 surface material classes over selected test areas within Fort Hood. The authors discuss the issues encountered in radiometric effects due to changing solar illumination and atmospheric conditions during the acquisition. They also describe their approach to image registration and geopositioning, using a full photogrammetric block adjustment solution.
 

Foresman, T. W.; J. E. Estes; J. J. Garegnani; D. L. Porter, (1996). Remote sensing and core data needed to support planning and policy decision making. IGARSS '96. 1996 International Geoscience and Remote Sensing Symposium. Remote Sensing for a Sustainable Future (Cat. No.96CH35875) Lincoln, NE, USA 27-31 May 1996
New York, NY, USA IEEE, pp.2243-5 vol.4.
Keywords: Geophysical techniques; Government policies; Remote sensing; Town and country planning; Geophysical measurement technique; Land surface; Terrain mapping; Planning; Policy decision making; Sustainable development research; Land use; Land cover change; Environment; Satellite imagery ; Regional Data Center
Original abstract: A variety of sustainable development research efforts and related activities are attempting to reconcile the issues of conserving our natural resources without limiting economic motivation while also improving our social equity and quality of life. Land use/land cover change, occurring on a global scale, is an aggregate of local land use decisions and profoundly impacts our environment. It is therefore the local decision making process that should be the eventual target of many of the ongoing data collection and research efforts which strive toward supporting a sustainable future. Satellite imagery data is a primary source of data upon which to build a core data set for use by researchers in analyzing this global change. A process is necessary to link global change research, utilizing satellite imagery, to the local land use decision making process. One example of this is the NASA-sponsored Regional Data Center (RDC) prototype. The RDC approach is an attempt to integrate science and technology at the community level. The anticipated result of this complex interaction between research and the decision making communities will be realized in the form of long-term benefits to the public.
 

Forster, B.; C. Ticehurst; Y. Dong, (1997). Analysis of radar response from urban areas. IGARSS'97. 1997 International Geoscience and Remote Sensing Symposium. Remote Sensing - A Scientific Vision for Sustainable Development (Cat. No.97CH36042) Singapore 3-8 Aug. 1997
New York, NY, USA IEEE, pp.891-4 vol.2.
Keywords: Backscatter; Geophysical techniques; Radar cross-sections; Radar imaging; Radar polarimetry; Remote sensing by radar; Synthetic aperture radar; Geophysical measurement technique; Land surface; Terrain mapping; Urban area; City; Town; Radar remote sensing; Buildings; Radar scattering; Backscattering; Image classification; AirSAR quad polarised radar; sar; Sydney; Australia ; Building orientation
Original abstract: The output from regular mapping and monitoring of urban areas provides an important source of information for urban planners and decision makers. The use of remotely sensed data to provide this information has been successful in particular environments but has had only limited success in tropical zone countries where cloud and rain often restrict the useful acquisition of visible/infrared image data on a regular basis. In many cases, and particularly in east Asia, these are precisely the areas that most need the data. A number of researchers have examined the potential of using radar images to overcome these problems, because at the wavelengths used (X- to P-), radar is not affected by cloud or rain. Urban areas are a spatially complex mixture of both natural and built surfaces whose spectral and geometric properties are many and varied. Buildings for example, cause significant backscatter when irradiated by microwave radiation, which is dependent on wavelength, polarisation and incidence angle of the radar beam, and roughness, dielectric properties and size, shape and orientation of the buildings and their surface facets. To some extent all combinations of specular and diffuse backscatter are a function of the height and width of buildings, and thus give rise to the possibility of using backscatter as a measure of the bulk density of the built environment. Equations for backscattering mechanisms, often found in urban environments, are well known. These are for example, facets, point scatterers, dihedral and trihedral corner reflectors, cylinders and wedges. This paper examines the theoretical relationships between urban morphology and remote sensing response at radar wavelengths, provides some preliminary results on measures of urban classification using AirSAR quad polarised radar data from test sites over the city of Sydney, Australia, and proposes a solution to the problem of backscatter variation due to building orientation.
 

Freeland, R.; J. Susa (1997). PennDOT deploys districtwide GIS. GIS World, 10, (8): 52-4.
Keywords: Geographic information systems; Public administration; Town and country planning; PennDOT; Districtwide GIS; Pennsylvania Department of Transportation; Roadway data; Map products; Maps; GIS workstation; Local database; Plotter ; System training
Original Abstract: The Pennsylvania Department of Transportation (PennDOT) is laying the groundwork to boost employees' productivity at its district offices by making it easier for them to find, format and analyze roadway data. Until recently, all requests for maps and map products were handled by PennDOT's central office GIS staff in Harrisburg. Following a successful pilot project, every district office is scheduled to receive a GIS workstation, software, local database, plotter and system training. The move positions PennDOT as one of the nation's first transportation agencies to successfully deploy GIS within its districts.
 

Freeman, A.; S. Hensley; E. Moore, (1999). Analysis of radar images of Angkor, Cambodia. IEEE 1999 International Geoscience and Remote Sensing Symposium. IGARSS'99 (Cat. No.99CH36293) Hamburg, Germany 28 June-2 July 1999
Piscataway, NJ, USA IEEE, pp.2572-4 vol.5.
Keywords: Airborne radar; Archaeology; Remote sensing by radar; Synthetic aperture radar; Terrain mapping; Angkor; Cambodia; Radar image analysis; 1996 AIRSAR Pacific Rim Deployment data; Temples; Cities; Prehistoric habitation; Hydraulic constructions; Urban zone; Topography; Feature identification; Feature delineation; Circular earthworks; Circular village sites; Earthwork dykes; Reservoirs; Canals; Temple sites ; Main temple complex
Original abstract: During the 1996 AIRSAR Pacific Rim Deployment, data were collected over Angkor in Cambodia. The temples of Angkor date the succession of cities to the 9th-13th century AD, but little is known of its prehistoric habitation. A related area of archaeological debate has been the origin, spiritual meaning and use of the hydraulic constructions in the urban zone. The high resolution, multi-channel capability of AIRSAR, together with the unprecedentedly accurate topography provided by TOPSAR, offer identification and delineation of these features. Examples include previously unrecorded circular earthworks around circular village sites, detection of unrecorded earthwork dykes, reservoirs and canal features, and of temple sites located some distance from the main temple complex at Angkor.
 

Frere, D.; J. Vandekerckhove; T. Moons; L. Van Gool, (1998). Automatic modelling and 3D reconstruction of urban buildings from aerial imagery. IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings. (Cat. No.98CH36174) Seattle, WA, USA 6-10 July 1998
New York, NY, USA IEEE, pp.2593-6 vol.5.
Keywords: Cartography; Computer graphics; Geophysical techniques; Geophysics computing; Photogrammetry; Remote sensing; Geophysical measurement technique; Terrain mapping; Building; Three dimensional model; Computer model; Automatic model; Three dimensional reconstruction; Urban buildings; Aerial image; House; Roof; Residential area; Urban site; Reasoning; Hypothesis generation ; Verification
Original abstract: A method is presented that automatically generates 3D models of generic house roofs from aerial images of residential areas in urban sites. Crucial to the method is the possibility of delineating regions in the images that correspond well to actual roof structures. Restricting the processing to relatively small regions allows at all stages of the algorithm to use constraints that are not very tight, and, at the same time, to keep the combinatorics under control. All modelling is done by reasoning in 3D. By adopting a strategy of hypothesis generation and verification the authors are not only are capable of exploiting all available image data at every step in the algorithm, but also to treat all views equally. Decoupling topology retrieval from metric accuracy makes it possible to generate and test combinations which otherwise would have been ruled out by more tight constraints. The method is implemented and tests on the correctness and completeness of the extracted roof models have been performed.
 

Frery, A. C.; H. J. Muller; C. C. F. Yanasse; S. J. S. Sant'Anna (1997). A model for extremely heterogeneous clutter. IEEE Transactions on Geoscience and Remote Sensing, 35, (3): 648-59.
Keywords: Backscatter; Electromagnetic wave scattering; Geophysical techniques; Radar clutter; Radar cross-sections; Radar imaging; Radar theory; Remote sensing by radar; Geophysical measurement technique; Terrain mapping; Land surface; Radar remote sensing; Model; Extremely heterogeneous clutter; G distribution; Multiplicative model; Multilook intensity; Amplitude data; Urban area ; Speckle
Original Abstract: A new class of distributions, G distributions, arising from the multiplicative model is presented, along with their main properties and relations. Their densities are derived for complex and multilook intensity and amplitude data. Classical distributions, such as K, are particular cases of this new class. A special case of this class called G/sup 0/, that has as many parameters as K distributions, is shown able to model extremely heterogeneous clutter, such as that of urban areas, that cannot be properly modeled with K distributions. One of the parameters of this special case is related to the degree of homogeneity, and a limiting case is that of a scaled speckle. The advantage of the G/sup 0/ distribution becomes evident through the analysis of a variety of areas (urban, primary forest and deforested) from two sensors.
 

Friedl, M. A.; C. E. Brodley; A. H. Strahler (1999). Maximizing land cover classification accuracies produced by decision trees at continental to global scales. IEEE Transactions on Geoscience and Remote Sensing, 37, (2, pt.2): 969-77.
Keywords: Decision trees; Feature extraction; Geophysical signal processing; Geophysical techniques; Image classification; Terrain mapping; Geophysical measurement technique; Land surface; Remote sensing; Land cover classification accuracy; Continental scale; Global scale; Feature selection; Classifier performance; avhrr ; Land cover type
Original Abstract: Classification of land cover from remotely sensed data at continental to global scales requires sophisticated algorithms and feature selection techniques to optimize classifier performance. The authors examine methods to maximize classification accuracies using decision trees to map land cover from multitemporal AVHRR imagery at continental and global scales. As part of their analysis they test the utility of "boosting", a new technique developed to increase classification accuracy by forcing the learning (classification) algorithm to concentrate on those training observations that are most difficult to classify. Their results show that boosting consistently reduces misclassification rates by 20-50% depending on the data set in question, and that most of the benefit gained by boosting is achieved after seven boosting iterations. They also assess the utility of including phenological metrics and geographic position as additional features to the classification algorithm. They find that using derived phenological metrics produces little improvement in classification accuracy relative to using an annual time series of NDVI data, but that geographic position provides substantial power for predicting land cover types at continental and global scales. However, in order to avoid generating spurious classification accuracies using geographic position, training data must be distributed evenly in geographic space.
 

Fruneau, B.; J. P. Rudant; D. Obert; D. Raymond, (1999). Small displacements detected by SAR interferometry on the city of Paris (France). IEEE 1999 International Geoscience and Remote Sensing Symposium. IGARSS'99 (Cat. No.99CH36293) Hamburg, Germany 28 June-2 July 1999
Piscataway, NJ, USA IEEE, pp.1943-5 vol.4.
Keywords: Geodesy; Geophysical techniques; Groundwater; Hydrological techniques; Remote sensing by radar; Synthetic aperture radar; Terrain mapping; Topography (Earth); Geophysical measurement technique; Hydrology; Land surface topography; Subsidence; InSAR; Displacement; SAR interferometry; Paris; France; City; Urban area; Slow deformation; Tandem image; ad 1993; ad 1994; ad 1995; ad 1996; Pumping ; Phreatic water
Original abstract: The feasibility of SAR interferometry for the detection of slow deformations on urban areas with standard atmospheric conditions is shown. The authors focus on the city of Paris (France), on which ten interferograms are derived from tandem images acquired during the period of July 28 1993, August 10 1996. The main limitation for this kind of measurements is due to tropospheric inhomogeneities, which lead to significant phase variations as high as one fringe. The best solution to compensate for the artifacts introduced by these inhomogeneities in the propagating medium appears to be the addition of interferograms. Then, a halo of subsidence, whose extension is about 600 m by 700 m is evidenced. It is precisely straight above an important working site: the construction of an underground station for the new "Eole" subway. This subsidence is produced by the lowering of the piezometric level, due to the pumping of the phreatic water.
 

Fuan, T.; W. Philpot (1998). Derivative analysis of hyperspectral data. Remote Sensing of Environment, 66, (1): 41-51.
Keywords: Data analysis; Fluorescence; Remote sensing; Spectral analysis; Vegetation mapping; Derivative spectral analysis; Hyperspectral data; High-resolution spectrally continuous remote sensing data; Smoothing algorithms; Spectral data sets; Interactive derivative analysis; Savitzky-Golay smoothing; Kawata-Minami smoothing; Mean-filter smoothing; Finite divided difference approximation algorithm; Convolution algorithm; Derivative computation procedures; Laboratory spectral data; Soybean fluorescence spectrum; Spectral feature extraction; Scaling effect; Band separations; Noise removal ; Sampling interval
Original Abstract: With the goal of applying derivative spectral analysis to analyze high-resolution, spectrally continuous remote sensing data, several smoothing and derivative computation algorithms have been reviewed and modified to develop a set of cross-platform spectral analysis tools. Emphasis was placed on exploring different smoothing and derivative algorithms to extract spectral details from spectral data sets. A modular program was created to perform interactive derivative analysis. This module calculated derivatives using either a convolution (Savitzky-Golay) or finite divided difference approximation algorithm. Spectra were smoothed using one of the three built-in smoothing algorithms (Savitzky-Golay smoothing, Kawata-Minami smoothing, and mean-filter smoothing) prior to the derivative computation procedures. Laboratory spectral data were used to test the performance of the implemented derivative analysis module. An algorithm for detecting the absorption band positions was executed on synthetic spectra and a soybean fluorescence spectrum to demonstrate the usage of the implemented modules in extracting spectral features. Issues related to smoothing and spectral deviation caused by the smoothing or derivative computation algorithms were also observed and are discussed. A scaling effect, resulting from the migration of band separations when using the finite divided difference approximation derivative algorithm can be used to enhance spectral features at the scale of specified sampling interval and remove noise or features smaller than the sampling interval.
 

Fujimura, S.; S. Kiyasu, (1997). A method for object-oriented feature extraction from hyperspectral data-generation of new channels by fusion of data. IGARSS'97. 1997 International Geoscience and Remote Sensing Symposium. Remote Sensing - A Scientific Vision for Sustainable Development (Cat. No.97CH36042) Singapore 3-8 Aug. 1997
New York, NY, USA IEEE, pp.975-7 vol.2.
Keywords: Feature extraction; Geophysical signal processing; Geophysical techniques; Image classification; Object-oriented methods; Remote sensing; Sensor fusion; Geophysical measurement technique; Land surface; Terrain mapping; Optical imaging; Multispectral remote sensing; Hyperspectral remote sensing; Data fusion; Image processing; Object-oriented method; New channel generation ; Supervised classification
Original abstract: Extracting significant features is essential for processing and transmission of a vast volume of hyperspectral data. Conventional ways of extracting features are not always satisfactory for this kind of data in terms of optimality and computation time. The authors present an object-oriented feature extraction method designed for supervised classification. After all the data are reduced and orthogonalized, a set of appropriate features for the prescribed purpose is extracted as linear combinations (fused channel) of the reduced components. Each dimension of hyperspectral data is weighted and fused according to the extracted features, which means the generation of new channels from hyperspectral data. Results of feature extraction are applied to evaluating the performance of sensors and to designing a new sensor.
 

Fujimura, S.; A. Yonenaga; S. Kiyasi, (1998). Application of an object-oriented feature extraction method to quantitative estimation from hyper-spectral data. IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings. (Cat. No.98CH36174) Seattle, WA, USA 6-10 July 1998
New York, NY, USA IEEE, pp.1061-3 vol.2.
Keywords: Feature extraction; Geophysical signal processing; Geophysical techniques; Geophysics computing; Object-oriented methods; Remote sensing; Geophysical measurement technique; Land surface; Terrain mapping; Optical imaging; Multispectral remote sensing; Image processing; Object oriented method; Quantitative estimation; Hyperspectral remote sensing ; Significant feature
Original abstract: Extracting significant features is essential for processing, storing and/or transmission of a vast volume of hyperspectral data. Conventional ways of extracting features are not always satisfactory for this kind of data in terms of optimality and computation time. The authors have already developed an object-oriented feature extraction method designed for supervised classification. They apply the basic idea of the approach to feature extraction for quantitative estimation from hyperspectral data. After the data obtained for various values of a quantity are orthogonalized and reduced by principal component analysis, the features describing the variation of spectra are extracted as linear combinations of the reduced components. An experiment using pigment shows that the feature extraction method for quantitative analysis yielded satisfactory results.
 

Fukuda, S.; H. Hirosawa, (1999). A wavelet-based texture feature set applied to classification of multifrequency polarimetric SAR images. IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings Seattle, WA, USA 6-10 July 1998
IEEE Trans. Geosci. Remote Sens. (USA), pp.2282-6.
Keywords: Feature extraction; Geophysical signal processing; Geophysical techniques; Image classification; Image texture; Radar imaging; Radar polarimetry; Remote sensing by radar; Synthetic aperture radar; Terrain mapping; Wavelet transforms; Geophysical measurement technique; Land surface; Radar remote sensing; Wavelet-based texture feature set; Multifrequency polarimetric SAR image; Land cover; Subimages; Wavelet decomposition; Downsampling; Flevoland site; Agricultural area; The Netherlands; Polarization selection; Feature reduction ; Holland
Original abstract: Texture is an essential key to the classification of land cover in SAR images. A wavelet-based texture feature set is derived. It consists of the energy of subimages obtained by the overcomplete wavelet decomposition of local areas in SAR images, where the downsampling between wavelet levels is omitted. The feature set has been successfully applied to multifrequency polarimetric images of the Flevoland site, an agricultural area in The Netherlands. The methods of polarization selection and feature reduction are also discussed.
 

Gaddis, L. R.; L. A. Soderblom; H. H. Kieffer; K. J. Becker; J. Torson; K. Mullins (1996). Decomposition of Aviris Spectra - Extraction of Surface-Reflectance, Atmospheric, and Instrumental Components. Ieee Transactions on Geoscience and Remote Sensing, V34, (N1): 163-178.
Keywords: AVIRIS , spectra decomposition, surface-reflectance
Original Abstract: Presents techniques that use only information contained within a raw, high-spectral-resolution, hyperspectral Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) scene to estimate and remove additive components (atmospheric scattering and instrument dark current). These techniques allow normalization of multiplicative components (instrument gain, topography, atmospheric transmission) and enhancement, extraction, and identification of relative-reflectance information related to surface composition and mineralogy. The authors' derivation of additive components from raw AVIRIS data is based on an adaptation of Crippen's "regression intersection method (RIM)." As does RIM, the authors use pairs of surface units that are spectrally homogeneous, spatially extensive, and located in rugged terrain. However, their technique utilizes the long-wavelength spectral data of AVIRIS to derive and remove atmospheric scattering components for each unit. AVIRIS data from the Kelso Dunes and Granite Mountain areas of southern California served as spectrally contrasting, topographically modulated surfaces for illustration of this technique. For a given site and wavelength pair, subtraction of the wavelength-dependent additive component from individual bands will remove topographic shading in both sites in band-to-band ratio images. Normalization of all spectra in the scene to the average scene spectrum results in cancellation of multiplicative components and produces a relative-reflectance scene. Absorption features due to mineral absorptions that depart from the average spectrum can be identified in the relative-reflectance AVIRIS product. The validity of these techniques is demonstrated by comparisons between relative-reflectance AVIRIS spectra derived from application of this technique and those derived by using the standard calibration techniques of JPL. Calibrated spectra were extracted from an AVIRIS scene of the Upheaval Dome area of Canyonlands National Park, UT. Results show that surface-reflectance information can be extracted and interpreted in terms of surface mineralogy after application of these techniques to AVIRIS data.
 

Gader, P.; J. M. Keller; H. Frigui; L. Hongwu; W. Dayou, (1998). Landmine detection using fuzzy sets with GPR images. 1998 IEEE International Conference on Fuzzy Systems Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36228) Anchorage, AK, USA 4-9 May 1998
New York, NY, USA IEEE, pp.232-6 vol.1.
Keywords: Fuzzy set theory; Object detection; Radar applications; Radar imaging; Landmine detection; Fuzzy sets; GPR images; Ground penetrating radar imaging system; 3D array; Intensity values; Multiple prototypes; Fuzzy clustering; Gradient features; Object prototypes; DARPA backgrounds data set; Mine lanes ; Roads
Original abstract: This paper describes a fuzzy set based approach to the detection of landmines using a novel ground penetrating radar (GPR) imaging system. The GPR produces a three-dimensional array of intensity values, representing a volume below the surface of the ground. Multiple prototypes are generated from fuzzy clustering of gradient features on training data, and a fuzzy confidence is then constructed for the test data from the "object" prototypes. This confidence plane is used to automatically detect objects, which are then scored by the ground truth information. Results on the training and testing with the DARPA backgrounds data set (open fields) and mine lanes (roads) are analyzed.
 

Gader, P. D.; M. Mystkowski; Z. Yunxin (2001). Landmine detection with ground penetrating radar using hidden Markov models. IEEE Transactions on Geoscience and Remote Sensing, 39, (6): 1231-44.
Keywords: Backscatter; Buried object detection; Geophysical techniques; Hidden Markov models; Military systems; Radar cross-sections; Radar theory; Remote sensing by radar; Terrain mapping; Terrestrial electricity; Geophysical measurement technique; Military system; Geoelectric method; Landmine; Mine detection; Unexploded ordnance; Radar remote sensing; Ground penetrating radar; Hidden Markov model; Radar signature; Moving vehicle; Radar scattering; Observation vector representation; Baum-Welch algorithm ; Land surface
Original Abstract: Novel, general methods for detecting landmine signatures in ground penetrating radar (GPR) using hidden Markov models (HMMs) are proposed and evaluated. The methods are evaluated on real data collected by a GPR mounted on a moving vehicle at three different geographical locations. A large library of digital GPR signatures of both landmines and clutter/background was constructed and used for training. Simple, but effective, observation vector representations are constructed to naturally model the time-varying signatures produced by the interaction of the GPR and the landmines as the vehicle moves. The number and definition of the states of the HMMs are based on qualitative signature models. The model parameters are optimized using the Baum-Welch algorithm. The models were trained on landmine and background/clutter signatures from one geographical location and successfully tested at two different locations. The data used in the test were acquired from over 6000 m/sup 2/ of simulated dirt and gravel roads, and also off-road conditions. These data contained approximately 300 landmine signatures, over half of which were plastic-cased or completely nonmetal.
 

Gamba, P.; B. Houshmand, (2001). Characterization of C-band and X-band InSAR data for 3D urban analysis. Proceedings of the 2001 IEEE Radar Conference (Cat. No.01CH37200) Proceedings of the 2001 IEEE Radar Conference Atlanta, GA, USA 1-3 May 2001
Piscataway, NJ, USA IEEE, pp.415-20.
Keywords: Microwave measurement; Radar resolution; Remote sensing by radar; Synthetic aperture radar; C-band; X-band; InSAR data; 3D urban analysis; SAR measurements; Los Angeles; nasa/jpl airsar; Intermap Star-3i system; Range measurements; Bald earth topography; 3D shapes; Ground resolution; Building analysis; Filtering ; Ad hoc algorithms
Original abstract: We compare C and X-band SAR measurements over the same urban area to understand which kind of information they are able to provide and which are the differences and similarities of the data sets. In particular, we consider data recorded over Los Angeles by the C-band NASA/JPL AIRSAR system and by the X-band Intermap Star-3i system. We analyze for both data sets the original range measurements as reconstructed after the phase unwrapping procedure, the bald earth topography that we were able to retrieve, and the 3D shapes of some of the buildings in the UCLA campus area. Our results show that, despite the lower resolution, AIRSAR data are still able to provide interesting views of an urban environment. The better ground resolution of the X-band system allows us to perform slightly better building analysis and extraction. Both systems suffer from large data drop out regions that prevent the original data from being immediately useful. However, it is still possible to extract the terrain height to some extent by means of a filtering procedure and to deduce built structure characteristics if suitable ad hoc algorithms are introduced.
 

Gamba, P.; B. Houshmand (2001). An efficient neural classification chain of SAR and optical urban images. International Journal of Remote Sensing, V22, (N8): 1535-1553.
Keywords:
Original Abstract: In this paper a suitable neural classification algorithm, based on the use of Adaptive Resonance Theory (ART) networks, is applied to the fusion and classification of optical and SAR urban images. ART networks provide a flexible tool for classification, but are ruled by a large number of parameters. Therefore, the simplified ART2-A algorithm is used in this paper, and the neural approach is integrated into a classification chain where fuzzy clustering for merging of classes is also considered. The interaction between the two methods leads to encouraging results in less CPU time than classification with fuzzy clustering alone or other classical approaches (ISODATA). Examples of classification are provided using C-band total power AIRSAR data and optical images of Santa Monica, Los Angeles.
 

Gamba, P.; B. Houshmand (2001). Integration of hyperspectral and IFSAR data for improved 3D urban profile reconstruction. Photogrammetric Engineering and Remote Sensing, V67, (N8): 947-956.
Keywords: 3D urban profile AVIRIS
Original Abstract: In this paper hyperspectral (AVIRIS) and radar (AIRSAR) aerial data acquired over urban environments are considered. The information available from each sensor was extracted and merged to improve the 3D profile reconstruction of builtup areas. Two classification schemes were evaluated for AVIRIS data clustering, while the effect of the radar view angle was considered in assessing the quality of the associated digital elevation models. A detailed analysis of what is possible to extract and to what extent these data are useful was also produced, considering precise 2D and 3D ground truth of the UCLA campus.
 

Gamba, P.; B. Houshmand (2000). Digital surface models and building extraction: a comparison of IFSAR and LIDAR data. IEEE Transactions on Geoscience and Remote Sensing, 38, (4, pt.2): 1959-68.
Keywords: Cartography; Feature extraction; Geophysical signal processing; Geophysical techniques; Radar imaging; Remote sensing by laser beam; Remote sensing by radar; Synthetic aperture radar; Terrain mapping; Geophysical measurement technique; Land surface; Image processing; Remote sensing; Digital surface model; Building extraction; Buildings; Urban area; Town; City; ifsar; lidar; Built structure; Interferometric SAR; Laser remote sensing ; Radar remote sensing
Synopsis: Discusses building extraction in DSMs, comparing results using both interferometric SAR and LIDAR data. Their automated extraction technique detects height and shape of buildings. Results show extracted buildings from LIDAR data show better shape characterization.
Original Abstract: The task of extracting significant built structure in digital surface models (DSM) is analyzed. The original data are obtained by means of interferometric SAR or LIDAR techniques and have different resolution and noise characteristics. This work aims to make a comparison of what (and how precisely) it is possible to detect and extract starting from these models, taking into account their differences but applying to them the same planar approximation approach. To this aim, data over Los Angeles and Denver is considered and evaluated. The results show that LIDAR data provide a better shape characterization of each building, and not simply because of their higher resolution. Indeed, less accurate results obtained starting from radar data are mainly due to shadowing/layover effects, which can be only partially corrected by means of the segmentation procedures. However, better results than those already presented in the literature could be achieved by using the IFSAR data correlation map.
 

Gamba, P.; B. Houshmand, (2000). Hyperspectral and IFSAR data for 3D urban characterization. IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120) Honolulu, HI, USA 24-28 July 2000
Piscataway, NJ, USA IEEE, pp.2611-13 vol.6.
Keywords: Geophysical signal processing; Geophysical techniques; Image processing; Multidimensional signal processing; Radar imaging; Remote sensing; Remote sensing by radar; Sensor fusion; Synthetic aperture radar; Terrain mapping; Geophysical measurement technique; Land surface; Multispectral method; sar; Data fusion; Urban area; Town; City; Hyperspectral remote sensing; Radar remote sensing; ifsar; Urban characterization; Three dimensional method; aviris; airsar; Hyperspectral classification; Built zone; Best footprint detection; Buildings; Building ; Terrain cover
Original abstract: AVIRIS and AIRSAR data over a urban environment are evaluated. The 2D maps available from hyperspectral classification are used to improve the detection and recognition of built zones starting from the IFSAR DEM. The improvements are twofold: best footprint detection provides a way to better reconstruct the 3D profile of individual buildings. Moreover, different terrain covers (e.g. trees) are recognized and discarded. Examples are provided over the UCLA campus in Los Angeles.
 

Gamba, P.; B. Houshmand, (1999). Three dimensional urban characterization by IFSAR measurements. IEEE 1999 International Geoscience and Remote Sensing Symposium. IGARSS'99 (Cat. No.99CH36293) IEEE 1999 International Geoscience and Remote Sensing Symposium. IGARSS'99 Hamburg, Germany 28 June-2 July 1999
Piscataway, NJ, USA IEEE, v. vol.5, pp.2401-3.
Keywords: Synthetic aperture radar , InSAR,Three dimensional urban characterization,ifsar,Machine vision
Synopsis: This paper proposes a building extraction algorithm for use with IFSAR data. Their goal is to detect height and shape of buildings. Algorithm is more effective in detecting height than detecting area.
Original abstract: In this paper a machine vision approach is applied to IFSAR data to extract the most relevant built structures in a dense urban environment. The algorithm tries to cluster primitives (line segments) into more complex surfaces (planes) to approximate the 3D shape of these objects. Very interesting results starting from TOPSAR data recorded over S. Monica are presented.
 

Gamba, P.; B. Houshmand, (1999). Three-dimensional road network by fusion of polarimetric and interferometric SAR data. IEEE 1999 International Geoscience and Remote Sensing Symposium. IGARSS'99 (Cat. No.99CH36293) Hamburg, Germany 28 June-2 July 1999
Piscataway, NJ, USA IEEE, pp.302-4 vol.1.
Keywords: Geophysical signal processing; Geophysical techniques; Image classification; Radar imaging; Radar polarimetry; Remote sensing by radar; Sensor fusion; Synthetic aperture radar; Terrain mapping; Geophysical measurement technique; Land surface; Land use; Radar remote sensing; Polarimetric radar; InSAR; sar; Road network; Three-dimensional method; Image processing; Fuzzy classification; Street pixel; Dynamic programming; Fuzzy membership function ; Urban infrastructure
Original abstract: In this paper a fuzzy classification procedure is applied to polarimetric radar measurements, and street pixels are detected. These data are successively grouped into consistent roads by means of a dynamic programming approach based on the fuzzy membership function values. Further fusion of the 2D road network extracted and 3D TOPSAR measurements provides a powerful way to analyze urban infrastructures.
 

Gamba, P.; B. Houshmand; B. Mercers; S. Schnick, (2000). 3D building profiles: comparison and fusion of LIDAR and IFSAR data. IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120) Honolulu, HI, USA 24-28 July 2000
Piscataway, NJ, USA IEEE, pp.984-6 vol.3.
Keywords: Geophysical signal processing; Geophysical techniques; Optical radar; Radar imaging; Remote sensing by laser beam; Remote sensing by radar; Sensor fusion; Synthetic aperture radar; Terrain mapping; Geophysical measurement technique; Land surface; Radar remote sensing; City; Urban area; Buildings; Building; 3D profile; Three dimensional structure; Laser remote sensing; lidar; ifsar ; sar
Original abstract: The authors analyze a data set composed of interferometric radar (IFSAR) and LIDAR measurements over a urban area. The data set horizontal resolution (2.5 meters) allows to characterize the major buildings in the studied area (Downtown Denver), and to make a comparison of the building 3D structure retrievable from the data. Furthermore, the integration of these two sensors, even if in a very preliminary forms, shows promising results. For instance, the problems affecting IFSAR measurements and due to multiple bouncing of the electromagnetic field in a crowded built area may be partially corrected by determining the building footprints by means of LIDAR data. Moreover, less expensive IFSAR data may be corrected from its layover and shadowing problems by exploiting LIDAR measurements on a sample area.
 

Gamba, P.; B. Houshmand; M. Saccani (2000). Detection and extraction of buildings from interferometric SAR data. IEEE Transactions on Geoscience and Remote Sensing, 38, (1, pt.2): 611-17.
Keywords: Geophysical signal processing; Geophysical techniques; Radar imaging; Remote sensing by radar; Synthetic aperture radar; Terrain mapping; Geophysical measurement technique; Land surface; Land use; Radar remote sensing; Urban scene; City; sar; Building; Feature extraction; Radar detection; Interferometric SAR; InSAR; Terrain elevation data; Machine vision approach; Local approximation; Three-dimensional data; Best-fitting planes; Height; Position ; Topographic surface
Synopsis: This is a journal version of the IGARSS '99 conference paper (Gamba, 2000). There are additional figures and description of their building extraction algorithm.
Original Abstract: The authors present a complete procedure for the extraction and characterization of building structures starting from the three-dimensional (3D) terrain elevation data provided by interferometric SAR measurements. Each building is detected and isolated from the surroundings by means of a suitably modified machine vision approach, originally developed for range image segmentation. The procedure is based on a local approximation of the 3D data by means of best-fitting planes. In this way, a building footprint, height and position, as well as its description with a simple 3D model, are recovered by a self-consistent partitioning of the topographic surface reconstructed from interferometric radar data.
 

Gamba, P.; M. Lilla; A. Mecocci, (1997). Extraction of discontinuous chains of symbols by means of perceptual grouping. Proceedings. International Conference on Image Processing (Cat. No.97CB36144) Santa Barbara, CA, USA 26-29 Oct. 1997
Los Alamitos, CA, USA IEEE Comput. Soc
Proceedings., pp.422-5 vol.2.
Keywords: Artificial intelligence; Feature extraction; Geographic information systems; Image recognition; Modules; Search problems; Discontinuous symbol chains extraction; Perceptual grouping; Algorithm; Digitized maps; Artificial intelligence kernel; Search strategy generation module; Pixels scanning; Symbol detection module; Cost function evaluation module; Global quality index; Gestalt rules; Grouping procedures optimisation ; Geographic information system
Original abstract: This paper proposes a new algorithm which applies perceptual grouping to track discontinuous chains of symbols in digitized maps. The procedure is based on an artificial intelligence kernel that supervises three different auxiliary processes: the search strategy generation module, responsible for the strategy to scan pixels; the symbol detection module that extracts the recognized symbols; the cost function evaluation module that assigns a global quality index to each symbol by considering the whole course of the line. Selected Gestalt rules are used to optimize the grouping procedures.
 

Gamba, P.; M. Lilla; A. Mecocci, (1997). A fast algorithm for target shadow removal in monocular colour sequences. Proceedings. International Conference on Image Processing (Cat. No.97CB36144) Proceedings of International Conference on Image Processing Santa Barbara, CA, USA 26-29 Oct. 1997
Los Alamitos, CA, USA IEEE Comput. Soc
Proceedings. International Conference on Image Processing (Cat. No.97CB36144)
Access restricted., pp.436-47 vol.1.
Original abstract: We present a fast algorithm to extract a shadow model from a monocular colour scene exploiting the hue, luminosity, saturation (HLS) colour components. The method allows one to recover target shapes in diurnal scene for improved identification and it is based on the definition of a global bitmap model and a more particular strip bitmap model to identify shadow regions. Each pixel in the image is then classified as shadow or target by a comparison with these models.
 

Gamba, P.; L. Lombardi, (1999). Coding scene contents using the image background. Proceedings IEEE International Conference on Multimedia Computing and Systems Proceedings of ICMCS99: IEEE Multimedia Systems '99: Florence, Italy 7-11 June 1999
Los Alamitos, CA, USA IEEE Comput. Soc, pp.860-4 vol.1.
Keywords: Boundary integral equations; Image coding; Image representation; Visual databases; Scene content coding; Image background; Scene coding approach; Spatial relations; Shape representation; Boundary Integral - Resonant Mode Expansion; Shape analysis; Vibration modes; Elastic sheet; Fixed boundary; Arbitrarily shaped object; BI-RME algorithm ; Scene background
Original abstract: We propose a scene coding approach that allows us to maintain the spatial relations among the individual objects and between these objects and the background by a suitable representation of their shapes. To this aim we apply the recently introduced Boundary Integral - Resonant Mode Expansion (BI-RME) approach for shape analysis, whose aim is to compute the vibration modes of an elastic sheet of fixed boundary to represent an arbitrarily shaped object. We demonstrate that the BI-RME algorithm is suitable to give contemporary and efficiently the shape representation for all the objects present in the original image. Moreover, it preserves the spatial relations by the analysis of the scene background, i.e. the part of an image left when all the meaningful objects have been extracted.
 

Gamba, P.; L. Lombardi (1999). Shape analysis with the *Boundary Integral-Resonant Mode Expansion' method. Image and Vision Computing, 17, (5-6): 357-64.
Keywords: Boundary integral equations; Image recognition; bi-rme; Shape analysis; Boundary Integral-Resonant Mode Expansion; Modal matching algorithm; Eigenfunctions; Helmholtz equation; Dirichlet boundary condition ; Vibration modes
Original Abstract: This paper proposes the applications of the Boundary Integral-Resonant Mode Expansion (BI-RME) method to the shape analysis problem, an approach originally implemented for the determination of modes of a cavity resonator. We explore its advantages for shape analysis and recognition of a BI-RME based modal matching algorithm, where each shape is represented with a set of eigenfunctions, and solutions of the Helmholtz equation with Dirichlet boundary condition. These solutions correspond to the vibration modes of an elastic sheet of arbitrary shape and fixed boundary and show some advantages over previous approaches. It is demonstrated that the BI-RME algorithm is particularly suitable for characterizing shapes with multiply connected boundaries and requires small cpu times.
 

Gamba, P.; L. Lombardi, (1997). Shape analysis by means of the *boundary integral-resonant mode expansion' method. Proceedings of the Third International Workshop on Visual Form. Advances in Visual Form Analysis Capri, Italy 28-30 May 1997
Singapore World Scientific, pp.227-36.
Keywords: Computer vision; Eigenvalues and eigenfunctions; Image recognition; Shape analysis; Boundary integral; Resonant mode expansion; Modal matching algorithm; Eigenfunctions; Helmholtz equation; Dirichlet boundary condition; Vibration modes; Elastic sheet; Arbitrary shape; BI-RME algorithm ; Multiply connected boundary
Original abstract: In this paper the application of the Boundary Integral-Resonant Mode Expansion (BI-RME) method to the shape analysis problem is proposed. We explore the advantages for shape analysis and recognition of a BI-RME based modal matching algorithm, where each shape is represented by means of a set of eigenfunctions, solutions of the Helmholtz equation with Dirichlet boundary condition. These solutions correspond to the vibration modes of an elastic sheet of arbitrary shape and fixed boundary and show some advantages over the previous approaches. It is demonstrated that the BI-RME algorithm is particularly suitable to characterize shapes with multiply connected boundary and requires small cpu-times.
 

Gamba, P.; A. Marazzi; A. Mecocci; P. Savazzi, (1996). A completely fuzzy classification chain for multispectral remote sensing images. IGARSS '96. 1996 International Geoscience and Remote Sensing Symposium. Remote Sensing for a Sustainable Future (Cat. No.96CH35875) Lincoln, NE, USA 27-31 May 1996
New York, NY, USA IEEE, pp.2071-3 vol.4.
Keywords: Geophysical signal processing; Geophysical techniques; Image classification; Remote sensing; Geophysical measurement technique; Land surface; Terrain mapping; Classification algorithm; Optical imaging; Multidimensional signal processing; Fuzzy classification chain; Multispectral remote sensing; fnp; Pyramidal approach; Training pixels ; Fuzzy nearest prototype
Original abstract: In this work a new classification algorithm that uses FNP mixed with a pyramidal approach is proposed. The prototypes of each class are generated by means of FCM with a FNP initialization. The aim of the work is to improve the performances of the usual non parametric classifiers by extracting the maximum information from the training pixels and from the pixels to be classified. This is done by using both the high spatial-correlation between pixels and the confidence levels, given by the fuzzy algorithm. Results are presented that show the improvement obtained by applying the proposed method to multispectral image classification.
 

Gamba, P.; A. Mecocci (1999). Perceptual grouping for symbol chain tracking in digitized topographic maps. Pattern Recognition Letters, 20, (4): 355-65.
Keywords: Cartography; Edge detection; Feature extraction; Group theory; Search problems; Symbol manipulation; Tracking; Symbol chain tracking; Digitized maps; Topographic maps; Artificial intelligence; Perceptual grouping; Search strategy generation module; Symbol detection module; Cost function evaluation module; Line detection ; Document analysis
Original Abstract: A new algorithm that applies perceptual grouping to detect and track discontinuous chains of symbols in digitized maps is proposed. The procedure is based on an artificial intelligence kernel that supervises three different auxiliary processes: the search strategy generation module that is responsible for the strategy to scan pixels; the symbol detection module that extracts the recognized symbols; the cost function evaluation module that assigns a global quality index to each symbol by considering the whole course of the line. Selected Gestalt rules are used to optimize the grouping procedures. After the algorithm discussion, the problem of the extraction of dotted and dashed lines from digitized topographic maps is discussed. Experimental results on many maps of the Istituto Geografico Militare Italiano show a very good performance: 92% of the discontinuous lines have been correctly chained, and the percentage of incorrectly classified symbols is also very small.
 

Gamba, P.; P. Savazzi, (1998). Classification of urban environments in SAR images: a fuzzy clustering perspective. IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings. (Cat. No.98CH36174) Seattle, WA, USA 6-10 July 1998
New York, NY, USA IEEE, pp.351-3 vol.1.
Keywords: Feature extraction; Geophysical signal processing; Geophysical techniques; Image classification; Radar imaging; Remote sensing by radar; Synthetic aperture radar; Geophysical measurement technique; Land surface; Terrain mapping; Town; City; Urban environment; sar; Radar remote sensing; Fuzzy clustering; Algorithm; SAR image; Pyramidal procedure; Green area; Street; Park; Buildings ; Fuzzy Bough transform
Original abstract: Fuzzy clustering algorithms are used for the interpretation of high resolution SAR images of urban environments. The idea is to define a pyramidal procedure suitable for the characterization first of more different environments (for instance, green areas, streets, and buildings). This rough analysis is then followed by more oriented fuzzy clustering tools, devoted to the extraction of more details: in this paper a modified fuzzy Bough transform is introduced and used to group pixels classified as pixels in consistent straight lines.
 

Gao, B. C.; K. B. Heidebrecht; A. F. H. Goetz (1993). Derivation of Scaled Surface Reflectances from Aviris Data. Remote Sensing of Environment, V44, (N2-3): 165-178.
Keywords:
 
 

Garro, A. J.; M. S. Vignale, (1996). Rhode Island Department of Transportation utilizing GIS for statewide design, construction and traffic program planning. URISA Proceedings, Annual Conference. Papers from the Annual Conference of the Urban and Regional Information Systems Association Proceedings of URISA 1996 Annual Meeting on Information Systems Salt Lake City, UT, USA 27 July-1 Aug. 1996
Washington, DC, USA Urban & Regional Inf. Syst. Assoc, pp.202-8.
Keywords: Geographic information systems; Scheduling; Traffic information systems; Rhode Island Department of Transportation; Statewide design; Traffic program planning; Transportation needs; Transportation system; GIS system; Highway infrastructure; Construction projects; Highway network; ridot; Rhode Island Geographic Information System ; Transportation improvement program
Original abstract: The Intermodal Surface Transportation Efficiency Act (ISTEA) of 1991 highlighted the importance of developing management systems to better identify and address our transportation needs and ensure a quality transportation system. Following this lead, the Rhode Island Department of Transportation (RIDOT) decided to implement a GIS system to aid in the overall management of its design, construction and traffic programs. As the state continues to improve and reconstruct its highway infrastructure and the number of design and construction projects increase, it has become more difficult to determine how these projects affect each other and the surrounding highway network. The system is designed to provide detailed information on design and construction projects throughout the state which allows the RIDOT to analyze and make intelligent decisions regarding scheduling and prioritizing of current projects. The base map selected for the project was developed by The Rhode Island Geographic Information System (RIGIS) in a cooperative effort with other state agencies and local groups. The database was designed to integrate relevant information available from several sections within the RIDOT into a single unique database. The development of the management system provides RIDOT with a valuable tool for the coordination of its overall transportation improvement program with minimal investment.
 

Gautam, N. C., (1997). IRS-1C applications for land use/land cover mapping, change detection and planning. IGARSS'97. 1997 International Geoscience and Remote Sensing Symposium. Remote Sensing - A Scientific Vision for Sustainable Development (Cat. No.97CH36042) Singapore 3-8 Aug. 1997
New York, NY, USA IEEE, pp.1775-7 vol.4.
Keywords: Agriculture; Cartography; Geophysical techniques; Remote sensing; Geophysical measurement technique; Land surface; Terrain mapping; Satellite remote sensing; Optical imaging; Visible; Infrared; Indian Remote Sensing satellite; irs 1c; Land use; Land cover; Change detection; Planning; Vegetation mapping; Wide-field Imaging Sensor (WiFS); Linear Imaging Self Scanning Sensor III; liss iii; Panchromatic sensor; Cadastral ; Urban application
Original abstract: Remote sensing applications using IRS-1A and IRS-1B data has successfully demonstrated the capabilities in generation of district-wise land use/land cover maps, depicting the information up to level-II on 1:250,000 scale which are being used as a basic input in land use planning of the 15 agro-climatic zones in the country. The launch of IRS-1C on 28 December, 1995 provided a new dimension in the application capabilities, in particular for land use/land cover mapping on various scales and levels for use by a diverse user community. An analysis has been made in the present paper on the capabilities of Wide-field Imaging Sensor (WiFS), Linear Imaging Self Scanning Sensor-III (LISS-III), Panchromatic sensor data for land use applications. It was observed from the above studies that WiFS data is useful in extracting land use/land cover information at Level-I for use at National/Regional level applications, LISS-III data useful in extraction of information at Level-II/III for use at District/Tehsil level applications and Panchromatic data has the capability to provide information at Level-III/IV for use in Cadastral and Urban applications.
 

Geling, G.; D. Ionescu, (1995). Further results on Kalman filters for speckle noise reduction on SAR images. 1995 Canadian Conference on Electrical and Computer Engineering (Cat. No.95TH8103) Montreal, Que., Canada 5-8 Sept. 1995
New York, NY, USA IEEE, pp.1152-5 vol.2.
Keywords: F. Gagnon
Original abstract: The modified adaptive block Kalman filter (MABKF) developed by Geling and Ionescu [1994] was designed to reduce the level of speckle in complex SAR images including urban regions where normal speckle assumptions are no longer true. In order to improve the performance of the filter two modifications have been developed. The MABKF filter methodology has been combined with a dynamic model using a symmetric full-plane region of support. Additionally, a multiplicative noise term has been added to the dynamic equation to model the highly variable nature of a complex urban scene containing many strong reflectors. The filters are demonstrated on an ERS-1 SAR image of Victoria, B.C.
 

Gingras, D., (1998). Optics and photonics used in road transportation. Opto-Contact: Workshop on Technology Transfers, Start-Up Opportunities,and Strategic Alliances Quebec, Canada 13-14 July 1998
SPIE-Int. Soc. Opt. Eng
Proc. SPIE - Int. Soc. Opt. Eng. (USA), pp.264-9.
Keywords: Active vision; Automated highways; Driver information systems; Image sensors; Laser ranging; Laser velocimetry; Optical scanners; Optical sensors; Road traffic; Surveillance; Video signal processing; Road transportation; Contactless measurements; Precise remote measurements; Photonics; Optical sensing; Automated traffic analysis; Road infrastructures diagnosis; Quality assessment; Smart driving; Intelligent vehicles; Safety; Inventories; Tolls; Various outdoor illumination conditions; 3D vision; Laser triangulation; Video traffic monitoring; Video image processing; Correlation-based velocimeter; Laser scanners ; Road sign recognition
Original abstract: Photonics is ideal for precise, remote and contactless measurements in harsh conditions. Thanks to major breakthroughs in the technologies involved, optical sensing is becoming more compact, robust and affordable. The purpose of this paper is to provide an overview on the capabilities of photonics applied to road transportation problems. In particular we will consider four types of situations: (1) measurements for traffic analysis and surveillance, (2) measurements for road infrastructures diagnosis and quality assessment, (3) photonics in smart driving and intelligent vehicles and (4) measurements for other purposes (safety, inventories, tolls, etc.). These topics will be discussed and illustrated by using the results of different projects that have been carried out at INO over the last few years. We will look at different challenges we had to face such as performing sensitive optical measurements in various outdoor illumination conditions and performing fast and accurate measurements without interfering with normal road traffic flow.
 

Gipps, P. G.; K. Q. Gu; A. Held; G. Barnett (2001). New technologies for transport route selection. Transportation Research Part C (Emerging Technologies), 9C, (2): 135-54.
Keywords: Photogrammetry; Transport route selection; Low cost high quality routes ; Alignment planning
Original Abstract: Planning a new road or railway can be an expensive and time-consuming process. There are numerous environmental issues that need to be addressed, and the problem is exacerbated where the alignment is also influenced by the location of services, existing roads and buildings, and the financial, social and political costs of land resumption. A comprehensive approach to the problem is available through the convergence of: geospatial imaging, softcopy photogrammetry, regional significance analysis and alignment optimisation. The first technology is concerned with obtaining low cost data containing far more information than was available in the past. The second two are concerned with extracting from that data, information essential to the planning process. The final technology is about automating the way alignments are generated to produce low cost, high quality routes. The convergence of these enabling technologies can have a major impact on the way that various jobs are performed-or whether they are done at all. Separately, they can have a major influence on a large number of disciplines, but taken in combination they can change the paradigm of alignment planning completely. By taking tasks that were previously difficult, time-consuming and expensive, and making them easy, fast and cheap, they can change completely the way alignments are planned.
 

Girard, S.; P. Guerin; H. Maitre; M. Roux, (1998). Building detection from high resolution color images. Image and Signal Processing for Remote Sensing IV Barcelona, Spain 21-23 Sept. 1998
SPIE-Int. Soc. Opt. Eng
Proc. SPIE - Int. Soc. Opt. Eng. (USA), pp.278-89.
Keywords: Geography; Geophysical signal processing; Image colour analysis; Image recognition; Image reconstruction; Image resolution; Remote sensing; Building detection; High resolution color images; Reconstruction; Dense urban areas; Aerial images; Dense digital elevation model; Sparse disparity map; Region-based segmentation; Noise; Complexity; Planar approximation; Fusion; Symmetrical regions; 3D object space; Bruxelles ; Suburb
Original abstract: We describe a new method for the detection and reconstruction of buildings in dense urban areas using high resolution aerial images. Our approach begins with the generation of a dense digital elevation model (DEM). A sparse disparity map is densified using a region-based segmentation of the left aerial image: each detected region is tested to be planar in the disparity map. A strategy is proposed to optimize the generation of these planar surfaces taking into account the noise present in the sparse disparity map and the robustness and complexity of different algorithms for planar approximation. The second step of our approach deals with the generation of building hypotheses. Based on the DEM previously computed, geometric and colorimetric criteria are used for the fusion of parallel regions, for the detection of symmetrical regions in the 3D object space and for the reconstruction of roof buildings. Experimental results are presented on a scene in the suburb of Bruxelles with color images at the resolution of 10 cm/pixel.
 

Goetz, S. J.; S. D. Prince; M. M. Thawley; A. J. Smith; R. Wright; M. Weiner, (2000). Applications of multi-temporal land cover information in the mid-Atlantic region: a RESAC initiative. IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120) Honolulu, HI, USA 24-28 July 2000
Piscataway, NJ, USA IEEE, pp.357-9 vol.1.
Keywords: Geophysical techniques; Remote sensing; Terrain mapping; Vegetation mapping; Geophysical measurement technique; Land surface; United States; usa; Multi-temporal land cover information; Mid-Atlantic region; resac; Image sequence; Regional Earth Science Applications Center; Maryland; Chesapeake Bay watershed; Satellite remote sensing; Change; Land use; Nutrient runoff; Urban sprawl; Farm; Agriculture ; Forest
Original abstract: The mid-Atlantic Regional Earth Science Applications Center (RESAC) was established in the Geography Department at the University of Maryland (UMD) by NASA's Earth Science Applications Program. The mid-Atlantic RESAC is to provide improved land cover mapping and ecological modeling capabilities for a diverse consortium of partners in government, academia, industry and NGOs within the 178000 km/sup 2/ Chesapeake Bay watershed. It is one of 7 regional centers established nationwide and leverages expertise in satellite remote sensing to address applications of regional significance including land cover change, land use planning, carbon exchange modeling, and integrated environmental monitoring. Examples of issues that are being addressed include nutrient runoff to the Chesapeake Bay, urban sprawl, farm and forest productivity, landscape fragmentation effects on biodiversity, a land manager decision support system, and educational outreach. The mid-Atlantic RESAC provides an example of how scientific advances can be focused on practical applications that challenge our ability to manage resources sustainably. A brief overview of the RESAC is provided and specific applications are reviewed using examples that emphasize the utility of remote sensing and GIS capabilities. Results of field activities undertaken during the 1999 growing season, for example, are used with a fusion of multi-temporal Landsat-7 Enhanced Thematic Mapper and SPOT panchromatic imagery to classify vegetation types, and to characterize development of the severe drought that took place in the region.
 

Goforth, M. A., (1998). Fusion of differing resolution imagery using multiresolution analysis. Proceedings of the International Conference on Multisource-Multisensor Information Fusion. FUSION '98 Las Vegas, NV, USA 6-9 July 1998
Athens, GA, USA CSREA Press, pp.419-26 vol.1.
Keywords: Feature extraction; Geophysical signal processing; Image classification; Image matching; Image resolution; Minimisation; Optical transfer function; Remote sensing; Sensor fusion; Spectral analysis; Data fusion; Multiresolution analysis; Panchromatic imagery; Spatial resolution; Low-resolution spectral imagery; Spatial/spectral sharpening; mra/mtf; Modulation transfer function; Detail extraction; Spectral distortion minimization; Classification maps; Spectral fidelity; Landsat imagery; Aerial photography ; ERDAS Imagine
Original abstract: High-resolution panchromatic imagery can be used to increase the spatial resolution of low-resolution spectral imagery through spatial/spectral sharpening techniques. A model for fusion of data from sensors with differing resolutions, called MRA/MTF, is presented. Before fusion of imagery with differing resolution, the images are matched in their spatial response through a correction to their modulation transfer function (MTF). The spatial detail is extracted from the high-resolution image by multiresolution analysis (MRA) and applied to the low-resolution image in a way that minimizes the spectral distortion of the image so that accurate classification maps can be derived from the sharpened imagery. This presentation of the spectral fidelity is demonstrated visually as well as quantitatively for Landsat imagery sharpened with aerial photography and compared with other resolution enhancement algorithms available within ERDAS Imagine.
 

Goncalves, M. L., (1999). A neural system for remote sensing multispectral image classification. Neural Nets WIRN VIETRI-98. Proceedings of the 10th Italian Workshop on Neural Nets Salerno, Italy 21-23 May 1998
London, UK Springer-Verlag London, pp.218-23.
Keywords: Feature extraction; Image classification; Multilayer perceptrons; Self-organising feature maps; Unsupervised learning; Remote sensing; Multispectral image classification; Neural system; Artificial neural networks; Kohonen self-organizing map; Classification ; Multilayer Perceptron
Original abstract: This work presents a system for Remote Sensing (RS) multispectral image classification based on Artificial Neural Networks (ANN), aiming at two objectives, namely: searching of techniques for improving the performance in the classification task and to exploit the advantages of unsupervised learning for feature extraction. The system is divided in two phases: feature extraction by the Kohonen Self-Organizing Map (SOM) and classification by a Multilayer Perceptron (MLP) network, trained by a learning algorithm which uses 2nd-order information exactly calculated. To evaluate the efficiency of this classification scheme, a comparative analysis with the maximum likelihood algorithm, conventionally used for RS multispectral images classification, is realized.
 

Goncalves, M. L.; M. L. de Andrade Netto; J. Zullo Junior, (1998). A neural architecture for the classification of remote sensing imagery with advanced learning algorithms. Neural Networks for Signal Processing VIII. (Cat. No.98TH8378) Proceedings of the 1998 IEEE Signal Processing Society Workshop Cambridge, UK 31 Aug.-2 Sept. 1998
New York, NY, USA IEEE, pp.577-86.
Keywords: Feature extraction; Image classification; Multilayer perceptrons; Neural net architecture; Remote sensing; Self-organising feature maps; Unsupervised learning; Neural architecture; Multispectral images; Kohonen self-organizing map; Multilayer perceptron ; LANDSAT/TM image
Original abstract: This work presents an artificial neural networks based architecture for the classification of remote sensing (RS) multispectral imagery. The architecture consists of two processing modules: an image feature extraction module using Kohonen self-organizing map and a classification module using multilayer perceptron network. The architecture was developed aiming at two specific goals: to exploit the advantages of unsupervised learning for feature extraction, and the testing of techniques to increase the learning algorithm's performance concerning training time. To test the applicability of this work, the architecture was applied to the classification of a LANDSAT/TM image segment from a pre-selected testing area and its performance was compared with that of a maximum likelihood classifier, conventionally used for RS multispectral images classification.
 

Gong, P.; J. Wang, (1997). Road network extraction from airborne digital camera images: a multi-resolution comparison. IGARSS'97. 1997 International Geoscience and Remote Sensing Symposium. Remote Sensing - A Scientific Vision for Sustainable Development (Cat. No.97CH36042) Singapore 3-8 Aug. 1997
New York, NY, USA IEEE, pp.895-7 vol.2.
Keywords: Feature extraction; Geophysical signal processing; Geophysical techniques; Image classification; Image resolution; Remote sensing; Geophysical measurement technique; Land surface; Terrain mapping; Optical imaging; Multispectral remote sensing; Visible; Infrared; Urban area; Suburban area; Road network extraction; Airborne digital camera image; Multiresolution comparison; Advanced linear analysis; Gradient direction profile analysis; Algorithm; Clustering; Contextual classifier; Context; Image clustering ; Morphologically filtered image
Original abstract: As image resolution increases from 10-30 m to 0.5-2 m, road networks will appear to be narrow areas rather than thin lines. This becomes a challenge for traditional linear analysis methods based on mask operations but creates an opportunity for classification based methods. The authors experimented with an advanced linear analysis, gradient direction profile analysis, and a few classification algorithms including a maximum classification, clustering and a contextual classifier for road network extraction using airborne digital camera data acquired over Livermore, California with approximately 1.6 m spatial resolution. Results indicate that both the linear extraction and image clustering algorithms worked reasonably well. The best road network results have been obtained by applying the linear extraction algorithm to a morphologically filtered image that was generated by combining the near infrared (NIR) and red (R) image bands through NIR/R+NIR. With this method, the correctly extracted road pixels account for 78.7% of the total road pixels obtained from image interpretation with field verification. The image clustering method resulted in 74.5% correctly extracted road pixels. When experimenting with the images resampled at approximately 3 m and 5 m resolution, the best overall accuracies for road extraction decreased to 74.6% and 61.6%, respectively.
 

Goodchild, M. F. (2000). GIS and transportation: status and challenges. GeoInformatica, 4, (2): 127-39.
Keywords: Cartography; Computerised navigation; Geographic information systems; Transportation; Visual databases; gis-t; Map view; Navigational view; Behavioral view; Inventory; Description; Accuracy; Interoperability; Connectivity; Planarity; Time-dependent attribute storage; Lane-level connectivity; Standards; Representation; Unambiguous communication; Economic models ; New technology response
Original Abstract: The evolution of GIS-T is characterized in three stages: the map view, navigational view, and behavioral view. The static nature of the map view favors applications related to inventory and description, and raises difficult questions of accuracy and interoperability. The navigational view adds concerns for connectivity and planarity, and the storage of time-dependent attributes. Navigation also raises issues of representation related to scale, including the need for lane-level connectivity. The behavioral view stems from the work of Hagerstrand (1970), treating transportation events as dynamic and occurring within the largely static transportation space. Appropriate representations for the behavioral view have still to be worked out. In all three cases the legacies of prior technologies and perspectives are still evident. The paper presents a series of research challenges, dealing with standards, representation, unambiguous communication, economic models, response to new technologies, and application of knowledge gained from GIS-T and ITS research to other fields.
 

Gosinski, T.; S. Avila, (1995). Implementing a regional traffic data management system. URISA Proceedings. Papers from the Annual Conference of the Urban and Regional Information Systems Association Proceedings of 33rd Annual URISA Conference San Antonio, MN, USA 16-20 July 1995
Washington, DC, USA Urban & Regional Inf. Syst. Assoc, pp.735-43.
Keywords: Geographic information systems; Government data processing; Legislation; Road traffic; Town and country planning; Traffic information systems; Regional traffic data management system; Intermodal Surface Transportation Efficiency Act; Clean Air Act Amendment; Transportation decision-making; Local governments; Regional governments; Metropolitan planning organizations; Transportation data collection activities; Technical resources; Collected data sets integration; Transportation project assessment; User access; Houston-Galveston Area Council; Desktop client-server system; Innovative System Developers Inc.; gis; Graphical user interface; Inter-agency users; Intra-agency users; Integrated modeling environment ; Transportation planning
Original abstract: The development of the Intermodal Surface Transportation Efficiency Act (ISTEA) and the Clean Air Act Amendment (CAAA) expands the transportation decision-making role of local and regional governments. This increased importance of decision-making in transportation issues requires increased attention to both the justification and analysis of transportation initiatives. Therefore, metropolitan planning organizations (MPOs) must coordinate transportation data collection activities and maximize available technical resources. Integrating collected data sets (such as traffic counts, vehicle mixes, roadway characteristics, functional classifications, employer statistics and land use information) are vital for the assessment of transportation projects. Combining data with analytical tools and providing access to all users enhances the success of programs such as air quality control, employer trip reduction, management system development and other mandated requirements of ISTEA and CAAA. The Houston-Galveston Area Council (H-GAC), which is the Houston area MPO, is addressing these issues by developing a desktop, client-server traffic data management system (TDMS). Furthermore, H-GAC has teamed up with Innovative System Developers Inc. in utilizing GIS technologies to allow transportation professionals to efficiently store, display, query, analyze and disseminate information. The TDMS includes a graphical user interface which allows both inter- and intra-agency users to employ an integrated modeling environment in support of transportation planning and programs.
 

Gouinaud, C.; F. Tupin; H. Maitre, (1996). Potential and use of radar images for characterization and detection of urban areas. IGARSS '96. 1996 International Geoscience and Remote Sensing Symposium. Remote Sensing for a Sustainable Future (Cat. No.96CH35875) Lincoln, NE, USA 27-31 May 1996
New York, NY, USA IEEE, pp.474-6 vol.1.
Keywords: Geophysical techniques; Radar imaging; Remote sensing by radar; Spaceborne radar; Land surface; Terrain mapping; Radar remote sensing; Geophysical measurement technique; Radar image; Urban area; Town; City; ers-1; Man-made structure; Captor response; Detection method; Landscape; Aix-en-Provence; Kourou; French Guyana ; France
Original abstract: The resolution of ERS-1 images should let allow man-made structures like urban areas to be detected. After a brief survey of the captor response to urban objects, the authors propose a method to detect urban areas. They illustrate the results obtained on two typical landscapes: European agricultural hilly landscapes and tropical zones. Some urban detections are presented both on Aix-en-Provence and Kourou towns in French Guyana.
 

Gouinaut, C.; I. Pons, (1996). Use of geometrical SAR simulation for visibility prediction: application to mission planning and urban study. IGARSS '96. 1996 International Geoscience and Remote Sensing Symposium. Remote Sensing for a Sustainable Future (Cat. No.96CH35875) Lincoln, NE, USA 27-31 May 1996
New York, NY, USA IEEE, pp.257-9 vol.1.
Keywords: Geophysical techniques; Radar imaging; Remote sensing by radar; Spaceborne radar; Synthetic aperture radar; Geophysical measurement technique; Radar remote sensing; View direction; Terrain mapping; Land surface; City; Town; Urban area; Geometrical simulation; sar; Visibility prediction; Observability prediction; Geometrical distortion; SAR image; Shadow; Lay over; Multiincidence radar image; Digital elevation model; Ray-tracing; Radar geometry; Incidence angle ; Mission planning
Original abstract: The specification of future radar satellites and many remote-sensing applications need information about the geometrical distortions seen in a SAR image. The main geometrical distortions are those that are called "shadow" and "lay-over"; it is very difficult to quantify them with a lone SAR image, but the use of many SAR images allows a numerical evaluation of these distortions. Unfortunately not only is this procedure very expensive, but also, before the launch of RADARSAT only SIR C produced satellite multiincidence radar images. On the contrary, digital elevation models are easy to access, for a large variety of countries and landscapes. The authors show the interest of geometrical SAR simulations in order to estimate the probability of geometrical distortions and extract practical information concerning visibility. They describe their approach of SAR simulation, based on an adaptation of ray-tracing to radar geometry, and expose two specific applications. The first one is used to specify the best incidence angle for the simulation with a representative DEM base (100000 km/sup 2/), and the second one is used to predict the visibility of urban objects with specific satellites. This work is based on incidence angle specification for RADARSAT III, and emphasizes the radar potential for urban study.
 

Goulias, D. G.; K. G. Goulias, (2000). GIS in pavement and transport management. Management Information Systems 2000. Second International Conference on Management Information Systems Incorporating GIS and Remote Sensing. Udine, Italy May 2000
Southampton, UK WIT Press, pp.165-75.
Keywords: Civil engineering computing; Emergency services; Geographic information systems; Traffic information systems; Transportation; Visual databases; gis; Pavement management; Transport management; Transportation planning; Spatial analysis; Time dependent analysis; Highway engineering; gis-t; Maintenance data; Cost models; Emergency management; Human behavior models; Demographic information ; Land-use information
Original abstract: The use of geographic information systems in transportation (GIS-T) can greatly enhance spatial and time dependent analysis. Its use in highway engineering and transportation planning/operations has been significantly intensified since GIS permits the assimilation, integration, modeling, and visualization of time and space related data and predictions. This paper presents two representative case studies on the development and use of GIS-T in: (i) pavement management and highway analysis, integrating performance models, user and agency cost models and pavement condition information (in terms of inventory and maintenance data); and (ii) emergency management and traffic operations, integrating models of human behavior, transportation network characteristics, and detailed regional demographic and land-use information. In the development of these GIS based management systems, temporal and spatial modeling was used for describing spatio-temporal phenomena and predicting future conditions. The methodologies illustrated can be adapted in other regions, and the GIS based systems are flexible enough to allow for the integration of any models representing local and/or regional conditions elsewhere.
 

Gracia, I.; M. Petrou; A. J. Fraser, (1998). Line tracking from satellite images. Image and Signal Processing for Remote Sensing IV Barcelona, Spain 21-23 Sept. 1998
SPIE-Int. Soc. Opt. Eng
Proc. SPIE - Int. Soc. Opt. Eng. (USA), pp.261-7.
Keywords: Buried object detection; Edge detection; Feature extraction; Image texture; Nonlinear filters; Optical tracking; Remote sensing; Line tracking; Satellite images; Detection; Buried linear features; Surface coverage; Buried structure; Contrast; Texture; Over-ground growth; Aerial photographs; Statistical nonlinear filters; Enhancement; Lateral continuity ; Arbitrary shape
Original abstract: We present an algorithm for the detection and tracking of buried linear features under a variety of surface coverages. The buried structures manifest themselves as a few pixels wide bands with contrast and texture changes of the over-ground growth, in high 1 m resolution aerial photographs. Some statistical non-linear filters are used to enhance these features, and their response is further enhanced by lateral continuity, taking into consideration prior knowledge about the shape of the feature.
 

Grau, A.; J. Climent; J. Aranda, (1998). Terrain segmentation by structural texture discrimination. Image and Signal Processing for Remote Sensing IV Barcelona, Spain 21-23 Sept. 1998
SPIE-Int. Soc. Opt. Eng
Proc. SPIE - Int. Soc. Opt. Eng. (USA), pp.339-44.
Keywords: Image segmentation; Image texture; Remote sensing; Structural texture discrimination; Terrain segmentation; Texture print; Texture analysis; Gray level intensity function; Image region size; Histograms; String-to-string correction problem; Placement rules; Primitives; Elements; Texture regions; Distance measure; Minimum-cost sequences; Edit operations; Leveshtein distance; Algorithm; Urban areas ; Rural areas
Original abstract: We present a new algorithm to generate the texture print of a region in an image. For this texture analysis, a texture print is found by means of counting the number of changes in the sign of the derivative in the gray level intensity function by rows and by columns, over a region with size N*N. These two histograms are represented as a unique string R of symbols. Therefore, a string-to-string correction problem as placement rules of elements (primitives) obtained statistically is used. In order to discriminate different texture regions a distance measure on strings based on minimum-cost sequences of edit operations is computed, this measure is the Leveshtein distance. The proposed algorithm is useful to discriminate between urban areas and rural areas due to the change in their textural aspect.
 

Green, R. O.; M. L. Eastwood; C. M. Sarture; T. G. Chrien; M. Aronsson; B. J. Chippendale; J. A. Faust; B. E. Pavri; C. J. Chovit; M. S. Solis; M. R. Olah; O. Williams (1998). Imaging spectroscopy and the Airborne Visible Infrared Imaging Spectrometer (AVIRIS). Remote Sensing of Environment, V65, (N3): 227-248.
Keywords: AVIRIS sensor
Original Abstract: Imaging spectroscopy is of growing interest as a new approach to Earth remote sensing. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) was the first imaging sensor to measure the solar reflected spectrum from 400 nm to 2500 nm at 10 nm intervals. The calibration accuracy and signal-to-noise of AVIRIS remain unique. The AVIRIS system as well as the science research and applications have evolved significantly in recent years. The initial design and upgraded characteristics of the AVIRIS system are described in terms of the sensor, calibration, data system, and flight operation. This update on the characteristics of AVIRIS provides the context for the science research and applications that use AVIRIS data acquired in the past several years. Recent science research and applications are reviewed spanning investigations of atmospheric correction, ecology and vegetation, geology and soils, inland and coastal waters, the atmosphere, snow and ice hydrology, biomass burning, environmental hazards, satellite simulation and calibration, commercial applications, spectral algorithms, human infrastructure, as well as spectral modeling.
 

Growe, S.; R. Tonjes, (1998). Use of explicit knowledge and GIS data for the 3D evaluation of remote sensing images. Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170) Brisbane, Qld., Australia 16-20 Aug. 1998
Los Alamitos, CA, USA IEEE Comput. Soc, pp.1413-15 vol.2.
Keywords: Data visualisation; Feature extraction; Geographic information systems; Image reconstruction; Image registration; Image texture; Knowledge based systems; Remote sensing; Stereo image processing; Remote sensing images; Image interpretation; Semantic nets; Digital landscape model; Geographic information system; Real time visualization; 3D geometry ; Polygon mesh
Original abstract: The evaluation of 3D scenes observed from different sensors requires the co-registration of sensor images and the reconstruction of the 3D geometry. To solve both tasks the presented system exploits prior knowledge, represented explicitly by semantic nets, and uses a digital landscape model of a geographic information system (GIS) as a hint for the object location. This is shown for the detection of control points for image registration and the extraction of objects (roads, buildings) for 3D reconstruction. For real time visualization the 3D geometry is approximated by a polygon mesh with overlaid photo texture.
 

Growe, S.; R. Tonjes, (1997). A knowledge based approach to automatic image registration. Proceedings. International Conference on Image Processing (Cat. No.97CB36144) Santa Barbara, CA, USA 26-29 Oct. 1997
Los Alamitos, CA, USA IEEE Comput. Soc, pp.228-31 vol.3.
Keywords: Feature extraction; Geographic information systems; Image matching; Image registration; Knowledge based systems; Radar imaging; Remote sensing; Remote sensing by radar; Synthetic aperture radar; Knowledge based approach; Automatic image registration; Automatic control point matching; Remotely sensed images; Flight parameters; Sensor specific appearance; Prior knowledge; Control points; gis; Semantic nets; Rules; A*-algorithm; Crossroads; Aerial imagery ; SAR imagery
Original abstract: The presented work addresses the problem of automatic control point matching for the registration of remotely sensed images. The inaccuracy of flight parameters and the sensor specific appearance of objects are the difficulties automatic registration suffers from. To overcome these problems the presented system uses prior knowledge to select appropriate structures for matching, i.e. control points, from a GIS and to extract their corresponding features from the sensor data. The knowledge is represented explicitly using semantic nets and rules. The best correspondence between the GIS data and the image is found by an A*-algorithm. The automatic control point matching is demonstrated for crossroads in aerial and SAR imagery.
 

Guindon, B., (1998). Application of spatial reasoning methods to the extraction of roads from high resolution satellite imagery. IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings. (Cat. No.98CH36174) Seattle, WA, USA 6-10 July 1998
New York, NY, USA IEEE, pp.1076-8 vol.2.
Keywords: Feature extraction; Geophysical signal processing; Geophysical techniques; Image recognition; Remote sensing; Geophysical measurement technique; Land surface; Terrain mapping; Image processing; Spatial reasoning method; Road; Highway; High resolution satellite imagery; High resolution imaging; Rule-based recognition algorithm; Residential street; Urban scene; Town ; City
Original abstract: By the end of this decade the civilian remote sensing community will have access to timely satellite imagery at high spatial resolution (1-3 meters). This will open the door for new applications, such as detailed topographic mapping. These data can be considered to be in a *transition' spatial resolution regime between conventional, low resolution satellite imagery and aerial photography. Correspondingly, information extraction methodologies to exploit these data must draw on both the data-driven, per-pixel processing of conventional satellite image analysis and the object-driven, image understanding technologies now being developed for aerial photography. This paper describes experiments to evaluate rule-based recognition algorithms for the purpose of automating planimetric feature extraction from these new satellite data. The overall feature extraction strategy is one drawn from image understanding namely spatial reasoning with a segmented rendition of the image. Recognition involves applying a set of evidence-accumulation attribute (inherent spatial/spectral and context) tests to selected segments in order to identify candidates which may form all or part of an object of interest. Conventional classification *training' has been modifed to develop a novel approach to evidence weight quantification and to assess inter-test correlation, analogous to conventional covariance. A recognition system has been developed to recognize residential streets in imagery.
 

Gunawardena, A.; J. Schroeder, (1998). Polynomial Hough transform based feature extraction from SAR imagery. EUSAR'98. European Conference on Synthetic Aperture Radar Proceedings of EURSAR '98: Friedrichshafen, Germany 25-27 May 1998
Berlin, Germany VDE VERLAG GMBH, pp.273-6.
Keywords: Edge detection; Feature extraction; Hough transforms; Matched filters; Polynomials; Radar imaging; Remote sensing by radar; Synthetic aperture radar; Polynomial Hough transform; SAR imagery; Curvilinear features; Roads; Rivers; Edge detector; 2-D Gaussian kernel; Matched filtering; Hough space; Thresholding ; Real SAR data
Original abstract: This paper proposes a processing scheme for extraction of curvilinear features such as roads and rivers from synthetic aperture radar (SAR) imagery. The processing consists of three stages. The first stage is an edge detector operating on data smoothed by a 2-D Gaussian kernel. The second stage is a polynomial Hough transform. The final stage consists of matched filtering in the Hough space followed by thresholding. The performance of the proposed processing scheme is demonstrated using real SAR data.
 

Haala, N.; C. Brenner (1999). Extraction of buildings and trees in urban environments. Isprs Journal of Photogrammetry and Remote Sensing, V54, (N2-3): 130-137.
Keywords: feature extraction airborne laser scanning
Synopsis: Discusses use of ALS in urban settings, extraction of urban features. Their method: combine multispectral information from color images with geometric information from laser scanner DSM.
Original Abstract: In this article, two methods for data collection in urban environments are presented. The first method combines multispectral imagery and laser altimeter data in an integrated classification for the extraction of buildings, trees and grass-covered areas. The second approach uses laser data and 2D ground plan information to obtain 3D reconstructions of buildings.
 

Haala, N.; C. Brenner (1998). Interpretation of urban surface models using 2D building information. Computer Vision and Image Understanding, 72, (2): 204-14.
Keywords: Computer vision; Feature extraction; Geographic information systems; Image reconstruction; Image segmentation; Object recognition; Remote sensing; Stereo image processing; Urban surface models; 2D building images; 3D image reconstruction; Image interpretation; Digital surface models; Stereo image matching; Aerial images; Surface geometry; Planar surfaces ; Geographic information system
Original Abstract: In 3D building reconstruction the interpretation process can be simplified if digital surface models (DSM), which can either be derived from stereo matching of aerial images or be directly measured by scanning laser systems, are used in addition to or instead of image data. The images contain much information, but the resulting complexity causes enormous problems for an automatic interpretation of this data type. Since the information of a DSM is restricted to surface geometry its interpretation is simplified by the absence of unnecessary details. Nevertheless, due to insufficient spatial resolution and quality of the DSM, especially for these applications, optimal results can only be achieved by the use of additional data sources. Within the approach presented the segmentation of planar surfaces from the DSM is supported by existing ground plans. This 2D building information is also used to derive hypotheses on the possible roof shapes in order to obtain a 3D boundary representation based on the segmented planes.
 

Hae Yeoun, L.; P. Wonkyu; L. Heung-Kyu; K. Tak-gon, (2000). Towards knowledge-based extraction of roads from 1 m-resolution satellite images. 4th IEEE Southwest Symposium on Image Analysis and Interpretation Proceedings Austin, TX, USA 2-4 April 2000
Los Alamitos, CA, USA IEEE Comput. Soc, pp.171-6.
Keywords: Computer vision; Feature extraction; Gradient methods; Image resolution; Image segmentation; Knowledge based systems; Remote sensing; Knowledge-based extraction; Road extraction; Satellite images; IKONOS satellite; Mapping; Spaceborne images; Photogrammetry; Road region extraction; Approximated road regions; Region segmentation; Hierarchical watershed transformation; Multi-scale gradient watershed transformation; Road gray level; Elongatedness ; Connectedness
Original abstract: As the IKONOS satellite with 1 m-resolution camera was launched in 1999, mapping using spaceborne images will be an important issue in the computer vision area as well as photogrammetry, mainly because most major man-made objects of interest can be identifiable. One of the automatically identifiable objects of importance may be roads. Detecting roads using edge detection approaches may be very difficult because a number of edge elements from such as buildings, etc., can be generated from edge detector. In this paper, we propose a method for the extraction of approximated road regions based on region segmentation that utilizes region information. Our method consists of the following three steps. First, an image is segmented using the modified hierarchical multi-scale gradient watershed transformation. Then, the road candidates are identified using information about road gray level, elongatedness and connectedness. The identified road candidates are expanded by connecting the close-by roads knowing that roads are connected objects. Our method was tested on the simulated spaceborne images and the result shows that the automation of road extraction is quite promising.
 

Hagg, W.; K. Segl; M. Sties, (1995). Classification of urban areas in multi-date ERS-1 images using structural features and a neural network. 1995 International Geoscience and Remote Sensing Symposium, IGARSS '95. Quantitative Remote Sensing for Science and Applications (Cat. No.95CH35770) Firenze, Italy 10-14 July 1995
New York, NY, USA IEEE, pp.901-3 vol.2.
Keywords: Feature extraction; Geophysical signal processing; Geophysical techniques; Image classification; Image sequences; Image texture; Neural nets; Radar applications; Radar imaging; Remote sensing by radar; Spaceborne radar; Synthetic aperture radar; Geophysical measurement technique; Radar remote sensing; Image processing; SAR image; Land surface; Terrain mapping; Urban area; Multi-date ERS-1 image; Image sequence; Structural feature; Neural network; Neural net; Inhomogeneity ; RBF-Network
Original abstract: Describes a new method to extract structural informations from images. The loss of spatial resolution and distortions-from edges, as it occurs with standard texture algorithms, are reduced to a minimum. Furthermore, the authors describe the inhomogeneity by three different structure types according to the structures contained in SAR images. Finally they use a neural network (RBF-Network) to get a more precise classification of urban areas from SAR images.
 

Haley, L., (1997). Integrating GIS and Oracle for traffic analysis. Proceedings AM/FM International Proceedings of AM/FM International's Annual Conference *Entering the Mainstream' Nashville, TN, USA 23-26 March 1997
Aurora, CO, USA AM/FM Int, pp.209-17.
Keywords: Geographic information systems; Graphical user interfaces; Integrated software; Planning; Public administration; Relational databases; Traffic engineering computing; Transportation; Software integration; Oracle; City of Bloomington; am/fm/gis; Relational database; Data tables; GenaMap; Traffic engineers; Transportation planners; Traffic accident report; Traffic count; Graphical user interface ; GENIUS II GUI builder
Original abstract: The City of Bloomington initiated the development of an AM/FM/GIS system in 1989. A completed base map of land-based features and water, wastewater, and storm water systems has been in place since early 1994. The City's initial focus was on maintaining its base map, expanding map features related to planning, public works, and utilities, and developing end-user applications for basic viewing, outputting, and querying map information. The City views GIS as part of a larger information management system and is now working towards integrating GIS with other data systems to serve end-user needs across departmental boundaries. With this goal in mind, the City is developing applications to integrate Oracle relational database software data tables with its GenaMap GIS software. One of the first applications projects involved creating a traffic analysis application for traffic engineers and transportation planners. Data tables were designed for traffic accident report, traffic count, and thoroughfare data and linked to the GIS road centerline network. Staff also entered intersection condition diagrams into the GIS. End-users can display, manipulate, and output graphic and ancillary information through a custom graphical user interface (GUI) created with GenaMap's GENIUS II GUI builder.
 

Hardin, P. J., (1999). Neural networks vs. nonparametric neighbor-based classifiers for semisupervised classification of Landsat imagery. Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation II Denver, CO, USA 19-20 July 1999
SPIE-Int. Soc. Opt. Eng
Proc. SPIE - Int. Soc. Opt. Eng. (USA), pp.252-63.
Keywords: Feature extraction; Feedforward neural nets; Image classification; Learning (artificial intelligence); Remote sensing; Nonparametric neighbor-based classifiers; Semisupervised image classification; Landsat imagery; Landcover maps; Clustering; Feedforward neural network ; Pixel assignment
Original abstract: Semisupervised classification is one approach to converting multiband optical and infrared imagery into landcover maps. First, a sample of image pixels is extracted and clustered into several classes. The analyst next combines the clusters by hand to create a smaller set of groups that correspond to a useful landcover classification. The remaining image pixels are then assigned to one of the aggregated cluster groups by use of a per-pixel classifier. This research reports the results of an experiment conducted on six Landsat TM images to compare the accuracy of pixel assignment performed by four nearest neighbor classifiers and two neural network paradigms in a semisupervised context. In all the experiments, it is shown that the feedforward network classifier generally produced the highest accuracy on all six of the images, but it was not significantly better than the accuracy produced by the best neighbor-based classifier.
 

Harman, L., (1999). Remote Sensing Applications for Transit Planning and Operations (Power Point file). A National Forum on Remote Sensing Applications to Transportation, May 11-12, 1999, Washington DC http://scitech.dot.gov/reeng/sensmsrm/rmtsense/sbrsagnd.html,

Hasegawa, H.; H. Aoki; F. Yamazaki; M. Matsuoka; I. Sekimoto, (2000). Automated detection of damaged buildings using aerial HDTV images. IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120) Honolulu, HI, USA 24-28 July 2000
Piscataway, NJ, USA IEEE, pp.310-12 vol.1.
Keywords: Earthquakes; Geophysical signal processing; Geophysical techniques; High definition television; Image processing; Image texture; Remote sensing; Terrain mapping; Geophysical measurement technique; Town; City; Urban area; Earthquake damage; Land surface; Optical imaging; Buildings; Automated detection; Damaged buildings; Building damage; hdtv; Aerial image; High-definition television; Kobe earthquake; ad 1995; Japan; Color indices; Edge intensity; Hue; Saturation; Threshold value ; Colour index
Original abstract: In order to seek the possibility of automated detection of damaged buildings from aerial television, the characteristics of high-definition television (HDTV) images taken after the 1995 Kobe earthquake were investigated. The relationships between the degree of building damage and the color indices and edge intensity from the aerial images were examined by image processing techniques. The characteristics of building damage were defined on the basis of hue, saturation, brightness and edge intensity. Using the threshold values of these parameters, the typical areas were classified into damaged and undamaged pixels. A texture analysis was further conducted to these pixels and damaged buildings were identified. The extracted damage distribution by the proposed method agreed well with ground truth data and visual inspection of the HDTV images.
 

Heene, G.; S. Gautama, (2000). Optimisation of a coastline extraction algorithm for object-oriented matching of multisensor satellite imagery. IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120) IGARSS 2000. Honolulu, HI, USA 24-28 July 2000
Piscataway, NJ, USA IEEE, pp.2632-4 vol.6.
Keywords: Edge detection; Feature extraction; Geophysical signal processing; Geophysical techniques; Image processing; Object-oriented methods; Oceanographic techniques; Optimisation; Remote sensing; Sensor fusion; Geophysical measurement technique; Ocean; Coast; Coastline; Terrain mapping; Feature extraction algorithm; Object-oriented matching; Multisensor satellite imagery; Image fusion; Data fusion; Optimized extraction; Point based method; Masking step; Edge focusing ; Closing step
Original abstract: The authors examine the optimized extraction of coastlines in multisensor satellite imagery as a first step in the object-oriented matching of these images, using whole coastlines as the matching features instead of a point based method. Typically, they want to extract these coastlines with the best positional accuracy possible, together with suppression of unnecessary detail. For this purpose, they add two additional masking steps, an edge focusing and a closing step to the edge detection process.
 

Heikkonen, J.; I. Kanellopoulos; A. Varfis; A. Steel; K. Fullerton, (1997). Urban land use mapping with multi-spectral and SAR satellite data using neural networks. IGARSS'97. 1997 International Geoscience and Remote Sensing Symposium. Remote Sensing - A Scientific Vision for Sustainable Development (Cat. No.97CH36042) Singapore 3-8 Aug. 1997
New York, NY, USA IEEE, pp.1660-2 vol.4.
Keywords: Backpropagation; Feature extraction; Geophysical signal processing; Geophysical techniques; Geophysics computing; Image classification; Image sequences; Image texture; Multilayer perceptrons; Radar imaging; Remote sensing; Remote sensing by radar; Sensor fusion; Spaceborne radar; Synthetic aperture radar; Geophysical measurement technique; Radar remote sensing; Optical imaging; Data fusion; Land surface; Terrain mapping; Image processing; Urban land use; Multispectral imaging; Multilayer perceptron; Neural net; Neural network; Gabor feature; Multitemporal data; sar; res-1; SOM algorithm; Decision tree algorithm ; Feature selection
Original abstract: Statistical, textural and Gabor features were extracted from integrated multitemporal multispectral TM data and ERS-1 SAR imagery for urban land use mapping. The computed features are first normalised using the SOM algorithm and then a decision tree algorithm is applied for feature selection. The classification procedure was carried out with a multilayer perceptron, trained with the resilient backpropagation algorithm. The authors' results demonstrate the potential of the proposed methodology.
 

Heikkonen, J.; A. Varfis (1998). Land cover/land use classification of urban areas: a remote sensing approach. International Journal of Pattern Recognition and Artificial Intelligence, 12, (4): 475-89.
Keywords: Cartography; Feature extraction; Pattern classification; Remote sensing; Self-organising feature maps; Trees (mathematics); Land cover classification; Land use classification; Urban areas; Feature coding; Feature selection; Self-organizing map; Regression trees; Landsat TM; ERS-1 SAR images; Lisbon ; Neural networks
Original Abstract: This paper proposes a method for remote sensing based land cover/land use classification of urban areas. The method consists of four main stages: feature extraction, feature coding, feature selection and classification. In the feature extraction stage, statistical, textural and Gabor features are computed within local image windows of different sizes and orientations to provide a wide variety of potential features for the classification. Then the features are encoded and normalized by means of the self-organizing map algorithm. For feature selection a classification and regression trees based algorithm was developed to select a subset of features for each class within the classification scheme at hand. The selected subset of features is not attached to any specific classifier. The paper reports experiments in land cover/land use classification with the Landsat TM and ERS-1 SAR images gathered over the city of Lisbon to show the potentials of the proposed method.
 

Heikkonen, J.; A. Varfis; G. Wilkinson; I. Kanellopoulos; K. Fullerton; A. Steel, (1997). Satellite image-based land cover/land use classification of urban areas. Neural Networks in Engineering Systems. Proceedings of the 1997 International Conference on Engineering Applications of Neural Networks Stockholm, Sweden 16-18 June 1997
Turku, Finland Syst. Eng. Assoc, pp.9-16 vol.1.
Keywords: Decision trees; Feature extraction; Geography; Image coding; Image texture; Learning (artificial intelligence); Multilayer perceptrons; Radar imaging; Remote sensing by radar; Self-organising feature maps; Statistical analysis; Synthetic aperture radar; Satellite image; Land cover; Land use classification; Urban areas; Feature coding; Feature selection; Statistical features; Textural features; Gabor features; Self-organizing map; Decision tree; Multilayer perceptron; Training; Lisbon; Landsat TM; ers-1 ; SAR images
Original abstract: A system for satellite image-based land cover/land use classification of urban areas is described. The system consists of the following main stages: feature extraction, feature coding, feature selection and classification. In feature extraction statistical, textural and Gabor features are computed from satellite images. Next the features are encoded and normalized by the self-organizing map algorithm and a decision tree-based algorithm was developed to select relevant features for the land cover/land use classification scheme at hand. Finally a multilayer perceptron is trained to map the selected features into the classes. The proposed system is tested on a land cover/land use classification task in the city of Lisbon with Landsat TM and ERS-1 SAR images, and the results show the potential of the proposed methodology.
 

Heinz, D. C.; C. I. Chang (2001). Fully constrained least squares linear spectral mixture analysis method for material quantification in hyperspectral imagery. Ieee Transactions on Geoscience and Remote Sensing, V39, (N3): 529-545.
Keywords:
Original Abstract: Linear spectral mixture analysis (LSMA) is a widely used technique in remote sensing to estimate abundance fractions of materials present in an image pixel. In order for an LSMA-based estimator to produce accurate amounts of material abundance, it generally requires two constraints imposed on the linear mixture model used in LSMA, which are the abundance sum-to-one constraint and the abundance nonnegativity constraint. The first constraint requires the sum of the abundance fractions of materials present in an image pixel to be one and the second imposes a constraint that these abundance fractions be nonnegative. While the first constraint is easy to deal with, the second constraint is difficult to implement since it results in a set of inequalities and can only be solved by numerical methods. Consequently, most LSMA-based methods are unconstrained and produce solutions that do not necessarily reflect the true abundance fractions of materials. In this case, they can only be used for the purposes of material detection, discrimination, and classification, but not for material quantification. The authors present a fully constrained least squares (FCLS) linear spectral mixture analysis method for material quantification. Since no closed form can be derived for this method, an efficient algorithm is developed to yield optimal solutions. In order to further apply the designed algorithm to unknown image scenes, an unsupervised least squares error (LSE)-based method is also proposed to extend the FCLS method in an unsupervised manner.
 

Heinz, D. C.; I. C. Chein, (2000). Unsupervised fully constrained squares linear spectral mixture analysis method for multispectral imagery. IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120) Honolulu, HI, USA 24-28 July 2000
Piscataway, NJ, USA IEEE, pp.1681-3 vol.4.
Keywords: Geophysical signal processing; Geophysical techniques; Image processing; Multidimensional signal processing; Remote sensing; Terrain mapping; Geophysical measurement technique; Land surface; Optical imaging; Multispectral remote sensing; Fully constrained squares linear spectral mixture analysis; Multispectral imagery; Subpixel detection; Endmembers; Linear mixture analysis ; Multispectral image analysis
Original abstract: Subpixel detection and quantification of materials in multispectral imagery presents a challenging problem due to a relatively low number of spectral bands available for analysis in which case the number of spectral bands may be less than the number of materials to be detected and quantified. The problem is even more difficult when the image scene is unknown and no prior knowledge is available. Under this circumstance, the desired information must be obtained directly from the image data. The authors present an unsupervised least squares-based linear mixture analysis method coupled with a band expansion technique for multispectral image analysis. This method allows the authors to extract necessary endmember information from an unknown image scene so that the endmembers present in the image can be detected and quantified. The band expansion technique creates additional bands from the existing multispectral bands using band-to-band nonlinear correlation. These expanded bands ease the problem of insufficient bands in multispectral imagery and can improve and enhance the performance of the proposed method. The experimental results demonstrate the advantages of the proposed approach.
 

Heipke, C.; H. Mayer; C. Wiedemann; O. Jamet, (1997). Evaluation of automatic road extraction. Joint ISPRS Commission III/IV Workshop. 3D Reconstruction and Modelling of Topographic Objects Stuttgart, Germany 17-19 Sept. 1997
Int. Arch. Photogramm. Remote Sens. (Australia), pp.151-60.
Keywords: Feature extraction; Geography; Image matching; Photogrammetry; Redundancy; Remote sensing; Automatic road extraction algorithms; Internal self-diagnosis; External evaluation; Image analysis; Manually plotted linear road axes; Reference data; Extracted primitives matching; Quality measures; Completeness; Correctness; Planimetric RMS differences; Gap statistics; Exhaustivity; Geometrical accuracy; Multiple algorithms ; Experimental results evaluation
Original abstract: Internal self-diagnosis and external evaluation of the obtained results are essential for any automatic system. In the long run, these factors are of major importance for the relevance of the system for practical applications. Obviously, this statement is also true for image analysis in photogrammetry and remote sensing. However, so far, only relatively little work has been carried out in this area. This paper deals with the external evaluation of automatic road extraction algorithms by means of comparison to manually plotted linear road axes used as reference data. The comparison is performed in two steps: (1) matching of the extracted primitives to the reference network; and (2) calculation of quality measures. Each part depends on the other: the less tolerant the matching, the less exhaustive the extraction is considered to be, but the more accurate it looks. Therefore, the matching process is an important part of the evaluation process. The quality measures proposed for the automatically extracted road data comprise completeness, correctness, quality, redundancy, planimetric RMS differences and gap statistics. They aim at evaluating exhaustivity as well as assessing geometrical accuracy. The evaluation methodology is presented and discussed in detail. Results of a comparative evaluation of three different automatic road extraction approaches are presented. They show the overall status of the road extractors, as well as the individual strengths and weaknesses of each individual approach. Thus, the applicability of the evaluation method is proven.
 

Heipke, C.; W. Mayr; C. Wiedemann; H. Ebner, (1997). Automatic aerotriangulation with frame and three-line imagery. Integrating Photogrammetric Techniques with Scene Analysis and Machine Vision III Orlando, FL, USA 21-23 April 1997
SPIE-Int. Soc. Opt. Eng
Proc. SPIE - Int. Soc. Opt. Eng. (USA), pp.286-94.
Keywords: Feature extraction; Image matching; Remote sensing; Automatic aerotriangulation; Frame imagery; Three-line imagery; Conjugate point extraction; Geometric differences; Point features; Coarse-to-fine strategy; Image pyramids; Feature-based matching; Overlapping image pairs; Manifold conjugate point tuples; Exterior orientation parameters; 3D-coordinates; Distributed conjugate points ; Stable block geometry
Original abstract: In this paper an approach for automatic aerotriangulation (AAT) is presented, which is designed for frame and three-line imagery. We focus on the extraction of conjugate points, because the geometric differences in geometry of frame and three-line imagery can be considered as well-known and are only different modules at the implementation stage. Our approach uses point features and a coarse-to-fine strategy based on image pyramids. To extract conjugate points we employ feature-based matching of image pairs on all pyramid levels. After matching all overlapping pairs of images, manifold conjugate point tuples are generated and checked for geometric consistency individually as well as in their local neighborhood. Subsequently, the exterior orientation parameters for the whole block are calculated on each pyramid level in a robust bundle adjustment together with 3D-coordinates for the conjugate point tuples in an arbitrary reference system. This information serves as initial values on the next lower pyramid level. Control information is not necessary a priori, but can be introduced at any stage of processing. The approach has been tested with various imagery. A few hundred well distributed conjugate points were extracted in all cases. In particular, a large number of many-ray points, which are essential for a stable block geometry was detected. The standard deviation of all image coordinates lies between 0.3 and 0.4 pixels. These results constitute a proof-of-concept and demonstrate the feasibility of the presented approach.
 

Hellmann, M.; S. R. Cloude; K. P. Papathanassiou, (1997). Classification using polarimetric and interferometric SAR-data. IGARSS'97. 1997 International Geoscience and Remote Sensing Symposium. Remote Sensing - A Scientific Vision for Sustainable Development (Cat. No.97CH360420) Singapore 3-8 Aug. 1997
New York, NY, USA IEEE, pp.1411-13 vol.3.
Keywords: Feature extraction; Geophysical signal processing; Geophysical techniques; Image classification; Radar imaging; Radar polarimetry; Remote sensing by radar; Sensor fusion; Synthetic aperture radar; Geophysical measurement technique; Land surface; Terrain mapping; Interferometric SAR; InSAR ; Automatic classification
Original abstract: The investigation presented in this paper demonstrate a first order approach to an automatic classification and extraction of cartographic relevant features from SAR data. The authors propose a fusion of polarimetric and interferometric classification techniques that is able to solve several classification ambiguities which are not resolvable with one method alone and is also able to improve significantly the accuracy of the classification results. The complimentarity of the polarimetric and interferometric coherence based classification approaches and the improvements resulting from their combination are demonstrated using data from the space-shuttle-borne SIR-C/X-SAR radar system.
 

Hellmann, M.; S. R. Cloude; K. P. Papathanassiou, (1997). Interpretation of SAR-data using polarimetric and interferometric techniques. Wideband Interferometric Sensing and Imaging Polarimetry San Diego, CA, USA 28-29 July 1997
SPIE-Int. Soc. Opt. Eng
Proc. SPIE - Int. Soc. Opt. Eng. (USA), pp.255-66.
Original abstract: The investigation presented in this paper demonstrates the potential of the combination of polarimetric and interferometric classification techniques for the extraction of map relevant features from space borne SAR data. In the first part we discuss a polarimetric classification technique based on Cloude's decomposition theorem (Cloude and Pottier 1995, 1997; Pottier 1994). Afterwards we demonstrate the abilities of interferometric classification. The complementarity of the polarimetric and interferometric coherence based classification approaches can be used to resolve ambiguities that remain if one method is applied alone. The improvements resulting from their combination are available for an automatic classification and extraction of cartographic relevant features from space borne SAR data.
 

Hellmann, M.; E. Kratzschmar, (1998). A new approach for interpretation of full-polarimetric SAR-data. Proceedings of the PIERS Workshop on Advances in Radar Methods Baveno, Italy 20-22 July 1998
Brussels, Belgium Commision of Eur. Communities, pp.204-7.
Keywords: Eigenvalues and eigenfunctions; Electromagnetic wave scattering; Entropy; Feature extraction; Pattern classification; Radar polarimetry; Remote sensing by radar; Spaceborne radar; Synthetic aperture radar; Full-polarimetric SAR data; Unsupervised classification; Eigenvalue based analysis; H- alpha feature extraction; Automatic classification; Scattering mechanisms; L-band data; C-band data; Spaceborne SAR; SIR-C/X-SAR mission; Germany ; Ground interaction
Original abstract: In this paper a new approach for unsupervised classification of full polarimetric SAR-data suitable for automation is outlined. To reach this aim it is important to develop an algorithm which is independent of data set and sensor. A well known approach towards this goal is the eigenvalue based analysis of the entropy H and alpha parameters. This H- alpha feature extraction is independent of data set and sensor and suitable for unsupervised and automatic classification due to the fact that it is possible to derive information about the scattering mechanisms on the ground without a priori knowledge. In this paper a extension of this algorithm is proposed. While the H- alpha feature extraction uses an averaged alpha value and also the entropy in the von-Neumann sense is an averaged value the new approach uses the 3 eigenvalues and their relations. A physical interpretation of the relationships between the eigenvalues is proposed. This algorithm can improve the class accuracy which is not sufficient for maps in the H- alpha classification case. For the classification L-band and C-band data of the space-shuttle-borne SIR-C/X-SAR mission from the test site Oberpfaffenhofen, Germany were used. The combination of both frequencies allows a more detailed classification of the scene due to different ground interaction of the different wavelengths. Therefore different scattering mechanisms can be seen in different bands and from the combination of both bands ambiguities can be resolved. For validation purposes the classification is compared with the ATKIS (official German GIS) data.
 

Hellwich, O.; M. Gunzl, (2000). Landuse classification by fusion of optical and multitemporal SAR imagery. IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120) Honolulu, HI, USA 24-28 July 2000
Piscataway, NJ, USA IEEE, pp.2435-7 vol.6.
Keywords: Remote sensing by radar; Synthetic aperture radar; Terrain mapping; Landuse classification; Multitemporal SAR imagery; Surface roughness; Soil moisture; Object extraction; Passive optical imagery; Speckle effect; Areal objects; All-weather capability; Time series; Optical image data; Data fusion; Multispectral data ; Object recognition
Original abstract: Optical imagery such as high resolution panchromatic or multispectral data, and synthetic aperture radar (SAR) data show different information about the imaged objects, and have different advantages and disadvantages when used for object extraction or landuse classification. Multispectral optical image data is largely determined by the type of the material an object consists of. Panchromatic data which is often available with a higher resolution than multispectral data emphasizes geometric detail of the objects, e.g. the complex structure of anthropogenic objects such as road networks. In contrary to this, SAR data contain information about surface roughness and - to a lower degree - soil moisture. These different types of information are referring to completely different object qualities and are, therefore, largely uncorrelated which helps to reduce ambiguities in the results of object extraction. The main advantage of passive optical imagery with respect to SAR data is the lack of the speckle effect leading to images with a far better extractability of linear as well as areal objects. A major advantage of SAR is its all-weather capability which allows the acquisition of time series of imagery with exact acquisition dates under any climatic conditions. In this paper, these complementary properties of SAR and optical image data are demonstrated and used to improve landuse classification results.
 

Hellwich, O.; C. Streck, (1996). Linear structures in SAR coherence data. IGARSS '96. 1996 International Geoscience and Remote Sensing Symposium. Remote Sensing for a Sustainable Future (Cat. No.96CH35875) Lincoln, NE, USA 27-31 May 1996
New York, NY, USA IEEE, pp.330-2 vol.1.
Keywords: Coherence; Edge detection; Feature extraction; Geophysical signal processing; Hydrological techniques; Radar imaging; Radiowave interferometry; Remote sensing by radar; Rivers; Spaceborne radar; Synthetic aperture radar; SAR coherence data; Thin linear structures; Roads; Railway lines; Speckle effects; Coherent imaging; Interferometric processing; Visibility; Spaceborne scenes; Airborne SAR; Optimal size; Correlation window; Linear structure extraction; Intensity ; Amplitude
Original abstract: The extraction of thin linear structures like roads, rivers and railway lines from synthetic aperture radar (SAR) scenes has been shown to be a difficult task owing to the speckle effects of coherent imaging (e.g. Hendri et al., 1988), Therefore, for line extraction it is reasonable to use all information that SAR scenes offer, and not only the amplitude data. One source of additional information is the coherence data computed by interferometric processing of two SAR scenes. The visibility of linear structures in SAR coherence data has been investigated. Scene pairs from the ERS-1 and the ERS-2 SAR sensors, the X-SAR experiment and a scene from a two-antenna airborne SAR system were evaluated The time difference between the acquisitions of the spaceborne scenes forming interferometric scene pairs was one to 35 days. An optimal size of the correlation window used to derive coherence maps for linear structure extraction was determined by visual inspection. The correlation between the intensity and the coherence data was used to infer how much information the coherence adds to the information of the amplitude of both scenes.
 

Hellwich, O.; C. Wiedemann, (1999). Multisensor data fusion for automated scene interpretation. Image and Signal Processing for Remote Sensing V Florence, Italy 22-24 Sept. 1999
SPIE-Int. Soc. Opt. Eng
Proc. SPIE - Int. Soc. Opt. Eng. (USA), pp.284-95.
Keywords: Feature extraction; Geography; Image classification; Image recognition; Image segmentation; Knowledge based systems; Principal component analysis; Radar imaging; Remote sensing by radar; Sensor fusion; Synthetic aperture radar; Multisensor data fusion; Automated scene interpretation; Linear objects; Two-dimensional objects; Feature-level fusion; Object level fusion; Data sources; DAIS hyperspectral data; AES-1 SAR data; High-resolution panchromatic digital orthoimages; Rural test areas; Road network; Agricultural fields; Small villages; Scene interpretation; Conceptual model; Semantic net; Network nodes; Hyperspectral bands; Extraction results; Areal objects; Principal component transformation; Image intensity; Interferometric elevation; Classifications; Rule-based methods ; Segment-based method
Original abstract: An approach to the combined extraction of linear as well as two-dimensional objects from multisensor data based on a feature- and object level fusion of the results is proposed. The data sources are DAIS hyperspectral data, AES-1 SAR data, and high-resolution panchromatic digital orthoimages. Rural test areas consisting of a road network, agricultural fields, and small villages were investigated. The scene interpretation is based on a conceptual model consisting of a semantic net for each of the sensors and a semantic net of the real world objects. The sensor nets and the object net are combined into one network by means of a geometry and material level of network nodes. Road networks are extracted from the panchromatic orthoimage and from selected hyperspectral bands. Based on the knowledge that roads compose networks the extraction results are combined. Two-dimensional, i.e. areal objects are extracted from hyperspectral data after a principal component transformation. The SAR data are segmented using image intensity and interferometric elevation. The classifications of the hyperspectral and SAR data are combined with the extracted road network using rule- and segment-based methods. In the outlook, comments are given on the trade-off between the improvement of the results using the new method and the increasing costs for data acquisition.
 

Hemmer, T. H., (1996). Towards automation of the extraction of lines of communication from multispectral images using a spatio-spectral extraction technique. Algorithms for Multispectral and Hyperspectral Imagery II Orlando, FL, USA 9-11 April 1996
SPIE-Int. Soc. Opt. Eng
Proc. SPIE - Int. Soc. Opt. Eng. (USA), pp.115-26.
Keywords: Cartography; Feature extraction; Image resolution; Remote sensing; Spectral analysis; Automated mapping; Lines of communication; Multispectral images; Spatio-spectral extraction technique; Commercial sensor resolutions; Identification; Spectral information ; Linear mixture model
Original abstract: Adequate imagery for automated mapping of large areas became available with the successful launch of the 30-meter 7-band thematic mapper (TM) on Landsat 4 in 1982. Yet an adequate approach to automated line-of-communication (LOC) extraction continues to elude the remote sensing community. Perhaps the single biggest complicating factor is the inherently subpixel nature of the problem; almost all LOCs are narrower than current commercial sensor resolutions. Other complications include: spatial and temporal variability of LOC surface spectra, proximity to, and abundance of, spectrally similar materials, and atmospheric effects. We describe progress towards the detection and identification of LOCs using a technique that simultaneously extracts both spatial and spectral information. The approach currently uses a linear mixture model for simultaneously decomposing the image into fractional compositions and corresponding spectra using physical constraints. The algorithm differs from other approaches in that no traditional preprocessing or prior spatial or spectral information is required to extract the LOCs and their spectra. The algorithm has been successfully applied to TM and M-7 data. Results are presented.
 

Henderson, F. M.; X. Zong-Guo (1997). SAR applications in human settlement detection, population estimation and urban land use pattern analysis: a status report. IEEE Transactions on Geoscience and Remote Sensing, 35, (1): 79-85.
Keywords: Demography; Geography; Geophysical techniques; Radar applications; Remote sensing by radar; Synthetic aperture radar; Geophysical measurement technique; Land use; Terrain mapping; Radar remote sensing; Urban area; sar; Human settlement detection; Town; City; Population estimation; Pattern analysis; Urbanized area ; Population migration
Original Abstract: Over 70 percent of the population of the world's developed countries live in urbanized areas. In developing countries migration to urban areas is continuing at an increasing rate. Detection and analysis of settlement patterns, estimating population, and monitoring population migration in a timely manner are requisite to accurately assess the impact of human activities on the environment. Monitoring urban land use change patterns is among the most critical information needs for future economic development planning, natural resource allocation, and environmental and ecosystem management. Previous research has demonstrated the potential of imaging radar systems in analyzing urban, population, and settlement phenomena. However, the variability and complexity within and between urban land use morphologies present a convoluted environment for analysis. Studies of vegetation, soils, geology, hydrology, and ice and snow have all received more attention and been the subject of considerably more widespread and in-depth radar research. Nevertheless, imaging radars offer some distinct advantages and opportunities for urban-based research. With the arrival of operational space imaging SAR systems, a review of the current status of applications of radar remote sensing in urban studies should be useful for focusing the authors' attention on this important area of radar research and identification of specific problems for in-depth analysis. This paper traces the history of imaging radar research for urban, settlement, and population analysis. It presents a status report on the applications of SAR in settlement detection, population estimation, assessment of the impact of human activities on the physical environment, mapping and analyzing urban land use patterns, and interpretation of socioeconomic characteristics. The demonstrated capabilities and limitations of past and current imaging radar systems with reference to these applications are described. Potential avenues of future research are addressed.
 

Henricsson, O. (1998). The role of color attributes and similarity grouping in 3D building reconstruction. Computer Vision and Image Understanding, 72, (2): 163-84.
Keywords: Computer vision; Edge detection; Feature extraction; Image colour analysis; Image reconstruction; Remote sensing; Stereo image processing; Color attributes; Similarity grouping; 3D building reconstruction; aruba ; Aerial images
Original Abstract: We present ARUBA, a general framework for automated 3D building reconstruction from multiple color aerial images. After highlighting the strategy and concisely describing the framework and its 2D and 3D processing modules, we evaluate the reconstructed roofs with respect to accurate reference data. The paper shows that geometry, although important, should not be the only source of information exploited in the reconstruction process. The main objectives are to demonstrate that: 1) color is a very important cue in reconstructing a general class of objects; 2) it is crucial to retain all information during the entire processing chain, 3) a general class of objects parts can be efficiently extracted by grouping edges and lines by means of similarity, and 4) a mutual interaction between 2D and 3D processing is important.
 

Henry, B., (2000). The potential of LiDAR in urban and regional development. URISA Proceedings. URISA 2000 Annual Conference and Exposition Proceedings of 37th Annual Conference of the Urban and Regional Information Systems Association Orlando, FL, USA 19-23 Aug. 2000
Park Ridge, IL, USA Urban & Regional Inf. Syst. Assoc, pp.379-81.
Keywords: cad; Civil engineering computing; Geographic information systems; Town and country planning; Visual databases; LiDAR dataset; Urban/regional development; Urban habitats; Natural environment; Urban areas; Data layers; Development enterprise; Spatial relations; Geographic layers; Buildings; Highways; Waterways; Trees; Ground contours; Terrain surfaces; CAD systems ; gis
Original abstract: Just like a beaver's dam or an owl's nest our urban habitats are a complex array of materials crafted to meet our species' needs, but exposed to the natural environment in which we live; an environment, seemly sedate and controlled, that proves highly sensitive to changes we make maintaining and expanding our habitat. With the advent of geographic information systems, we have been able to study the relationships between our habitats and their environment, we have created systems for planning new growth, managing our current situation and designing solutions for the unexpected forces of nature. However, even the smallest of urban areas is a big place. In order to make accurate decisions, data layers for all areas that affect an environment should be included and at as high an accuracy level as possible. LiDAR presents a method of capturing a large urban or regional area in a manner suitable to all aspects within a planning and development enterprise. A LiDAR dataset is not just a picture of a city or region, but its essence. All the spatial relations existing within the area are available in 3 dimensions. Using various tools, the raw data can be transformed into geographic layers such as buildings, highways, waterways, trees, ground contours, and terrain surfaces. These layers can be added to GIS or CAD systems, aiding planners and developers in their decisions. The paper presents an overview of the tools and methods available for creating data layers from LiDAR and provides insight into using these layers throughout the planning and development enterprise.
 

Hepner, G. F.; B. Houshmand; I. Kulikov; N. Bryant (1998). Investigation of the integration of AVIRIS and IFSAR for urban analysis. Photogrammetric Engineering and Remote Sensing, V64, (N8): 813-820.
Keywords: AVIRIS , IFSAR integration
 
 

Hernandez, R. R. (1995). Enterprisewide GIS reduces traffic congestion. GIS World, 8, (4): 48-51.
Keywords: Geographic information systems; Town and country planning; Traffic; Transportation; Enterprise-wide geographic information system; Traffic congestion; Los Angeles Metropolitan Transportation Authority; Traffic planners; GIS-based transportation development project; Graphical environment; Analytical environment; Real-time traffic monitoring; GIS database; Metropolitan planning agency; New roads; Light-rail links; Transit systems; Real-time information; Bus schedules; Hot-line number; arc/info; Environmental Systems Research Institute; IBM RS/6000 workstations ; Token ring network
Original Abstract: With the help of GIS technology and some creative forward-thinking by the Los Angeles Metropolitan Transportation Authority (MTA), Los Angeles' traffic planners are in the midst of one of the largest GIS-based transportation development projects ever-designing, developing and implementing an enterprisewide GIS. The GIS will provide a graphic and analytical environment for real-time traffic monitoring and planning of the entire Los Angeles County region. The GIS database under development will be one of the largest in use by a metropolitan planning agency, covering some 4,000 square miles. The system will link users in several MTA departments and other agencies to accommodate a range of applications, from providing analysis tools for planning new roads and light-rail links to tools for operating transit systems and providing real-time information on bus schedules using a hot-line number. The project uses ARC/INFO GIS software from the Environmental Systems Research Institute, running on IBM RS/6000 workstations on a token ring network at MTA's downtown Los Angeles headquarters. In the first year of implementation, services have been extended to numerous groups within MTA, including transportation modeling, planning, scheduling and operations, and benefits/assessment. Similar hardware and GIS software eventually will link into an enterprisewide system among MTA offices and other agencies.
 

Herr, A. V., Jr.; J. A. Szemraj; L. Parks, (1995). A joint effort to develop a national transportation data base. GIS/LIS *95 Annual Conference and Exposition Proceedings of Geographic Information Systems/Land Information Systems Nashville, TN, USA 14-16 Nov. 1995
Bethesda, MD, USA American Soc. Photogrammetry & Remote Sensing & American Congress on Surveying & Mapping, pp.428-35 vol.1.
Keywords: Geographic information systems; Merging; Research initiatives; Transaction processing; Transportation; Visual databases; National transportation database development; usa; US Geological Survey; Bureau of the Census; Data merging; Transportation feature data; Data accuracy; Data quality; Common core data set; Road features; Digital line graph data; Topographic quadrangles; Topologically Integrated Geographic Encoding and Referencing; TIGER system data; High-resolution commercial data; Feature identification code scheme; Geodata sources; Transaction file; Automated geospatial database updating; Federal Geographic Data Committee National Spatial Data Infrastructure Framework; Data initiative; Data revision ; Data exchange
Original abstract: The US Geological Survey (USGS) and the Bureau of the Census (BOC) have entered into a pilot program that studies the merging of transportation feature data of differing accuracies and qualities in order to create a common core data set. The data used are the road features from USGS digital line graph (DLG) data collected from the 1:100,000-scale topographic quadrangles, the BOC Topologically Integrated Geographic Encoding and Referencing (TIGER) system data, and higher resolution commercial data. The purpose is to integrate the best qualities of each data set to create an improved common core feature data set, to develop a feature identification code scheme that will allow users to quickly and easily equate features to their own geodata sources, and to develop a scheme for a transaction file that will allow for the automated updating of geospatial databases. These objectives support the Federal Geographic Data Committee National Spatial Data Infrastructure Framework data initiative. This paper describes the approach used for ingesting, conflating, revising and exchanging the data, and discusses the results of this first pilot project for the development effort.
 

Hideo, T., (1999). Urban gas monitoring system using optical sensors. 13th International Conference on Optical Fibre Sensors Kyongju, South Korea 12-16 April 1999
SPIE-Int. Soc. Opt. Eng
Proc. SPIE - Int. Soc. Opt. Eng. (USA), pp.332-6.
Keywords: Air pollution measurement; Gas sensors; Leak detection; Monitoring; Optical modulation; Optical sensors; Organic compounds; Remote sensing by laser beam; Spectrochemical analysis; Urban gas monitoring system; Methane monitoring system; Distributed-feedback semiconductor laser; Detection limit; Concentration pathlength product; High sensitivity; Second-harmonic detection; Wavelength modulation frequency; Methane absorption line; Positioning system; Mobile GIS; Gas leakage points; Buried pipelines; Digital map; Real time; Vehicle mounted system; Sensitivity; Linearity ; 1.66 micron
Original abstract: We have developed a methane monitoring system using a 1.66 mu m distributed-feedback semiconductor laser. The detection limit of the system is 70 ppb m in concentration pathlength product with the time constant of 1 s. This high sensitivity is achieved by the second-harmonic detection of wavelength modulation frequency of the laser whose center wavelength is stabilized on an the absorption line of methane. The system was installed on a vehicle in combination with a positioning system and a mobile GIS that enabled to record and indicate gas leakage points from buried pipelines on the digital map in real time.
 

Hill, J. M. (2000). Wide-Area Topographic Mapping and Applications Using Airborne LIght Detection and
Ranging (LIDAR) Technology. Photogrammetric Engineering and Remote Sensing, V66, (N8).
Keywords: LIDAR system
Synopsis: This is a "highlight" article describing recent LIDAR applications. There are sections on transportation and urban landscape applications. This is a good 'intro to LIDAR' article.
 
 

Hillman, R., (1997). GIS-based innovations for modelling public transport accessibility. Geographic Information - Exploiting the Benefits. Proceedings of the AGI'97 Conference Proceedings of Conference on Products and Services Relating to Geographical Information Systems Birmingham, UK 7-9 Oct. 1997
London, UK Assoc. Geogr. Inf, pp.1-6.
Keywords: Geographic information systems; Government policies; Planning; Public administration; Transportation; Visual databases; GIS-based innovations; Local government; Government transport policy; Accessibility modelling; Spatial databases; Geodemographic data; Land use data; Travel times; Development control ; Public transport network planning
Original abstract: Central and local government transport policy is increasingly focused on promoting sustainable transport schemes, and in particular shifting dependence from the private car towards the increased use of public transport. The effective implementation of this process is facilitated by information about the transport networks that are managed, and the effects of changes to those networks. Increasingly the measurement of public transport accessibility is viewed as a useful tool in this planning process. This provides data on the ease, or otherwise, of travel between two points; and may take into consideration factors such as walking to a network access point, travel through the network, interchanges, and access to the intended destination. GIS provides an excellent environment for the modelling of accessibility. Transport data is inherently spatial in nature and the GIS provides access to additional data such as geodemographic and land use data sets. This enables the planner to look not only at the basic travel times between points but to assess the utility of specific destinations to specific user groups. This paper briefly studies the reasons for measuring public transport accessibility and considers various methods of calculating accessibility indices. Examples are drawn from a variety of applications including development control and public transport network planning. Data issues in developing and maintaining public transport databases are investigated.
 

Hippie, J. D.; D. J. Daugherty, (2000). Urban validation site for testing impervious surface models derived from remotely sensed imagery. IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120) Honolulu, HI, USA 24-28 July 2000
Piscataway, NJ, USA IEEE, pp.2074-6 vol.5.
Keywords: Geophysical signal processing; Geophysical techniques; Hydrological techniques; Remote sensing; Sensor fusion; Terrain mapping; Hydrology; Runoff; Land surface; Measurement technique; Urban site; Town; City; Validation site; Impervious surface model; Impervious surface; Hydraulic model; Landscape; Multiple sensor; Multifarious classification; Springfield; Missouri; United States; usa; Land cover; Industrial land use; Park ; Open space
Original abstract: Accurate quantification of impervious surfaces is a necessary input in a variety of urban applications including hydrologic and hydraulic models and landscape change. The purpose is to assess the performance and effectiveness of multiple sensor platforms for the delineation of impervious surface in an urban setting using multifarious classification strategies. Data acquired from airborne and satellite based sensors are used, along with a variety of classification and data fusion strategies, to gather a cost versus reliability measurement for each of the systems. A framework is presented to aid users in selecting the appropriate dataset and methodology for their specific situational needs. The impervious surface generation models are applied to remotely sensed data collected over the Springfield Urban Validation Site (UVS), an approximately 1-km N-S by 4-km E-W urban corridor within the City of Springfield, Missouri. The site is highly documented with respect to position and composition of structures and land covers and consists of varying aged residential developments, commercial, institutional, parks and open space, and light industrial land uses. The models and comparisons developed here can be reliably used to estimate the costs and spatial variability of different methods of impervious surface generation from various imagery inputs, aiding urban planners and managers in the assessment of the errors and biases of various impervious surface generation strategies.
 

Hipple, J. D.; D. J. Daugherty; J. M. Dunajcik, (2000). Long-term growth visualization and change detection for urban planning applications: a Springfield MO urbanized watershed. IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120) Honolulu, HI, USA 24-28 July 2000
Piscataway, NJ, USA IEEE, pp.2875-7 vol.7.
Keywords: Geophysical techniques; Remote sensing; Terrain mapping; Geophysical measurement technique; Land use; Land surface; United States; usa; Urban area; Expansion; Growth; Town; City; Visualization; Change detection; Urban planning; Springfield; Urbanized watershed; Missouri; Landsat; Optical imaging ; Multispectral remote sensing
Original abstract: A long-term growth analysis was conducted for the City of Springfield, Missouri. The Springfield Department of Planning and Development was interested in determining the characteristics and patterns of urban growth within the metropolitan area over the past three decades. The interest in assessing urban growth and development trends within the region stems from present day environmental problems in areas recently annexed or areas that have undergone intensive development. A myriad of problems exist if the city continues to grow as expected (a fifty percent increase in area over the next 20 years). A historic look at urban growth through remote sensing allows planners and the public to visualize the expansion occurring in and around the city. The assessment of growth impacts uses a multi-tiered strategy where the NALC Landsat MSS triplicate sets provides long-term data for analysis and Landsat TM and ETM+ data provides the higher resolution data for a refined analysis. The methodology consisted of the identification of highly changed areas through numerous change detection techniques using the NALC data-sets. Once identified, the higher resolution data-sets were used to characterize the types of change that occurred. The authors present results dealing with one highly impacted area, that of a rapidly urbanized watershed. An assessment, such as the one presented, will aid determining environmental *priority areas' due to urban growth and assist in developing growth policies.
 

Hivernat, C.; X. Descombes; S. Randriamasy; J. Zerubia (2000). Matching of two line networks: application to the analysis and registration of road networks extracted from a couple map/SPOT image. Traitement du Signal, 17, (1): 21-32.
Keywords: Cartography; Edge detection; Feature extraction; Graphs; Image matching; Image registration; Image segmentation; Markov processes; Matrix algebra; Remote sensing; Line network matching; Image analysis; Road networks; SPOT image; Line graph matching; Segments; Markov model; Labelling problem; Rotation invariance; Translation invariance; Cartographic database; Road pixel chaining; Qualification step ; Registration matrix
Original Abstract: We consider the problem of line graph matching. The nodes correspond to segments characterized by their length and their angle. A Markov model allows us to embed the problem into a labelling problem. The derived model is invariant with respect to rotations and translations. The algorithm is applied to road networks extracted from a SPOT image and a cartographic database. The matching is performed after having chained the road pixels extracted from the image. After the matching, a qualification step provides a registration matrix and allows us to interpret the results in order to update the cartographic database.
 

Hoffman, R. N.; D. W. Johnson (1994). Application of Eofs to Multispectral Imagery - Data Compression and Noise Detection for Aviris. Ieee Transactions on Geoscience and Remote Sensing, V32, (N1): 25-34.
Keywords: AVIRIS , data compression, noise detection
Original Abstract: Investigates the first stage of a two stage approach to data compression for multispectral imagery. The first stage is to compress the data spectrally using empirical orthogonal functions (EOFs). In the second stage, each EOF image is further compressed using standard techniques, such as transform encoding. The characteristics of EOFs make them ideal for spectral compression. The EOFs form the orthogonal basis in the data space which provides the most economical data representation. Furthermore, and perhaps of more interest, EOFs are effective noise filters. In the authors experiments with the 224 channel AVIRIS data, lossy compression ratios of order 50:1 are attained by the EOF representation under the condition that the residual rms error be smaller than the independently measured instrument noise.
 

Hoffmann, A.; G. M. Smith; F. Lehmann, (2000). The classification of fine spatial resolution imagery: parcel-based approaches using HRSC-A data. IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120) Honolulu, HI, USA 24-28 July 2000
Piscataway, NJ, USA IEEE, pp.3009-11 vol.7.
Keywords: Geophysical signal processing; Geophysical techniques; Image classification; Remote sensing; Terrain mapping; Geophysical measurement technique; Land surface; Image processing; Fine spatial resolution imagery; Parcel-based approach; hrsc-a; High Resolution Sterwo Camera Airborne; Optical imaging ; Land cover type
Original abstract: Large amounts of remotely sensed data are now being collected from airborne platforms carrying digital scanners and digital cameras with spatial resolutions from 2 m down to 15 cm. Spaceborne instruments are now being launched with spatial resolutions between 1 and 4 m. These systems are used to address mapping issues in locating and identifying objects or areas on the surface. The fine spatial resolution of the data now becoming available would at first appear to be a major advantage for mapping applications compared to conventional satellite systems. However, it must be remembered that similar reasoning proceeded the launch of Landsat 4 and the Systeme Probatoire de l'Observation de la Terre (SPOT-I) in the 1980s. Work comparing TIM and HRV with the established 80 m spatial resolution Landsat Multispectral Scanner System (MSS) found that finer spatial resolutions actually reduced classification accuracy for certain land cover types. The coarse spatial resolution of the MSS smoothed out spatial complexity within heterogeneous land cover types, such as urban, as scene components, such as buildings and vegetation, become lost within a pixel. At finer spatial resolutions a scale boundary is crossed where the data recorded for each pixel is related not to the character of object or area as a whole, but to components of it and this requires a re-definition of the information that can be extracted. The current move toward even finer spatial resolution data sets should raise the same question how these types of data should be analysed using (semi-)automated techniques. This paper describes a methodology for classifying fine spatial resolution data to land cover types. The problem faced was two fold; firstly, how to extract meaningful information from the pixels within the fine spatial resolution images and secondly, how to integrate this detailed information at the pixel level to useable classes and appropriate scales.
 

Hoffmann, A.; J. W. Van Der Vegt; F. Lehmann, (2000). Towards automated map updating: detecting houses with new digital data-acquisition and processing techniques. IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120) Honolulu, HI, USA 24-28 July 2000
Piscataway, NJ, USA IEEE, v.5, pp.2108-10.
Keywords: Automated map updating
Original abstract: Up to now large scale mapping (scales >1:10000) is done nearly exclusively with aerial photographs. New digital camera systems will replace these analogue systems in the near future. This paper describes an approach for automated detection of houses, using a data set of the High Resolution Stereo Camera-Airborne (HRSC-A). The system provides multispectral information with a resolution of 15 cm (3000 m flight altitude) and Digital Surface Models with a resolution of 50 cm, depicting elevation in steps of 10 cm. The elevation and spectral information supplied by the sensor was used for this study. New object-oriented approaches allow the interpretation of these high resolution data sets. The combination of a new approach (multiresolution segmentation, hierarchical networks) and the multispectral high resolution data of HRSC-A with its accurate Digital Surface Model shows very promising results.
 

Horowitz, A. J. (1997). Integrating GIS concepts into transportation network data structures. Transportation Planning and Technology, V21, (N1-2): 139-153.
Keywords:
 
 

Hoyano, A.; K. Asano; A. Iino (1997). Urban environment and thermal infrared imaging technology. Journal of the Japan Society of Infrared Science and Technology, 7, (2): 2-12.
Keywords: Geophysical techniques; Infrared imaging; Remote sensing; Temperature distribution; Thermal infrared imaging technology; Urban environment; Radiation temperature distribution; Environmental information; Heat island ; Land cover classification
Original Abstract: This article describes the application of thermal infrared imaging technology to the urban environment. The method of applying the thermal infrared imaging technique is classified into two parts. One uses thermal infrared images directly for analyzing radiation temperature distribution in urban areas and the other creates environmental information which is effective for assessment of urban environment. Some examples of practical methods including the author's investigations are presented.
 

Hoyano, A.; A. Iino, (1997). Application of high resolution side-looking MSS data to heat island potential in urban area. IGARSS'97. 1997 International Geoscience and Remote Sensing Symposium. Remote Sensing - A Scientific Vision for Sustainable Development (Cat. No.97CH36042) Singapore 3-8 Aug. 1997
New York, NY, USA IEEE, pp.1239-42 vol.3.
Keywords: Air pollution measurement; Atmospheric boundary layer; Atmospheric techniques; Atmospheric temperature; Geophysical techniques; Infrared imaging; Atmosphere; Boundary layer; Temperature; Air pollution; Town city; Remote sensing; Geophysical measurement technique; High resolution side-looking MSS; Multispectral remote sensing; IR imaging; Optical imaging; Heat island potential; Urban area; Side-looking airborne MSS; Surface temperature distribution; Land surface; Complex ground surface form; Residential region; Urban land use change ; Terrain mapping
Original abstract: The authors employed side-looking airborne MSS data with high resolution to investigate the actual conditions of surface temperature distributions in an urban area with the complex ground surface form. In addition, airborne MSS and GIS data were used to calculate the HIP of various types of residential regions, and results verified its effectiveness for monitoring urban land use change and thermal environment.
 

Huber, R., (1998). Airborne InSAR image interpretation towards cartographic mapping. IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings. (Cat. No.98CH36174) Seattle, WA, USA 6-10 July 1998
New York, NY, USA IEEE, pp.1911-13 vol.4.
Keywords: Airborne radar; Bayes methods; Cartography; Feature extraction; Geophysical signal processing; Geophysical techniques; Geophysics computing; Image classification; Image texture; Multilayer perceptrons; Radar imaging; Remote sensing by radar; Synthetic aperture radar; Topography (Earth); Geophysical measurement technique; Land surface topography; Terrain mapping; Radar remote sensing; Interferometric SAR; Airborne InSAR image interpretation; Cartographic mapping; High-resolution; AeS-1 X-Band InSAR; X-band; shf; Microwave radar; Automatic map production; Interpretation task; Coherence image; Elevation; Backscatter image; Image feature; Foreshortening; Shadow ambiguity; Multilayer perceptron classifier; Contextual classification; Bayesian method; Bayes method ; Neural net
Original abstract: The capabilities of the airborne high-resolution AeS-1 X-Band InSAR data for automatic cartographic map production are investigated. The cartographic interpretation task becomes feasible by using coherence images and elevation information provided by InSAR processing additionally to the SAR backscatter image. Moreover, as in visual interpretation, features in SAR images are classified upon their textural appearance and background knowledge. Special attention is paid to SAR foreshortening and shadow ambiguities and their impact onto classification. Those ambiguity areas are derived from the DEM and taken into account in training example selection and a semantic classification step supporting a textural multilayer perceptron classifier. A contextual classification operating on MLP results incorporates class context and a-priori knowledge on class composition by Bayesian information fusion.
 

Huet, B.; E. N. Hancock, (1996). Cartographic indexing into a database of remotely sensed images. Proceeding. Third IEEE Workshop on Applications of Computer Vision. WACV'96 (Cat. No.96TB100084) Sarasota, FL, USA 2-4 Dec. 1996
Los Alamitos, CA, USA IEEE Comput. Soc. Press, pp.8-14.
Keywords: Cartography; Indexing; Remote sensing; Statistical analysis; Visual databases; Cartographic indexing; Remotely sensed images; Simple statistical methods; Application vehicle; Aerial image database; Cartographic model; Semi urban areas; Road network; Imaging distortions; Simple Euclidean transform; Pairwise histograms; Angle differences; Cross ratios; Line segment extraction; Raw aerial images; Sensitivity analysis; Discriminating index; Image distortion; Variable quality ; Input line segmentation
Original abstract: The paper aims to develop simple statistical methods for indexing line patterns. The application vehicle used in this study involves indexing into an aerial image database using a cartographic model. The images contained in the database are of urban and semi urban areas. The cartographic model represents a road network known to appear in a subset of the images contained within the database. There are known to be severe imaging distortions present and the data cannot be recovered by applying a simple Euclidean transform to the model. We effect the cartographic indexing into the database using pairwise histograms of the angle differences and the cross ratios of the lengths of line segments extracted from the raw aerial images. We investigate several alternative ways of performing histogram comparison. Our conclusion is that the Matusita and Bhattachargya distances provide significant performance advantages over the L/sub 2/ norm employed by M. Swain and D. Ballard (1990). Moreover, a sensitivity analysis reveals that the angle difference histogram provides the most discriminating index of line structure; it is robust both to image distortion on to the variable quality of input line segmentation.
 

Hugenschmidt, J. (2000). Railway track inspection using GPR. Journal of Applied Geophysics, V43, (N2-4): 147-155.
Keywords:
Original Abstract: Swiss Federal Railways SBB inspect their railway tracks at regular intervals. The first step of track renewal planning is a geotechnical study. Inspection is focused on the thickness of the ballast, on subsoil material penetrating upwards into the ballast and on geotechnical properties of subgrade and subsoil materials. Up to now, the inspection has been done mainly by digging trenches at evenly spaced intervals and in locations of special interest. In order to evaluate the benefits and limits of GPR railway track inspections, three GPR surveys were carried out on three different railway lines. Data were acquired using a mobile system travelling at 10 kmrh. Subsequent to radar data acquisition, trenches were dug. The positioning of some of the trench locations was based on preliminary GPR results in order to support the interpretation of GPR data. Only those trenches were available during interpretation of radar data. In addition, SBB performed their usual investigation programme. This provided an opportunity for checking the radar results in great detail.
 

Hugenschmidt, J. (1998). Ground Penetrating Radar for road engineering. Materials and Structures, V31, (N207): 192-194.
Keywords:
 
 

Hugenschmidt, J.; M. N. Partl; H. deWitte (1998). GPR inspection of a mountain motorway in Switzerland. Journal of Applied Geophysics, V40, (N1-3): 95-104.
Keywords:
Original Abstract: A radar survey was carried out to support the planning of maintenance work on Switzerland's Gotthard Motorway. This work became necessary after damaged pavement layers had been detected by visual inspection and coring. Radar data acquisition, processing and interpretation focused on the investigation of pavement damage. However, additional information such as layer thicknesses and the position of the rock surface could be extracted from the acquired dataset. Results of the radar survey were verified by local coring and during repair work. The radar survey proved to be a useful complement to traditional pavement monitoring methods providing not only quasi-continuous information between boreholes but also locating previously unknown problem zones. The comparison between datasets that were acquired before and after the maintenance work suggests the success of the repair work and the suitability of GPR as a quality control tool.
 

Hurd, J. D.; D. L. Civco, (1996). Multisource remote sensing data image analysis for Connecticut statewide land cover mapping. GIS/LIS'96 Annual Conference and Exposition Proceedings Proceedings of Geographic Information Systems/Land Information Systems Denver, CO, USA 19-21 Nov. 1996 Bethesda, MD, USA American Society for Photogrammetry & Remote Sensing, pp.564-72.
Keywords: Image processing; Terrain mapping; Remote sensing data image analysis; Connecticut; Statewide land cover mapping; Land cover map; Urban areas ; Pollution modeling
Original abstract: In 1990, under a grant from the joint Long Island Sound Study (LISS) of the Connecticut Department of Environmental Protection and the United States Environmental Protection Agency, land cover maps of the state of Connecticut were prepared through computer-assisted analysis of satellite digital remote sensing data. Land cover information was extracted from multi-seasonal Landsat Thematic Mapper and Multispectral Scanner (MSS) imagery for 23 land cover types. The accuracy of these data has proven to be adequate for the initial purposes for which they were intended, i.e., area-wide nonpoint pollution modeling using land use-dependent coefficients. However, categories of urban and suburban land cover, particularly low density development, were found to be some of the least accurate yet most essential categories for the development of nonpoint load estimates. Urban regions have been found to be a major source of nutrients to rivers, lakes, and estuaries. It has therefore proven necessary to develop a procedure to create a new land cover map which better identifies different densities of urban areas and provides an up-to-date map for the state of Connecticut.
 

Hussin, Y. A., (1995). Effect of polarization and incidence angle on radar return from urban features using L-band aircraft radar data. 1995 International Geoscience and Remote Sensing Symposium, IGARSS '95. Quantitative Remote Sensing for Science and Applications (Cat. No.95CH35770) Firenze, Italy 10-14 July 1995
New York, NY, USA IEEE, pp.178-80 vol.1.
Keywords: Airborne radar; Backscatter; Geophysical techniques; Radar applications; Radar cross-sections; Radar polarimetry; Remote sensing by radar; Geophysical measurement technique; Remote sensing; Terrain mapping; Land surface; Town city; Polarization; Incidence angle; Radar return; UHF L-band; Radar scattering backscatter; Urban features; Aircraft radar; Radar energy reflectance; Buildings; Fence; Tower; Multiple incidence angle; Decimetric; sir-b; Look direction; Objects orientation ; 24.5 cm
Original abstract: The objective of this research was to study the effect of different polarization (HH, VV, VH, and HV) on the radar energy reflectance or backscatter from variety of corner reflectors (e.g. buildings, fences, towers, etc.). Multipolarized and multiple incidence angle L-band (24.5 cm.) JPL (Jet Propulsion Laboratory) aircraft L-band data and SIR-B HH-polarized multiple incidence angle data were used in this study. The results showed that the radar energy reflectance was strongly influenced by radar look direction in relation to objects orientation, type of polarization within the normal range of incidence angle. The corner reflectors were clearly seen and significantly reflect the radar energy on the like-polarized data, but not on the cross-polarized data and low incidence angle. Within the like-polarized data, HH-polarized data showed different pattern of reflectance comparing to the VV-polarized data. This paper discusses the reflectance in different polarizations and the apparent reasons for such radar energy.
 

Hussin, Y. A.; K. D. P. Shantha, (1995). Updating terrain information in topographic databases using radar aircraft images part. III. A change detection approach. 1995 International Geoscience and Remote Sensing Symposium, IGARSS '95. Quantitative Remote Sensing for Science and Applications (Cat. No.95CH35770) Firenze, Italy 10-14 July 1995
New York, NY, USA IEEE, pp.320-2 vol.1.
Keywords: Airborne radar; Cartography; Feature extraction; Geographic information systems; Geophysical signal processing; Geophysical techniques; Radar applications; Radar imaging; Radar polarimetry; Remote sensing; Remote sensing by radar; Topography (Earth); Geophysical measurement technique; Map revision update updating; Land surface; Terrain information; Topographic database; Radar aircraft image; Change detection; Image analysis; Topographic feature; Linear feature; Road; L-band; Automatic feature detection ; Image processing
Original abstract: The main objective of this research was to investigate the use of radar images for updating terrain information in topographic databases. The strategy was to utilize change detection image analysis techniques in addition to conventional methods to detect topographic features in radar images, with special emphasis on linear features (e.g. roads). The results show that main and secondary roads can be visually detected using 7*11 meter (in the range and azimuth) spatial resolution HH-polarized L-band aircraft radar data. Automatic feature detection (conventional and model-based) procedures can be employed for the detection of main roads. However, spatial resolution is important since it was not possible to identify tracks and unpaved roads with low resolution. Hence, for the road feature extraction, a very high resolution image must be used. The experimental results shows positive indications for updating main and secondary roads in road network at 1:25,000 scale.
 

Huston, D.; J. Q. Hu; K. Maser; W. Weedon; C. Adam (2000). GIMA ground penetrating radar system for monitoring concrete bridge decks. Journal of Applied Geophysics, V43, (N2-4): 139-146.
Keywords:
Original Abstract: Ground Penetrating Radar GPR has been investigated as a non-destructive method for evaluating damage in concrete structures. However, the commercially available techniques are limited to detection of gross quantities of deterioration, due to the limited resolution of the system. The objective of this research is to evaluate a ground penetrating radar system with a novel Good Impedance Match Antenna GIMA for concrete structural assessment. This system has the capacity to detect concrete cracks as small as 1 mm thick, while being able to reflect from and detect features at depths of up to 360 mm. Laboratory results of testing of the GIMA antenna by using a step-frequency and a high-frequency impulse system are presented. The experimental results reveal that the GIMA antenna is capable for use in frequency ranges, at least as broad as 500 Mhz to 6 GHz for the step-frequency and 1 to 16 GHz for the high-frequency impulse system.
 

Ifarraguerri, A.; C. I. Chang (2000). Unsupervised hyperspectral image analysis with projection pursuit. Ieee Transactions on Geoscience and Remote Sensing, V38, (N6): 2529-2538.
Keywords: hyperspectral image analysis , projection pursuit, HYDICE, principal component analysis, data compression
Original Abstract: Principal components analysis (PCA) is effective at compressing information in multivariate data sets by computing orthogonal projections that maximize the amount of data variance. Unfortunately, information content in hyperspectral images does not always coincide with such projections. The authors propose an application of projection pursuit (PP), which seeks to find a set of projections that are "interesting," in the sense that they deviate from the Gaussian distribution assumption. Once these projections are obtained, they can be used for image compression, segmentation, or enhancement for visual analysis. To find these projections, a two-step iterative process is followed where they first search for a projection that maximizes a projection index based on the information divergence of the projection's estimated probability distribution from the Gaussian distribution and then reduce the rank by projecting the data onto the subspace orthogonal to the previous projections. To calculate each projection, they use a simplified approach to maximizing the projection index, which does not require an optimization algorithm. It searches for a solution by obtaining a set of candidate projections from the data and choosing the one with the highest projection index. The effectiveness of this method is demonstrated through simulated examples as well as data from the hyperspectral digital imagery collection experiment (HYDICE) and the spatially enhanced broadband array spectrograph system (SEBASS).
 

Ifarraguerri, A.; C. I. Chang (1999). Multispectral and hyperspectral image analysis with convex cones. Ieee Transactions on Geoscience and Remote Sensing, V37, (N2 PT1): 756-770.
Keywords: hyperspectral image analysis , linear spectral unmixing, convex cone analysis, HYDICE (hyperspectral digital imagery collection experiment)
Original Abstract: A new approach to multispectral and hyperspectral image analysis is presented. This method, called convex cone analysis (CCA), is based on the bet that some physical quantities such as radiance are nonnegative. The vectors formed by discrete radiance spectra are linear combinations of nonnegative components, and they lie inside a nonnegative, convex region. The object of CCA is to find the boundary points of this region, which can be used as endmember spectra for unmixing or as target vectors for classification. To implement this concept, the authors find the eigenvectors of the sample spectral correlation matrix of the image. Given the number of endmembers or classes, they select as many eigenvectors corresponding to the largest eigenvalues. These eigenvectors are used as a basis to form linear combinations that have only nonnegative elements, and thus they lie inside a convex cone. The vertices of the convex cone will be those points whose spectral vector contains as many zero elements as the number of eigenvectors minus one. Accordingly, a mixed pixel can be decomposed by identifying the vertices that were used to form its spectrum. An algorithm for finding the convex cone boundaries is presented, and applications to unsupervised unmixing and classification are demonstrated with simulated data as well as experimental data from the hyperspectral digital imagery collection experiment (HYDICE).
 

Iisaka, J.; T. Sakurai-Amano, (1995). Automated terrain feature detection from remotely sensed images integrating spectral, spatial and geometrical attributes of objects. GIS/LIS *95 Annual Conference and Exposition Proceedings of Geographic Information Systems/Land Information Systems Nashville, TN, USA 14-16 Nov. 1995 Bethesda, MD, USA American Soc. Photogrammetry & Remote Sensing & American Congress on Surveying & Mapping, pp.486-95 vol.1.
Keywords: Feature extraction; Genetic algorithms; Geographic information systems; Object recognition; Remote sensing; Town and country planning; Visual databases; Terrain feature detection; Remotely sensed images; Geometrical attributes; Spatial attributes; Spectral attributes; Spatial image computing; Soft computing; Database; Image cue detection; Image cue analysis; Pattern recognition; Terrain feature component analysis; Road feature detection; Urban area delineation; Forest clear-cut area detection ; Ocean cold ring detection
Original abstract: This paper describes an approach to extract terrain features from remotely sensed images by using spatial image computing functions, soft computing functions and a database. The processes to detect terrain features are divided into the detection of image cues which are primal image entities in an image with/without physical meaning, image cue analysis, image object/pattern recognition, terrain feature component analysis and terrain feature identification. Then a unified method for spectral and spatial image processing is described. This method facilitates the implementation of the terrain understanding processes and gives a new perspective in image computing. Some results of using the method of automated terrain feature detection are also demonstrated such as road feature detection from TM data, urban area delineation from SAR image, forest clear-cut area detection from TM data, and ocean cold ring detection which are extracted by using genetic algorithms.
 

Ikuta, K.; N. Yoshikane; N. Vasa; Y. Oki; M. Maeda; M. Uchiumi; Y. Tsumura; J. Nakagawa; N. Kawada (1999). Differential absorption lidar at 1.67 mu m for remote sensing of methane leakage. Japanese Journal of Applied Physics Part 1-Regular Papers Short Notes & Review Papers, V38, (N1A): 110-114.
Keywords:
 
 

Ioannilli, M.; U. Schiavoni, (1996). GIS in transport planning: a districting procedure. Geographical Information from Research to Application Through Cooperation. Second Joint European Conference and Exhibition Proceedings of Joint European Conference on Geographical Information Barcelona, Spain 27-29 March 1996
Amsterdam, Netherlands IOS Press, pp.695-8 vol.1.
Keywords: Geographic information systems; Interactive systems; Town and country planning; Transportation; GIS applications; Transport planning; Districting procedure; Urban areas; Interactive procedure ; Transport model implementation
Original abstract: A number of GIS applications have been developed to support transport planning in urban areas. The flow of an interactive procedure for districting-that is the first step for transport model implementation-is reported.
 

Ito, Y.; S. Omatu, (1997). Polarimetric SAR data classification using scattering models and neural networks. Image Processing, Signal Processing, and Synthetic Aperture Radar for Remote Sensing London, UK 22-26 Sept. 1997
SPIE-Int. Soc. Opt. Eng
Proc. SPIE - Int. Soc. Opt. Eng. (USA), pp.132-40.
Keywords: Backpropagation; Electromagnetic wave scattering; Image classification; Neural nets; Radar polarimetry; Remote sensing by radar; Spaceborne radar; Synthetic aperture radar; Polarimetric SAR data classification; Scattering models; Integrated neural network classifier; Mueller matrix; Stokes vector; Back-propagation; Competitive neural network; lvq1; lvq2.1; SIR-C C-band data; Water category; Factory categories; Urban categories; Learning process; Eight-dimension feature vector; Pseudo relative; Backscattering coefficients; hh ; vv
Original abstract: We consider a polarimetric SAR data classification method which includes scattering models. The proposed method is an integrated neural network classifier composed of two classification procedures. First, SAR data is pre-classified into three scattering classes by individually computing the Mueller matrix and Stokes vector. Second, we construct a neural network appropriate to each scattering class in order to classify the SAR data into realistic categories. Either the competitive or back-propagation neural network is employed as a classifier. The former learns by the LVQ1 and LVQ2.1 algorithms. As a result of the procedure using SIR-C C-band data, pixels in the water category will be classified almost exclusively into the odd class. The even class includes only factory and urban categories. Therefore, it can be concluded that the neural classifier contains a smaller network and a more efficient learning process since it is applied to more limited category classifications. The neural network classifier employs an eight-dimension feature vector with backscattering coefficients and pseudo relative phases between HH and VV from the L and C bands. Average accuracy of the competitive neural network is slightly higher than that of the back-propagation network.
 

Jackson-Pringle, J.; F. K. Wilson, (2000). Use of remote sensing to study the impact of land-cover/land-use change on the environment: a Baltimore area, Maryland case study. IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120) Honolulu, HI, USA 24-28 July 2000
Piscataway, NJ, USA IEEE, pp.2871-3 vol.7.
Keywords: Geophysical techniques; Remote sensing; Terrain mapping; Geophysical measurement technique; Land use; Urban area; Expansion; Optical imaging; Multispectral remote sensing; Town city; United States; usa; Land-cover; Land-use change; Baltimore; Maryland; Land-cover change; Landsat Thematic Mapper; TM image ; AD 1990 to 1999
Original abstract: Remote sensing was utilized, to analyze and study land-use/land-cover change impact on the environment of a section of Baltimore County and City. This study area was selected because it is one of the fastest growing regions in the state of Maryland. This growth (population and land-use activities) continues to exert immense pressure on both its resource and environment. Accordingly, a study was scoped to determine the magnitude of land-use/land-cover change, with special emphasis on transportation, and assess its impact on the local environment over the past ten years. The study utilized data sets obtained from several sources. Such data include remotely sensed imagery, land-use/land-cover maps, hydrology, and roads. The remote sensing data comprised mostly Landsat Thematic Mapper (TM) images acquired from the early 1990 to 1999 with varying temporal internals. The Environment for Visualizing Images (ENVI) was used to process and analyze the data on a Personal Computer (PC) environment. Five level-I land-use/land-cover categories (urban, vegetation, cultivated, mix (bare/built-Up), and Water) were analyzed for change in an attempt to reveal a general pattern and trend. Initial analysis of the TM images for 1990 and 1999 showed increase in the urban category and a decrease in the cultivated land. The final results from this study are expected to be beneficial to scientists, resource planners, managers, and policy makers.
 

Jarvis, C. H.; N. Stuart (1996). The sensitivity of a neural network for classifying remotely sensed imagery. Computers & Geosciences, 22, (9): 959-67.
Keywords: Backpropagation; Feedforward neural nets; Image classification; Learning (artificial intelligence); Remote sensing; Sensitivity; Neural network sensitivity; Remotely sensed imagery classification; Feedforward backpropagation neural network; Urban land cover classification; Landsat TM data; Network nodes; Hidden layers; Input layers; Surplus nodes; Momentum; Network learning; Optimal pairing; Convergence; Dockland area; Parametric method; Parametric classifiers; Network parameters; Training times ; Accuracy
Original Abstract: A series of experiments are conducted on a feedforward backpropagation neural network which is used to classify land cover from Landsat TM data. By investigating the effects of changing the numbers of network nodes in the input and hidden layers, potentially surplus nodes can be identified and removed to create a more compact network, without loss of classification accuracy. By exploring how momentum can be used with different rates of network learning, an optimal pairing is found which leads to a more rapid convergence and better classification of urban land cover than obtained in previous studies where momentum rarely was used. These optimal network parameters are used to classify an extract of a Landsat TM image of a dockland area with accuracy equal to that obtained using the maximum likelihood method. Given that in this case, the nature of the image data is ideal for a parametric method, this result is not unexpected. The competence of the neural technique is however demonstrated and criteria are given to help determine in advance when neural techniques may be preferable to parametric classifiers. Taken together, the findings show that careful balancing and adjustment of network parameters may be required to obtain a satisfactory result. The method can guide new users in configuring a popular neural network to suit their image data. Given the specific nature of our results, further research on neural networks in remote sensing could benefit from more systematic reporting of network parameters, training times and accuracies obtained.
 

Jaynes, C., (1999). View alignment of aerial and terrestrial imagery in urban environments. Integrated Spatial Databases. Digital Images and GIS. International Workshop ISD'99. Selected Papers (Lecture Notes in Computer Science Vol.1737) Proceedings of NSFWS99: International Workshop on Integrated Spatial Databases: Digital Images and GIS Portland, ME, USA 14-16 June 1999
Berlin, Germany Springer-Verlag, pp.3-19.
Keywords: Computational geometry; Geographic information systems; Image reconstruction; Image registration; Image texture; Photography; Remote sensing; Sensor fusion; Surveillance; Town and country planning; View alignment; Aerial imagery; Terrestrial imagery; Urban environments; Information fusion; Automatic model reconstruction; High-resolution building models; Built-up areas; Calibrated aerial photography; Building location; Building 2D footprint; Rooftop shape; Ground-level images; Close-range high-resolution views; Pose information; 3D model; Symbolic model matching; Pose refinement technique; High-resolution facade texture mapping; Model geometry; Segmentation; Pixel regions; Vertical structures; Context-sensitive processing; Symbolic extraction ; Surface structures
Original abstract: Introduces an algorithm that fuses information from aerial and terrestrial views for the automatic reconstruction of high-resolution building models within built-up areas. Calibrated aerial photography is commercially available for wide areas of coverage and has been shown to be a useful source of information about the location of buildings at the site, their 2D footprint and their rooftop shape. In contrast, terrestrial imagery is usually uncalibrated, not available commercially for most urban areas, and difficult to acquire. These ground-level images do, however, provide close-range, high-resolution views that are not normally available in aerial data. Our approach uses the pose information typically associated with aerial surveillance imagery to acquire an initial 3D model of the buildings at the site. Uncontrolled terrestrial imagery is then aligned to the model using a symbolic model matching and pose refinement technique. Once aligned, ground-level views can be used to enhance the site model in a number of ways. High-resolution facade textures can be mapped onto the model geometry using the recovered pose information and standard texture-mapping algorithms. The same algorithms allow explicit segmentation of building facades from terrestrial views as regions of pixels that project on to vertical structures in the model. Context-sensitive processing can be applied to these facade regions for the symbolic extraction of surface structures such as windows, doors and pillars.
 

Jensen, J. R.; D. C. Cowen (1999). Remote sensing of urban suburban infrastructure and socio-economic attributes. Photogrammetric Engineering and Remote Sensing, V65, (N5): 611-622.
Keywords:
 
 

Jensen, J. R.; D. J. Cowen; J. Halls; S. Narumalani; N. J. Schmidt; B. A. Davis; B. Burgess (1994). Improved Urban Infrastructure Mapping and Forecasting for Bellsouth Using Remote Sensing and Gis Technology. Photogrammetric Engineering and Remote Sensing, V60, (N3): 339-346.
Keywords:
 
 

Jian, L.; W. Renbiao (1998). An efficient algorithm for time delay estimation. IEEE Transactions on Signal Processing, 46, (8): 2231-5.
Keywords: Delays; Fourier transforms; Least squares approximations; Parameter estimation; Pattern classification; Radar applications; Radar detection; Radar signal processing; Time delay estimation; Computationally efficient algorithm; wrelax; Relaxation-based minimizer; Nonlinear least squares; Roadway subsurface anomalies detection; Subsurface anomalies classification; Ultra-wideband ground-penetrating radar; Performance; Weighted Fourier transform ; Range resolution
Original Abstract: We present a conceptually simple and computationally efficient algorithm, which is referred to as WRELAX for the well-known time delay estimation problem. The method is a relaxation-based minimizer of a complicated nonlinear least squares criterion, WRELAX can be applied to detecting and classifying roadway subsurface anomalies by using an ultra-wideband ground-penetrating radar. Numerical and experimental examples are provided to demonstrate the performance of the new algorithm.
 

Jimenez, L. O.; D. A. Landgrebe (1999). Hyperspectral data analysis and supervised feature reduction via projection pursuit. Ieee Transactions on Geoscience and Remote Sensing, V37, (N6): 2653-2667.
Keywords: hyperspectral data analysis , projection pursuit
Original Abstract: As the number of spectral bands of high-spectral resolution data increases, the ability to detect more detailed classes should also increase, and the classification accuracy should increase as well. Often the number of labelled samples used for supervised classification techniques is limited, thus limiting the precision with which class characteristics can be estimated. As the number of spectral bands becomes large, the limitation on performance imposed by the limited number of training samples can become severe. A number of techniques for case-specific feature extraction have been developed to reduce dimensionality without loss of class separability. Most of these techniques require the estimation of statistics at full dimensionality in order to extract relevant features for classification. If the number of training samples is not adequately large, the estimation of parameters in high-dimensional data will not be accurate enough. As a result, the estimated features may not be as effective as they could be. This suggests the need for reducing the dimensionality via a preprocessing method that takes into consideration high-dimensional feature-space properties. Such reduction should enable the estimation of feature-extraction parameters to be more accurate. Using a technique referred to as projection pursuit (PP), such an algorithm has been developed. This technique is able to bypass many of the problems of the limitation of small numbers of training samples by making the computations in a lower-dimensional space, and optimizing a function called the projection index. A current limitation of this method is that, as the number of dimensions increases, it is likely that a local maximum of the projection index will be found that does not enable one to fully exploit hyperspectral-data capabilities.
 

Jinwook, G.; L. Chulhee, (2000). Analytical decision boundary feature extraction for neural networks. IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120) IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Honolulu, HI, USA 24-28 July 2000
Piscataway, NJ, USA IEEE, pp.3072-4 vol.7.
Keywords: Feature extraction; Feedforward neural nets; Geophysical signal processing; Geophysical techniques; Geophysics computing; Image processing; Remote sensing; Terrain mapping; Geophysical measurement technique; Land surface; Neural net; Decision boundary; Analytical method; Feedforward neural network; Normal vector; 3 layer ; Sigmoid function
Original abstract: Recently, a feature extraction method based on decision boundary has been proposed for neural networks. The method is based on the fact that the vector normal to the decision boundary contains information useful for discriminating between classes. However, the normal vector was estimated numerically, resulting in inaccurate estimation and a long computational time. The authors propose a new method to calculate the normal vector analytically and derive all the necessary equations for 3 layer feedforward neural networks with a sigmoid function. Experiments show that the proposed method provides a noticeably improved performance.
 

Johnston, R. A.; T. De La Barra (2000). Comprehensive regional modeling for long-range planning: linking integrated urban models and geographic information systems. Transportation Research, Part A (Policy and Practice), 34A, (2): 125-36.
Keywords: Geographic information systems; Town and country planning; Transportation; Regional modeling; Long-range planning; Integrated urban models; Regional transportation; Land use policies; tranus; Market-based urban model; Land allocation model; Regional policy assessments; Spatial competition ; User welfare
Original Abstract: Demonstrates the sequential linking of two types of models to permit the comprehensive evaluation of regional transportation and land use policies. First, we operate an integrated urban model (TRANUS), which represents both land and travel markets with zones and networks. The travel and land use projections from TRANUS are outlined, to demonstrate the general reasonableness of the results, as this is the first application of a market-based urban model in the US. Second, the land use projections for each of the 58 zones in the urban model were fed into a geographic information system (GIS)-based land allocation model, which spatially allocates the several land uses within each zone according to simple accessibility rules. While neither model is new, this is one of the first attempts to link these two types of models for regional policy assessments. Other integrated urban models may be linked to other GIS land allocation models in this fashion. Pairing these two types of models allows the user to gain the advantages of the urban models, which represent spatial competition across a region and produce measures of user welfare (traveler and locator surplus), and the advantages of the GIS land allocation models, which produce detailed land use maps that can then be used for environmental impact assessment.
 

Jones, K. J., (2000). 2D wavelet feature detection for defining curved boundaries in Landsat images. Image and Video Communications and Processing 2000 San Jose, CA, USA 25-28 Jan. 2000
SPIE-Int. Soc. Opt. Eng
Proc. SPIE - Int. Soc. Opt. Eng. (USA), pp.796-806.
Keywords: Agriculture; Edge detection; Feature extraction; Remote sensing; Vegetation mapping; Wavelet transforms; 2D wavelet feature detection; Curved boundaries; Landsat images; Multiscale feature detection; Homogeneous regions; Crops; Man-made boundaries; River beds; 2-D curve; 2-D edges ; Remote sensing images
Original abstract: Multiscale feature detection is extended over a large region of Landsat images to define boundaries between homogeneous regions formed by individual crops. It is expected that it will be possible to define a grid between homogeneous regions defined by both man-made boundaries (2-D edges) and river beds (2-D curves) which define the availability of water. This approach might be usefully applied to remote sensing images based on other wavelengths (i.e. IR or laser remote sensing).
 

Jong-Hyn, P.; R. Tateishi; K. Wikantika; P. Jong-Geol, (1999). The potential of high resolution remotely sensed data for urban infrastructure monitoring. IEEE 1999 International Geoscience and Remote Sensing Symposium. IGARSS'99 (Cat. No.99CH36293) Hamburg, Germany 28 June-2 July 1999
Piscataway, NJ, USA IEEE, v.V2, pp.1137-9.
Keywords: Multisource imagery Urban infrastructure monitoring, High spatial resolution
Original abstract: The object of this research investigated the urban infrastructure monitoring using high resolution remotely sensed data. Multi-source imagery with high spatial resolution has great potential to improve the performance of detailed urban expansion and infrastructure analysis. These images allowed for continual monitoring of infrastructure needs. Multi-temporal analysis of satellite imagery is effective for urban growth and changes of infrastructure because a high correlation exists between spectral variation in images from different dates and urban land cover change.
 

Jong-Hyun, P.; R. Tateishi; S. Dong-Jo; P. Chong-Hwa, (1998). Urban expansion and change analysis using Russian 2m resolution DD-5, IRS-1C, and Landsat TM data. IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings. (Cat. No.98CH36174) Seattle, WA, USA 6-10 July 1998
New York, NY, USA IEEE, pp.2577-9 vol.5.
Keywords: Geophysical signal processing; Geophysical techniques; Remote sensing; Sensor fusion; Terrain mapping; Town and country planning; Geophysical measurement technique; Land surface; Land use; Town planning; Multispectral remote sensing; Image processing; Urban expansion; Change analysis; dd-5; irs-1c; Landsat TM; Land cover; Agricultural land; Multisource information fusion; Multisource imagery; Korea ; Seoul
Original abstract: This research was a pilot study for urban feature interpretation and change analysis using multisource data. Data are used Landsat TM, IRS-1C, and Russian 2m high resolution photographic image (DD-5). The objective of this research is to analyze change in land cover from agricultural land to a construction site or residential development using multisource information fusion. Firstly, this study is to fuse the spectral information from Landsat TM combine it with the spatial information from DD-5 and IRS-1C. This data combination is essential for the change detection and analysis. Secondly, this study is to compare the development of the town, which is based on natural and artificial features before the new town construction. The agricultural and forest area were destroyed and urbanized by 5 new town constructions of The Seoul metropolitan region. The authors' conclusions are that multisource imagery with moderate spatial resolution has potential to improve the performance of detailed information to policy maker for regional planning and decision making.
 

Kabanov, M. M.; S. N. Kapustin, (1998). Detecting buildings by remote sensing of urban territories. Ascending and descending strategy of control. Pattern Recognition and Image Analysis: New Information Technologies (PRIA-3-97) Moscow, Russia Dec. 1997
MAIK Nauka/Interperiodica Publishing
Pattern Recognit. Image Anal. (Russia), pp.315-16.
Keywords: Image enhancement; Image segmentation; Object detection; Remote sensing; Urban territories; Buildings detection; Mapping; Raster image; Space pictures; Aerial pictures; Raster processing ; Sequential detection
Original abstract: The updating of maps of urban territories is one of the most difficult problems of modern mapping. The need for the constant renewal of the maps necessitates the automation of input and updating of the information. The detection of buildings in the raster image (aerial and space pictures) is one of the key problems in this case. We developed and realized two methods of raster processing for building detection (with an ascending and descending strategy of control) that provide the best results when combined. Both methods are based on the stepwise processing of the raster image with sequential detection of the necessary objects.
 

Kageyama, Y.; M. Nishida; T. Oi, (2000). Analysis of the segments extracted by automated lineament detection. IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120) IGARSS 2000. Honolulu, HI, USA 24-28 July 2000
Piscataway, NJ, USA IEEE, pp.289-91 vol.1.
Keywords: Earth crust; Feature extraction; Geology; Geophysical signal processing; Geophysical techniques; Image segmentation; Pattern recognition; Radar imaging; Remote sensing; Remote sensing by radar; Synthetic aperture radar; Tectonics; Topography (Earth); Geophysical measurement technique; Land surface; Topography; Relief; Multispectral remote sensing; Optical imaging; Crust structure; Automated lineament detection; Fault; Lineament detection; Automatic extraction; Image processing; sar; Landsat 5 thematic mapper; Stream pattern; Subsurface structure; Drainage system ; Radar remote sensing
Original abstract: Lineaments are important features showing subsurface elements or structural weaknesses such as faults. Most lineament maps have been drawn based on fieldwork by experts and visual analysis of enhanced image data. In visual interpretation and mapping of lineaments, geologists use their knowledge and experience to extract the lineaments from the curved and straight lines in image data. A different expert may extract different segment elements through a visual approach. In order to conduct the lineament detection under the same conditions, automatic extraction for lineaments though image processing is useful. In an earlier paper, an extraction method for lineaments using airborne Synthetic Aperture Radar (SAR) data was presented. The results indicated that the segments given by the method agree with a lineament map drawn by experts. The objective of this paper is to examine the relationship between extracted segments from both airborne SAR and Landsat 5 thematic mapper (TM) data and geographical features. River erosion creates various stream patterns that are influenced by the subsurface structure. Many lineaments can be extracted from a drainage system for topography. This paper seeks to compare extracted segments and water systems. Also, relief energies can indicate the level of the river erosion. The relief energy at a study site has been compared and the correspondence between the computation and extracted segments is described. Finally, the difference between segments in SAR and TM data has been compared.
 

Katartzis, A.; H. Sahli; V. Pizurica; J. Cornelis (2001). A model-based approach to the automatic extraction of linear features from airborne images. IEEE Transactions on Geoscience and Remote Sensing, 39, (9): 2073-9.
Keywords: Feature extraction; Geophysical signal processing; Geophysical techniques; Radar imaging; Remote sensing; Remote sensing by radar; Terrain mapping; Geophysical measurement technique; Land surface; Radar remote sensing; Image processing; Model-based approach; Automatic extraction; Linear feature; Airborne image; Road; Path; sar; Airborne image analysis; Synthetic aperture radar ; Optical imaging
Original Abstract: The authors describe a model-based method for the automatic extraction of linear features, like roads and paths, from aerial images. The paper combines and extends two earlier approaches for road detection in SAR satellite images and presents the modifications needed for the application domain of airborne image analysis together with representative results.
 

Kaufman, Y. J.; D. Tanre (1996). Strategy for Direct and Indirect Methods for Correcting the Aerosol Effect on Remote Sensing - from Avhrr to Eos-Modis. Remote Sensing of Environment, V55, (N1): 65-79.
Keywords:
Original Abstract: Aerosol scatters solar radiation before it reaches the surface and scatters and absorbs it again after it is reflected from the surface and before it reaches the satellite sensor. The effect is spectrally and spatially dependent. Therefore, atmospheric aerosol (dust, smoke, and air pollution particles) has a significant effect on remote sensing. Correction for the aerosol effect on remote sensing of land areas was never achieved on an operational basis though several case studies were demonstrated. We distinguish between direct correction, in which the aerosol loading is derived from the image itself (or supplied from external sources) followed by correction of the image using an appropriate radiative transfer model, and indirect correction, achieved by defining remote sensing functions that are less dependent on the aerosol loading. To some degree this was already achieved in global remote sensing of vegetation where a composite of several days of the normalized difference vegetation index (NDVI) measurements, choosing the maximal value, was used instead of a single cloud-screened value. The atmospheric resistant vegetation index (ARVI) introduced recently for the Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) is the most appropriate example of indirect correction, where the index is defined in such a way that the atmospheric effect in a blue spectral channel cancels to a large degree the atmospheric effect in the red channel in computations of the vegetation index. Atmospheric corrections can also use aerosol climatology or simultaneous measurements with ground-based instrumentation. These aspects of aerosol studies and remote sensing are reviewed in this article. New advances in ground-based instrumentation and future satellite systems (including measurements of polarization) are discussed. In the conclusions a strategy is introduced for a combination of ground-based measurements, with direct and indirect corrections that is implemented for the EOS-MODIS and recommended for other similar platforms. Such strategy, planned in advance, is a first step to face the challenge and take advantage of the opportunities that the remote sensing community will face with the launch of EOS and ADEOS in the next several years.
 

Kavzoglu, T.; P. M. Mather, (2000). Using feature selection techniques to produce smaller neural networks with better generalisation capabilities. IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120) IGARSS 2000. Honolulu, HI, USA 24-28 July 2000
Piscataway, NJ, USA IEEE, pp.3069-71 vol.7.
Keywords: Feature extraction; Geophysical signal processing; Geophysical techniques; Geophysics computing; Neural nets; Remote sensing; Terrain mapping; Geophysical measurement technique; Land surface; Image processing; Feature selection; Smaller neural network; Neural net size; Generalisation; Optimum network size ; Input features
Original abstract: The issue of feature selection is of considerable importance, particularly where artificial neural networks are used, as the size of the network is directly related to the number of input sources. Despite the fact that artificial neural networks have been applied to solve many problems in different fields, and found to be superior to conventional statistical classifiers, they have a major drawback: the need to define the optimum network size for a particular problem. In remote sensing applications, which are generally in the area of image classification, the use of more input features would make the network overspecific to the training data. Over-specificity reduces the generalisation capabilities of a neural network.
 

Keechoo, C.; P. Incheol, (1996). A spatial decision support system for transportation planning and investment decision analysis. URISA Proceedings, Annual Conference. Papers from the Annual Conference of the Urban and Regional Information Systems Association Proceedings of URISA 1996 Annual Meeting on Information Systems Salt Lake City, UT, USA 27 July-1 Aug. 1996
Washington, DC, USA Urban & Regional Inf. Syst. Assoc, pp.222-31.
Keywords: Decision support systems; Economics; Expert systems; Geographic information systems; Traffic information systems; Transportation; Visual databases; Transportation planning; Investment decision analysis; Expert spatial decision support system; Data layers; Economic feasibility study; Operating cost savings; GIS database; Sensitivity analysis; Cost data changes; Economic efficiency indices; Benefit/cost ratio; Net present value; Infrastructure expansion plans; Developing countries; Transportation planning model; Economic feasibility model; Optimum route selection procedure ; Integrated GIS architecture
Original abstract: The paper proposes a more normative use of GIS for transportation within the framework of an expert spatial decision support system-how GIS can be exploited for generating optimum route based on such data layers as slope, land use, aspect, and land value, etc. Coupled with transportation planning models, GIS may be an efficient tool for conducting an economic feasibility study of the proposed routes. That is, both benefits (time and operating cost savings) and costs (construction and maintenance) may be easily calculated based on GIS database. In addition, sensitivity analysis can be easily conducted with cost data changes and various economic efficiency indices (such as benefit/cost ratio, net present value and/or internal rate of return) can be calculated. Considering numerous infrastructure expansion plans especially in developing countries, the methodology combining transportation planning model, optimum route selection procedure, GIS, and economic feasibility model seems to be useful for evaluating economic feasibility of the route proposed. In this sense, the purpose of the paper is both to propose a structure of integrating different models and methodologies for route selection and its evaluation inside an integrated GIS architecture.
 

Keechoo, C.; J. Wonjae (2000). Development of a transit network from a street map database with spatial analysis and dynamic segmentation. Transportation Research Part C (Emerging Technologies), 8C, (1-6): 129-46.
Keywords: Geographic information systems; Service industries; Transportation; Visual databases; Transit network development; Street map database; Spatial analysis; Dynamic segmentation; Integrated transit-oriented travel demand modeling procedure; gis; Transit stop digitizing; Route system building; Topological relation; Street map databases; Legacy urban transportation planning systems; utps; Travel modeling packages; Omnibus route design ; 'bus route planning
Original Abstract: This paper presents an integrated transit-oriented travel demand modeling procedure within the framework of geographic information systems (GIS). Focusing on transit network development, this paper presents both the procedure and algorithm for automatically generating both link and line data for transit demand modeling from the conventional street network data using spatial analysis and dynamic segmentation. For this purpose, transit stop digitizing, topology and route system building, and the conversion of route and stop data into link and line data sets are performed. Using spatial analysis, such as the functionality to search arcs nearest from a given node, the nearest stops are identified along the associated links of the transit line, while the topological relation between links and line data sets can also be computed using dynamic segmentation. The advantage of this approach is that street map databases represented by a centerline can be directly used along with the existing legacy urban transportation planning systems (UTPS) type travel modeling packages and existing GIS without incurring the additional cost of purchasing a full-blown transportation GIS package. A small test network is adopted to demonstrate the process and the results. The authors anticipate that the procedure set forth in this paper will be useful to many cities and regional transit agencies in their transit demand modeling process within the integrated GIS-based computing environment.
 

Keenan, P. B. (1998). Spatial decision support systems for vehicle routing. Decision Support Systems, 22, (1): 65-71.
Keywords: Decision support systems; Geographic information systems; Management science; Transportation; Visual databases; Spatial decision support systems; Vehicle routing ; Decision making
Original Abstract: The vehicle routing field is a well-developed area of management science application. There is increasing recognition that effective decision making in this field requires the incorporation of vehicle routing techniques into a decision support system (DSS). In order to provide decision support for a wide range of problems, routing techniques should be combined with systems that can take advantage of new technologies. These include spatial techniques drawn from the field of geographic information systems (GIS). A synthesis of appropriate algorithms and a GIS based computer system is identified as being necessary for effective decision support for the vehicle routing problem.
 

Kennedy, R. E.; W. B. Cohen; G. Takao (1997). Empirical methods to compensate for a view-angle-dependent brightness gradient in AVIRIS imagery. Remote Sensing of Environment, V62, (N3): 277-291.
Keywords: AVIRIS
Original Abstract: A view-angle-dependent brightness gradient was observed in an AVIRIS image of a forested region in Oregon's Cascade Mountains. A method of removing the view-angle effect was sought that would not alter the radiometric integrity of the image, and which would require minimal ancillary information. Four methods were tested and evaluated in terms of remaining brightness gradient and in terms of retention of spectral characteristics. All methods used a quadratic fitting equation to model the changes in brightness across view angles. Other descriptive coefficients were calculated to aid in interpretation. The observed view-angle effect varied with wavelength in a manner consistent with predictions of bidirectional reflectance distribution function characteristics for vegetation. View-angle effects were determined to contain both additive and multiplicative components, with multiplicative components being strong in the chlorophyll absorption region. The view-angle effect in a given pixel was a function of both an underlying view-angle response determined by surface structure and the inherent brightness of that pixel. The most successful compensation method was the one that best accounted for broad differences between pixels in these two components. Despite the simplifying assumptions necessary for empirical view-angle correction techniques, they can still be useful for hyperspectral remote-sensing data in situations where the view-angle brightness variations would mask variance useful for extracting scene information.
 

Kiema, J. B. K., (2000). Wavelet compression and data fusion: An investigation into the automatic classification of urban environments using colour photography and laser scanning data. Proceedings 15th International Conference on Pattern Recognition. Barcelona, Spain 3-7 Sept. 2000
Los Alamitos, CA, USA IEEE Comput. Soc, pp.85-9 vol.3.
Keywords: Data compression; Feature extraction; Image classification; Image coding; Image segmentation; Infrared imaging; Maximum likelihood estimation; Photogrammetry; Remote sensing by laser beam; Sensor fusion; Terrain mapping; Wavelet compression; Data fusion; Urban environments; Colour photography; Automatic classification; Airborne laser scanning data; Colour infrared imagery; Context information; Feature base; Nonspectral features; Spectral features; Maximum likelihood classification approach; Urban scenes ; Wavelet-based algorithm
Original abstract: The field of wavelets has opened up new opportunities for the compression of satellite sensory imagery. The paper examines the influence of wavelet compression on the automatic classification of urban environments. Airborne laser scanning data is introduced as an additional channel along-side the spectral channels of colour infrared imagery. This effectively integrates the local height and multi-spectral information sources. To incorporate context information, the feature base is expanded to include both spectral and non-spectral features. A maximum likelihood classification approach is then applied. It is demonstrated that the classification of urban scenes is considerably improved by fusing multi-spectral and geometric data sets. The fused imagery is then systematically compressed (channel by channel) at compression rates ranging from 5 to 100 using a wavelet-based algorithm. The compressed imagery is then classified using the approach described here-above. Analysis of the results obtained indicates that a compression rate of up to 20 can conveniently be employed without adversely affecting the segmentation results.
 

Kim, K.; N. Levine (1996). Using GIS to improve highway safety. Computers, Environment and Urban Systems, 20, (4-5): 289-302.
Keywords: Data analysis; Geographic information systems; Safety; Traffic information systems; Visual databases; gis; Highway safety; United States; Intermodal Surface Transportation Efficiency Act; istea; Information management systems; Public resources; Traffic safety GIS prototype; Spatial analysis; Traffic collisions; Hawaii ; Motor vehicle collisions
Original Abstract: In the United States the Intermodal Surface Transportation Efficiency Act (ISTEA) of 1991 has encouraged the development of information management systems. GIS, to promote safety and efficient expenditure of public resources, is an example. This paper therefore describes the development of a traffic safety GIS prototype for spatial analysis of traffic collisions in Honolulu, Hawaii. Various classes of spatial analyses, which involve points, segments, and zones, with special reference to the nature of motor vehicle collisions and traffic safety research, have been developed.
 

Kimura, H.; H. Kinoshita, (2000). Interferometric features of land surface from a series of JERS-1 SAR interferograms. IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120) Honolulu, HI, USA 24-28 July 2000
Piscataway, NJ, USA IEEE, pp.2227-9 vol.5.
Keywords: Geophysical techniques; Remote sensing by radar; Spaceborne radar; Synthetic aperture radar; Terrain mapping; Vegetation mapping; Geophysical measurement technique; Land surface; Radar remote sensing; Interferometric feature; jers-1; SAR interferogram; InSAR; Differential interferometry; Corner reflector; Ground reference points; Coherency; Differential phase; Land surface type; Forest; Urban; Residential; Paddy; Agriculture ; Farm
Original abstract: Experiments for differential interferometry were conducted over sixteen months using corner reflectors (CRs). From eleven scenes acquired during the period, four high-quality interferograms are produced. Using CRs as ground reference points, baselines are estimated. Referring to the digital elevation model (DEM), topographic effects are removed. Interferometric features (coherency and differential phase) are analyzed for typical land surface types; i.e. forest, urban, residential, paddy and farm.
 

Kolbe, T. H.; L. Plumer; A. B. Cremers, (1996). Using constraints for the identification of buildings in aerial images. PACT 96. Proceedings of the Second International Conference on the Practical Application of Constraint Technology Proceedings of PACT 96. London, UK 24-26 April 1996
Blackpool, UK Practical Application Company, pp.143-54.
Keywords: Constraint handling; Feature extraction; Geographic information systems; Logic programming languages; Object detection; Town and country planning; Building identification; Aerial images; Geo information systems; Photogrammetry; Image processing; Low level syntactic operators; Line detectors; Simple pattern matchers; Explicit models; Semantically meaningful objects; Representation formalisms; Extracted image features; Aspect graphs; Constructive solid geometry; Constraint logic programming; Representation formalism; Implementation language; Strong heuristics ; Complex search problem
Original abstract: Aerial images constitute an important data source for geo information systems. In order to get actual data at reasonable costs, the development of (semi) automatic tools has been an active research topic in photogrammetry and image processing in the recent years. Based on established techniques for low level syntactic operators such as filters, feature extraction, line detectors and simple pattern matchers, nowadays there is strong interest in explicit models in order to improve the identification of semantically meaningful objects. From the pixel to the object level, several representation formalisms such as graphs of extracted image features, aspect graphs and constructive solid geometry (CSG) are applied. Constraint logic programming has been identified as an adequate representation formalism and implementation language for building the necessary experimental environment, specifying the models on the different levels, expressing strong heuristics and approaching the complex search problem involved in object detection. The paper focusses on the detection of buildings. It discusses model representation by CLP program fragments and the required adaption and extensions of the CLP(FD) solver of ECLIPSE, the Prolog/CLP platform underlying our implementation. Illustrating examples show how the problems arising in the detection of buildings are approached by CLP techniques.
 

Kumar, S.; J. Ghosh; M. M. Crawford (2001). Best-bases feature extraction algorithms for classification of hyperspectral data. IEEE Transactions on Geoscience and Remote Sensing, 39, (7): 1368-79.
Keywords: Feature extraction; Geophysical signal processing; Geophysical techniques; Image classification; Multidimensional signal processing; Remote sensing; Terrain mapping; Geophysical measurement technique; Land surface; Multispectral remote sensing; Hyperspectral remote sensing; Best bases feature extraction algorithm; Top-down algorithm; Bottom-up algorithm; Agglomerative tree ; Fisher direction
Original Abstract: Due to advances in sensor technology, it is now possible to acquire hyperspectral data simultaneously in hundreds of bands. Algorithms that both reduce the dimensionality of the data sets and handle highly correlated bands are required to exploit the information in these data sets effectively. the authors propose a set of best-bases feature extraction algorithms that are simple, fast, and highly effective for classification of hyperspectral data. These techniques intelligently combine subsets of adjacent bands into a smaller number of features. Both top-down and bottom-up algorithms are proposed. The top-down algorithm recursively partitions the bands into two (not necessarily equal) sets of bands and then replaces each final set of bands by its mean value. The bottom-up algorithm builds an agglomerative tree by merging highly correlated adjacent bands and projecting them onto their Fisher direction, yielding high discrimination among classes. Both these algorithms are used in a pairwise classifier framework where the original C-class problem is divided into a set of (/sub 2//sup C/) two-class problems. The new algorithms (1) find variable length bases localized in wavelength, (2) favor grouping highly correlated adjacent bands that, when merged either by taking their mean or Fisher linear projection, yield maximum discrimination, and (3) seek orthogonal bases for each of the (/sub 2//sup C/) two-class problems into which a C-class problem can be decomposed. Experiments on an AVIRIS data set for a 12-class problem show significant improvements in classification accuracies while using a much smaller number of features.
 

Kumar, S.; J. Ghosh; M. M. Crawford, (2000). Multiresolution feature extraction for pairwise classification of hyperspectral data. Applications of Artificial Neural Networks in Image Processing V San Jose, CA, USA 27-28 Jan. 2000
SPIE-Int. Soc. Opt. Eng
Proc. SPIE - Int. Soc. Opt. Eng. (USA), pp.60-71.
Keywords: Computational complexity; Correlation methods; Feature extraction; Geophysical signal processing; Image classification; Image resolution; Terrain mapping; Multiresolution feature extraction; Pairwise classification; Hyperspectral data; Landcover type prediction; Airborne sensors; Spaceborne sensors; Remote sensing; Hyperspectral data acquisition; EM spectrum; Electromagnetic spectrum window; Statistically correlated bands; Efficient top-down multiresolution class-dependent feature extraction algorithm; Pairwise classification scheme; Recursive band decomposition; Subspaces ; AVIRIS data set
Original abstract: Prediction of landcover type from airborne/spaceborne sensors is an important classification problem in remote sensing. Due to advances in sensor technology, it is now possible to acquire hyperspectral data simultaneously in more than 100 bands, each of which measures the integrated response of a target over a narrow window of the electromagnetic spectrum. The bands are ordered by their wavelengths and spectrally adjacent bands are generally statistically correlated. Using such high dimensional data for classification of landcover potentially provides greatly improved results. However, it is necessary to select bands that provide the best possible discrimination among the classes of interest. In this paper, we propose an efficient top-down multiresolution class-dependent feature extraction algorithm for hyperspectral data to be used with a pairwise classification scheme. First, the C class problem is divided into (/sup C//sub 2/) two class problems. Features for each pair of classes are extracted independently. The algorithm decomposes the bands recursively into groups of adjacent bands (subspaces) in a top-down fashion. The features extracted are specific to the pair of classes that are being distinguished and exploit the ordering information in the hyperspectral data. Experiments on a 183 band AVIRIS data set for a 12 class problem show significant improvements in both classification accuracies and the number of features required for all 66 pairs of classes.
 

Kuo-Tu, K., (1995). Using back-propagation neural networks and image processing techniques to identify roads in Landsat TM imagery. Intelligent Engineering Systems Through Artificial Neural Networks. Vol.5. Fuzzy Logic and Evolutionary Programming. Proceedings of the Artificial Neural Networks in Engineering (ANNIE'95) Proceedings of Intelligent Engineering Systems through Artificial Neural Networks St. Louis, MO, USA 12-15 Nov. 1995
New York, NY, USA ASME Press, pp.809-14.
Keywords: Backpropagation; Image recognition; Neural nets; Object detection; Remote sensing; Traffic engineering computing; Back-propagation neural networks; Image processing techniques; Road identification; Landsat TM imagery; Landsat Thematic Mapper satellite images; Interstate highways; Bridges; Urban area roads; Residential area roads ; Parkways
Original abstract: The research reported in this paper investigates an automated technique for the detection of roads (interstate highways, two-lane highways, bridges, urban area roads, residential area roads, and parkways) in Landsat Thematic Mapper satellite images. It is shown that the hybrid system which combines traditional image processing techniques with back-propagation neural networks performs better than using only image processing techniques or only neural network techniques.
 

Kurtz, J. L.; J. M. Cowdery; J. H. Meloy; C. H. Overman, (2000). Subsurface measurements utilizing the fusion of ground-coupled and air-launched GPR. Subsurface Sensing Technologies and Applications II San Diego, CA, USA 31 July-3 Aug. 2000
SPIE-Int. Soc. Opt. Eng
Proc. SPIE - Int. Soc. Opt. Eng. (USA), pp.466-73.
Keywords: Civil engineering; Permittivity measurement; Radar signal processing; Radar tracking; Remote sensing by radar; Sensor fusion; Surface topography measurement; Thickness measurement; Subsurface measurements; Data fusion; Air-launched ground penetrating radar; Ground-coupled ground penetrating radar; Signal processing techniques; Roadways; Subsurface layers; Dielectric constant; Layer interface time differences; Layer thickness measurement; Dual GPR system; Tracking; Asphalt air void content ; Surface roughness
Original abstract: The authors are currently working on a task to fuse the data from ground-coupled and air-launched ground penetrating radar (GPR) systems. The goal of the project is to improve the overall accuracy of the system and to extract additional information from the data. It is important that to be able to obtain accurate depth and dielectric constant information for roadways and the constituent subsurface layers. This has not been consistently possible with current systems that rely on the amplitude measurements of air-launched GPR because of variations in surface roughness and material types. Using layer interface time differences from dual ground-coupled antennas can mitigate the effects of surface roughness and variations of the properties of materials by removing the dependence on amplitude measurements; although locating the surface of the roadway is often difficult and inaccurate. By using both systems, the air-launched GPR to locate the surface of the roadway and the ground-coupled system with multiple antennas to locate subsequent layers of the roadway, more accurate information about subsurface roadway depth and dielectric constant can be obtained. This additional information may allow better detection of subsurface anomalies. In addition, by using the error obtained by calculating the thickness of the surface layer with the air-launched system and comparing with the thickness calculated with the fused data, an estimate of the roughness of the roadway surface can be obtained. This paper describes the methods and signal processing techniques being developed for this project as well as provide examples of processed data that demonstrate applications.
 

Kurtz, J. L.; J. W. Fisher, III; G. Skau; J. Armaghani; J. G. Moxley, (1997). Advances in ground-penetrating radar for road subsurface measurements. Radar Sensor Technology II Orlando, FL, USA 24 April 1997
SPIE-Int. Soc. Opt. Eng
Proc. SPIE - Int. Soc. Opt. Eng. (USA), pp.11-21.
Keywords: Matched filters; Pattern classification; Radar applications; Radar signal processing; Remote sensing by radar; Time-domain analysis; Ground-penetrating radar; Road subsurface measurements; Subsurface characterization; Florida Department of Transportation; High resolution measurements; Depth profile scan rates; Time domain data; Thickness; Road surface; Subsurface layers; Signal processing; Voids; Road layer interface; Florida DOT; Detection; Classification; 1 GHz ; 50 to 55 mph
Original abstract: Ground penetrating radar (GPR) is becoming an increasingly useful tool for road subsurface characterization. The Florida Department of Transportation (FDOT) has obtained a 1 GHz ground penetrating radar with the ability to make high resolution measurements. Depth profile scan rates of the new radar are about 50 scan/sec and the radar operates on a test van travelling at speeds up to 50-55 mph. The time domain data collected by the GPR allow the determination of thickness of the road surface and subsurface layers and, with appropriate signal processing, the data can provide information about voids and other anomalies within road layer interfaces. This paper describes the salient features of the Florida DOT ground penetrating radar, measurement results, and applications of GPR for road assessments. It also describes preliminary results of a University of Florida project which is employing advanced signal processing techniques to detect and classify subsurface anomalies in road layers.
 

Kux, H. J. H.; L. R. Penido; J. T. de Mattos, (1999). GIS techniques applied to highway planning: the Sao Paulo metropolitan ring road (RODOANEL), Brazil. IEEE 1999 International Geoscience and Remote Sensing Symposium. IGARSS'99 (Cat. No.99CH36293) Hamburg, Germany 28 June-2 July 1999
Piscataway, NJ, USA IEEE, pp.2699-701 vol.5.
Keywords: Geographic information systems; Town and country planning; GIS techniques; Highway planning; Sao Paulo metropolitan ring road; rodoanel; Brazil; Ground appropriateness; Sao Paulo Metropolitan Region; Synthetic map; Thematic maps; Relief; Slope; Geology; Land use; Land cover; dersa ; Sao Paulo State Department of Highways
Original abstract: This study presents a GIS application to help the analysis of the ground appropriateness to construct the ring road surrounding Sao Paulo Metropolitan Region. A synthetic map was made, through the integration of thematic maps on relief, slope, geology, land use/land cover. The map obtained presents 5 quantitative classes of aptness for the location of this highway, considering two trace alternatives for this highway, presented by DERSA [Sao Paulo State Dept. of Highways].
 

Kyung Soo, C., (1995). Standardization efforts for digital road maps and databases in Korea. *Steps Forward'. Proceedings of the Second World Congress on Intelligent Transport Systems *95 Yokohama Japan 9-11 Nov. 1995
Tokyo, Japan Vehicle, Road & Traffic Intelligence Soc, pp.2459-64 vol.5.
Keywords: Driver information systems; Geographic information systems; Navigation; Road traffic; Standardisation; Traffic control; Standardization; Digital road maps; Korea; ATMS programs; Local governments; Automobile industries; In-vehicle navigation devices; ITS planning and research group ; Korea Transportation Research Society
Original abstract: This paper identifies the available raw data and its supplying institutions in Korea for digital road maps (DRM) and the related databases. Various ATMS programs which are authorized in many local governments in Korea are described, currently the consortium of automobile industries is developing nationwide DRM database for in-vehicle navigation devices. The general description of the databases and their organization are provided in this paper. Finally, this paper explains the approaches and activities of the ITS planning and research group (K.ITS P&RG) in the Korea Transportation Research Society (KTRS) for the integrated solution for these problems.