IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477)
DOI: 10.1109/igarss.2003.1293719
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Classification of urban SAR imagery using object oriented techniques

Abstract: This paper describes the development of techniques for the production of urban mapping data from interferometric polarimetric synthetic aperture radar (SAR) data. The information contained in the radar data originates from four types of data properties:• Radiometric, i.e. the channel intensities • Polarimetric, e.g. decomposition properties entropy and alpha •Interferometric, e.g. coherence and interferometric height • Geometric, e.g. shape and area A multi-scale analysis, using the infrastructure provided by … Show more

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Cited by 25 publications
(19 citation statements)
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“…Numerous studies concerning automated land cover/land use classifications of specific datasets in urban areas, or at least in partly built-up areas, can be found in the literature (see, for example, [1][2][3][4][5] for aerial image data, [6][7][8][9] for laser scanner data, [10][11][12][13][14][15] for high-resolution optical satellite images, and [16][17][18][19][20] for high-resolution SAR images). Some details of selected studies are presented in Table 1 (we selected studies that used only remotely sensed data for classification, presented the overall accuracy of the classification, and had classes most similar to our study).…”
Section: Comparison Of New Remotely Sensed Datasets For Land Cover CLmentioning
confidence: 99%
“…Numerous studies concerning automated land cover/land use classifications of specific datasets in urban areas, or at least in partly built-up areas, can be found in the literature (see, for example, [1][2][3][4][5] for aerial image data, [6][7][8][9] for laser scanner data, [10][11][12][13][14][15] for high-resolution optical satellite images, and [16][17][18][19][20] for high-resolution SAR images). Some details of selected studies are presented in Table 1 (we selected studies that used only remotely sensed data for classification, presented the overall accuracy of the classification, and had classes most similar to our study).…”
Section: Comparison Of New Remotely Sensed Datasets For Land Cover CLmentioning
confidence: 99%
“…A generic object-based multi-scale idea is introduced to the land classification (Corr,D.G., 2003).After the polarimetric analysis for different lands, surface scattering fraction as feature parameters to distinguish surface, forest, building and cultivated lands via multi-threshold segmentation at the first scale analysis layer. As it is sensitive to texture features exhibited in different types orchards and crops, the two features of gray level cooccurrence matrix (GLCM) homogeneity and dissimilarity are selected to distinguish orchards and crops via region-based segmentation at the following scale analysis layer.…”
Section: Land Classification Resultsmentioning
confidence: 99%
“…For purpose of accurate classification for PolSAR image, an Oriented-Object classification scheme based on hierarchical segmentation (Corr et al 2003b) is employed in test area 1.…”
Section: Oriented-object Classification Based On Hierarchical Segmentmentioning
confidence: 99%