Characterization of Land Cover Types in TerraSAR-X Images by Combined Analysis of Speckle Statistics and Intensity Information
Esch, Thomas and Schenk, Andreas and Ullmann, Tobias and Thiel, Michael and Roth, Achim and Dech, Stefan (2011) Characterization of Land Cover Types in TerraSAR-X Images by Combined Analysis of Speckle Statistics and Intensity Information. IEEE Transactions on Geoscience and Remote Sensing, Volume 49 ( Issue:6), pp. 1911-1925. DOI: 10.1109/TGRS.2010.2091644. ISSN 0196-2892.
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The appearance of objects and surfaces in synthetic aperture radar (SAR) images significantly differs from the human perception of the environment. In addition, the quality of SAR data is degraded by speckle noise, superposing the true radiometric and textural information of the radar image. Hence, the interpretation of SAR images is considered to be more challenging compared to the analysis of optical data. However, in this paper, we demonstrate how information on the local development of speckle can be used for the differentiation of basic land cover (LC) types in a single-polarized SAR image. For that purpose, we specify the speckle characteristics of the following LC types: 1) water; 2) open land (farmland, grassland, bare soil); 3) woodland; and 4) urban area by means of an unsupervised analysis of scatter plots and standardized histograms of the local coefficient of variation. Next, we use this information for the implementation of a straightforward preclassification of single-polarized TerraSAR-X stripmap images by combining information on the local speckle behavior and local backscatter intensity. The output is either provided as a discrete classification or as a color composite image whose bands can be interpreted in terms of a fuzzy classification. The results of this paper show that unsupervised speckle analysis in high-resolution SAR images supplies valuable information for a differentiation of the water, open land, woodland, and urban area LC types. While the color composite image supports the visual interpretation of SAR data, the outcome of the fully automated discrete LC classification procedure represents a valuable preclassification image, showing overall accuracies of 77%–86%.
|Title:||Characterization of Land Cover Types in TerraSAR-X Images by Combined Analysis of Speckle Statistics and Intensity Information|
|Journal or Publication Title:||IEEE Transactions on Geoscience and Remote Sensing|
|In Open Access:||No|
|In ISI Web of Science:||Yes|
|Page Range:||pp. 1911-1925|
|Series Name:||IEEE Transactions on Geoscience and Remote Sensing|
|Keywords:||Classification, land cover (LC), Synthetic Aperture Radar (SAR), speckle, statistical distribution, TerraSAR-X (TSX), texture.|
|HGF - Research field:||Aeronautics, Space and Transport|
|HGF - Program:||Raumfahrt|
|HGF - Program Themes:||R EO - Erdbeobachtung|
|DLR - Research area:||Raumfahrt|
|DLR - Program:||R EO - Erdbeobachtung|
|DLR - Research theme (Project):||R - Vorhaben Geowissenschaftl. Fernerkundungs- und GIS-Verfahren|
|Institutes and Institutions:||German Remote Sensing Data Center > Land Surface|
|Deposited By:||Dr.rer.nat. Thomas Esch|
|Deposited On:||24 Jan 2012 13:21|
|Last Modified:||15 Apr 2013 14:10|
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