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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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Abstract

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%.

Document Type:Article
Title:Characterization of Land Cover Types in TerraSAR-X Images by Combined Analysis of Speckle Statistics and Intensity Information
Authors:
AuthorsInstitution or Email of Authors
Esch, ThomasThomas.Esch@dlr.de
Schenk, Andreasandreas.schenk@kit.edu.de
Ullmann, Tobiastobias.ullmann@uni-wuerzburg.de
Thiel, Michaelmichael.theil@uni-wuerzburg.de
Roth, Achimachim.roth@dlr.de
Dech, Stefanstefan.dech@dlr.de
Date:2011
Journal or Publication Title:IEEE Transactions on Geoscience and Remote Sensing
Refereed publication:Yes
In Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:Volume 49
DOI:10.1109/TGRS.2010.2091644
Page Range:pp. 1911-1925
Series Name:IEEE Transactions on Geoscience and Remote Sensing
ISSN:0196-2892
Status:Published
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:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben Geowissenschaftl. Fernerkundungs- und GIS-Verfahren
Location: Oberpfaffenhofen
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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