DocumentCode :
2228223
Title :
Contribution of TerraSAR-X radar images texture for forest monitoring
Author :
Benelcadi, H. ; Frison, P. -L ; Lardeux, C. ; Capel, A. -C ; Routier, J. -B ; Rudant, J. -P
Author_Institution :
Lab. ESYCOM, Univ. of Paris-Est Marne-la-Vallee, Champs sur Marne, France
fYear :
2012
fDate :
22-27 July 2012
Firstpage :
6427
Lastpage :
6430
Abstract :
This study aims to evaluate the texture analysis of high spatial resolution images for mapping tropical forests. More precisely, it evaluates the potential of TerraSAR-X image, with spatial resolution of 0.5 meter for the classification of tropical forests located in southern Cambodia. In particular, the focus is put on the contribution of the analysis of textural information for classification. This latter is apprehended through the analysis of Haralick textural parameters. The retained algorithm of classification is the Support Vector Machine, as it allows taking into account numerous parameters, which can be heterogeneous with respect to their physical dimension. First results show that the addition of Haralick parameters to intensity channel may improve significantly the accuracy of the classification results. However, their performance for classification discrimination strongly depends on the size of the neighborhood from which they are estimated. Preliminary analysis of variograms allows optimizing the choice of the neighborhood size. Best results are obtained with a 25×25 sliding window size, with a classification accuracy improvement higher than 50% is observed.
Keywords :
forestry; geophysical image processing; image classification; image resolution; image texture; radar imaging; remote sensing by radar; support vector machines; synthetic aperture radar; vegetation mapping; Haralick textural parameters; TerraSAR-X radar image texture; classification discrimination analysis; forest monitoring; high spatial resolution images; southern Cambodia; support vector machine; textural information analysis; tropical forest classification; tropical forest mapping; variogram analysis; Accuracy; Biomass; Carbon; Spatial resolution; Support vector machines; Synthetic aperture radar; Vegetation mapping; Haralick; REDD+; SAR; SVM; TerraSAR-X; Texture; Tropical forest; Variogram;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location :
Munich
ISSN :
2153-6996
Print_ISBN :
978-1-4673-1160-1
Electronic_ISBN :
2153-6996
Type :
conf
DOI :
10.1109/IGARSS.2012.6352130
Filename :
6352130
Link To Document :
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