Title :
Using texture from high resolution Terrasar-X images for tropical forest mapping
Author :
Benelcadi, H. ; Frison, P.-L. ; Lardeux, C. ; Mercier, G. ; Rudant, J.-P.
Abstract :
This study aims to evaluate the contribution of textural analysis from high spatial resolution TerraSAR-X images for tropical forests mapping. This study evaluates the potential of the High resolution Spotlight TerraSAR-X image (HS), with a spatial resolution of 0.6 meter in Range and 1.1 meter in Azimuth, for the classification of tropical forest plantation of native species. Indeed, the contribution of the analysis of textural information for classification has been emphasized through the analysis of Haralick textural parameters, a second order statistic parameters computed in a certain direction with a distance (d) and window size (w). The retained algorithm of classification is SVM (Support Vector Machine as it allows taking into account numerous parameters, which can be heterogeneous with respect to their physical dimension. To resolve the issue of class heterogeneity in the context of high resolution image, a post classification has been applied by the mean of a majority filter. In this case, the majority filter was weighted by integrating a shape of different plots containing the label of the tree planted species.
Keywords :
image texture; support vector machines; synthetic aperture radar; vegetation; Haralick textural parameter analysis; SVM classification algorithm; class heterogeneity; distance direction; high resolution Spotlight TerraSAR-X image potential; high resolution image context; high spatial TerraSAR-X image resolution textural analysis; majority filter mean; native species tropical forest plantation classification; physical dimension; plot shape integration; post classification; second order statistic parameter computation; support vector machine; textural information analysis; tree planted species label; tropical forest mapping; window size; Biomass; Context; Spatial resolution; Support vector machines; Synthetic aperture radar; Vegetation mapping; Haralick; Post classification; SAR; SVM; TerraSAR-X; Texture; Tropical forest;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International
Conference_Location :
Quebec City, QC
DOI :
10.1109/IGARSS.2014.6946937