Analysis of decomposition methods for classification of land-cover targets based on RISAT-1 hybrid SAR images

2018 ◽  
Author(s):  
Atasi De ◽  
Dheeraj Kumar ◽  
Parul Patel
Keyword(s):  
Land Cover ◽  
Decomposition Methods ◽  
Sar Images

Texture modelling for land cover classification of fully polarimetric SAR images

2012 ◽  
Vol 3 (2) ◽  
pp. 129-148 ◽  
Author(s):  
Assia Kourgli ◽  
Mounira Ouarzeddine ◽  
Youcef Oukil ◽  
Aichouche Belhadj-Aissa
Keyword(s):  
Land Cover ◽  
Land Cover Classification ◽  
Polarimetric Sar ◽  
Sar Images ◽  
Texture Modelling

scholarly journals SYNTHETIC APERTURE RADAR (SAR) BASED CLASSIFIERS FOR LAND APPLICATIONS IN GERMANY

2016 ◽  
Vol XLI-B1 ◽  
pp. 1187-1193 ◽  
Author(s):  
G. Suresh ◽  
R. Gehrke ◽  
T. Wiatr ◽  
M. Hovenbitzer
Keyword(s):  
Land Cover ◽  
Synthetic Aperture Radar ◽  
Land Cover Classification ◽  
Classification Systems ◽  
Synthetic Aperture ◽  
Optical Data ◽  
Sar Images ◽  
Sentinel 2 ◽  
Aperture Radar

Land cover information is essential for urban planning and for land cover change monitoring. This paper presents an overview of the work conducted at the Federal Agency for Cartography and Geodesy (BKG) with respect to Synthetic Aperture Radar (SAR) based land cover classification. Two land cover classification approaches using SAR images are reported in this paper. The first method involves a rule-based classification using only SAR backscatter intensity while the other method involves supervised classification of a polarimetric composite of the same SAR image. The LBM-DE has been used for training and validation of the SAR classification results. Images acquired from the Sentinel-1a satellite are used for classification and the results have been reported and discussed. The availability of Sentinel-1a images that are weather and daylight independent allows for the creation of a land cover classification system that can be updated and validated periodically, and hence, be used to assist other land cover classification systems that use optical data. With the availability of Sentinel-2 data, land cover classification combining Sentinel-1a and Sentinel-2 images present a path for the future.

The influence of filtration and decomposition window size on the threshold value and accuracy of land-cover classification of polarimetric SAR images

2015 ◽  
Vol 37 (1) ◽  
pp. 212-228 ◽  
Author(s):  
Edyta Woźniak ◽  
Wlodek Kofman ◽  
Paweł Wajer ◽  
Stanisław Lewiński ◽  
Artur Nowakowski
Keyword(s):  
Land Cover ◽  
Window Size ◽  
Threshold Value ◽  
Land Cover Classification ◽  
Polarimetric Sar ◽  
Sar Images
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