Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/64955
Title: Comparison of pixel-based, object-based and sequential masking classification procedures for land use and land cover mapping using multiple sensor SAR in Sweden
Authors: Sarker, MLR
Ban, Y
Nichol, JE 
Keywords: Multiple sensors SAR
Pixel-based
Object-based
Sequential masking and ANN
Issue Date: 2008
Publisher: Asian Remote Sensing Research Information Network
Source: Asian journal of geoinformatics, 2008, v. 8, no. 1, p. 25-30 How to cite?
Journal: Asian journal of geoinformatics 
Abstract: Multiple sensor applications have become increasingly common in recent years and offer new opportunities to the remote sensing community to extract better information about the earth surface. However, the processing of multiple sensor SAR for land use and land cover mapping is not straightforward and still needs more investigation in order to become operational. This study investigates the efficiency of three different types of classification procedures, namely pixel-based, object-based and sequential masking to extract land use and land cover information from multiple sensor SAR images using the same training and validation areas. Four sensors (RADARSAT finebeam, RADARSAT standard-beam, ERS-2, and JERS-1) in different combinations were investigated in two study areas, to compare their effectiveness for accurate land cover mapping.
URI: http://hdl.handle.net/10397/64955
ISSN: 1513-6728
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