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http://dx.doi.org/10.7780/kjrs.2018.34.4.2

Investigation of Polarimetric SAR Remote Sensing for Landslide Detection Using PALSAR-2 Quad-pol Data  

Cho, KeunHoo (Department of Geoinformation Engineering, Sejong University)
Park, Sang-Eun (Department of Geoinformation Engineering, Sejong University)
Cho, Jae-Hyoung (Radar R&D Center, Hanwha System)
Moon, Hyoi (Radar R&D Center, Hanwha System)
Han, Seung-hoon (Radar R&D Center, Hanwha System)
Publication Information
Korean Journal of Remote Sensing / v.34, no.4, 2018 , pp. 591-600 More about this Journal
Abstract
Recent SAR systems provide fully polarimetric SAR data, which is known to be useful in a variety of applications such as disaster monitoring, target recognition, and land cover classification. The objective of this study is to evaluate the performance of polarization SAR data for landslide detection. The detectability of different SAR parameters was investigated based on the supervised classification approach. The classifier used in this study is the Adaptive Boosting algorithms. A fully polarimetric L-band PALSAR-2 data was used to examine landslides caused by the 2016 Kumamoto earthquake in Kyushu, Japan. Experimental results show that fully polarimetric features from the target decomposition technique can provide improved detectability of landslide site with significant reduction of false alarms as compared with the single polarimetric observables.
Keywords
Synthetic Aperture Radar; Landslide detection; Polarimetric SAR; PALSAR-2;
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