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Fully-Polarimetric ALOS-2 자료를 이용한 산사태 탐지 알고리즘 개발
Development of Landslide Detection Algorithm Using Fully Polarimetric ALOS-2 SAR Data
Econ. Environ. Geol. 2019 Aug;52(4):313-22
Published online August 31, 2019;  https://doi.org/10.9719/EEG.2019.52.4.313
Copyright © 2019 the Korean society of economic and environmental gelology.

Minhwa Kim1, KeunHoo Cho2, Sang-Eun Park1,2*, Jae-Hyoung Cho3, Hyoi Moon3 and Seung-hoon Han3
김민화1 ·조근후2 ·박상은1,2* ·조재형3 ·문효이3 ·한승훈3

1Department of Energy and Mineral Resources Engineering, Sejong University
2Department of Geoinformation Engineering, Sejong University
3Radar R&D Center, Hanwha System
1세종대학교 에너지자원공학과, 2세종대학교 지구정보공학과, 3한화시스템 레이더 R&D 센터
Received July 29, 2019; Revised August 19, 2019; Accepted August 26, 2019.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
 Abstract
SAR (Synthetic Aperture Radar) remote sensing data is a very useful tool for near-real-time identification of landslide affected areas that can occur over a large area due to heavy rains or typhoons. This study aims to develop an effective algorithm for automatically delineating landslide areas from the polarimetric SAR data acquired after the landslide event. To detect landslides from SAR observations, reduction of the speckle effects in the estimation of polarimetric SAR parameters and the orthorectification of geometric distortions on sloping terrain are essential processing steps. Based on the experimental analysis, it was found that the IDAN filter can provide a better estimation of the polarimetric parameters. In addition, it was appropriate to apply orthorectification process after estimating polarimetric parameters in the slant range domain. Furthermore, it was found that the polarimetric entropy is the most appropriate parameters among various polarimetric parameters. Based on those analyses, we proposed an automatic landslide detection algorithm using the histogram thresholding of the polarimetric parameters with the aid of terrain slope information. The landslide detection algorithm was applied to the ALOS-2 PALSAR-2 data which observed landslide areas in Japan triggered by Typhoon in September 2011. Experimental results showed that the landslide areas were successfully identified by using the proposed algorithm with a detection rate of about 82% and a false alarm rate of about 3%.
Keywords : landslide, polarimetric SAR, microwave scattering, speckle filtering, orthorectification

 

August 2019, 52 (4)