Economic and Environmental Geology (자원환경지질)

The Korean Society of Economic and Environmental Geology (대한자원환경지질학회)
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Development of Landslide Detection Algorithm Using Fully Polarimetric ALOS-2 SAR Data

Fully-Polarimetric ALOS-2 자료를 이용한 산사태 탐지 알고리즘 개발

  • Kim, Minhwa (Department of Energy and Mineral Resources Engineering, Sejong University) ;
  • Cho, KeunHoo (Department of Geoinformation Engineering, Sejong University) ;
  • Park, Sang-Eun (Department of Energy and Mineral Resources 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)
  • 김민화 (세종대학교 에너지자원공학과) ;
  • 조근후 (세종대학교 지구정보공학과) ;
  • 박상은 (세종대학교 에너지자원공학과) ;
  • 조재형 (한화시스템 레이더 R&D 센터) ;
  • 문효이 (한화시스템 레이더 R&D 센터) ;
  • 한승훈 (한화시스템 레이더 R&D 센터)
  • Received : 2019.07.29
  • Accepted : 2019.08.26
  • Published : 2019.08.28
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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%.

SAR (Synthetic Aperture Radar) 원격탐사 관측 자료는 폭우나 태풍으로 인해 넓은 지역에 걸쳐 발생할 수 있는 산사태 피해 지역을 신속하게 탐지하는데 매우 유용한 도구이다. 본 연구의 목적은 산사태 발생 이후에 관측이 수행된 다중 편광 SAR 자료를 이용하여 산사태 지역을 자동으로 분류하는 효과적인 알고리즘을 개발하는 것이다. 실험적인 분석을 바탕으로 SAR 관측 자료로부터 산사태를 탐지하기 위해서는 SAR 영상의 스펙클 현상을 줄여주는 스펙클 필터와 경사진 지형에서의 기하왜곡을 보정하는 정사보정이 필수적임을 확인하였고, IDAN 필터를 적용하여 스펙클을 줄이고 다중 편광 파라미터를 추정한 후에 정사보정을 수행하는 것이 산사태 탐지를 위해 적합한 처리 과정임을 제시하였다. 또한 다양한 다중 편광 파라미터에 대한 탐지 성능 분석을 통해 entropy 파라미터가 산사태 탐지에 좋은 성능을 보임을 파악하였다. 이러한 분석을 토대로 다중 편광 파라미터에 대한 자동적인 문턱값 설정과 DEM을 보조적으로 사용하는 산사태 탐지 알고리즘을 제안하였다. 탐지 알고리즘은 2011년 9월 태풍 탈라스에 의해 발생한 산사태에 대해 관측을 수행한 ALOS-2위성의 PALSAR-2 자료를 이용하여 실험적인 평가를 수행하였고, 약 82%의 탐지율과 3%의 오경보율로 산사태를 탐지 할 수 있음을 확인하였다.

Keywords

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