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J. Korean Soc. Hazard Mitig. > Volume 19(7); 2019 > Article
풍수해방재
Journal of the Korean Society of Hazard Mitigation 2019;19(7):471-483.
DOI: https://doi.org/10.9798/KOSHAM.2019.19.7.471    Published online December 31, 2019.
인공위성영상과 지형자료를 동시에 활용한 침수지역 판별
김수현1, 이상구2, 김태웅3, 김동균4
1정회원, 홍익대학교 토목공학과 박사과정
2홍익대학교 토목공학과 석사과정
3정회원, 한양대학교 건설환경공학과 교수
4정회원, 홍익대학교 토목공학과 부교수
Estimation of Flooded Area Using Satellite Imagery and DSM Terrain Data
Soohyun Kim1, Sangku Lee2, Tae-Woong Kim3, Dongkyun Kim4
1Member, Doctor's Course, Department of Civil Engineering, Hongik University
2Master's Course, Department of Civil Engineering, Hongik University
3Member, Professor, Department of Civil and Environmental Engineering, Hanyang University
4Member, Associate Professor, Department of Civil Engineering, Hongik University
Corresponding author:  Dongkyun Kim, Tel: +82-70-8221-0058, Fax: +82-2-322-1244, 
Email: kim.dongkyun@hongik.ac.kr
Received: 27 September 2019   • Revised: 1 October 2019   • Accepted: 21 October 2019
Abstract
This study used satellite image and topographical data simultaneously to identify and verify the areas flooded in Yeongdeok-gun, Gyeongsangbuk-do, Korea, as a result of Typhoon Kong-Rey. The satellite image data were obtained from ESA Sentinel-1 Synthetic Aperture Radar (SAR) imagery and PlanetLab's PlanetScope optical imagery. The topographical data used to identify the depth and extent of the flooding was Digital Surface Model (DSM) data obtained through drone surveying, with resolutions of 0.02 m, 0.1 m, 0.5 m, 1 m, 3 m, 5 m, and 10 m. The area with a large color difference before and after the flooding was designated the primary flooded area. The area that was identified as lower than the primary flooded area, according to the topography data, was determined as the final flooded area. The accuracy was calculated by the intersection versus union method. It increased as the resolution of the topographical data increased and ranged between 62 and 97 percent, depending on the analysis area. In the case of flat areas of land, SAR images showed high accuracy and in the case of areas with densely-placed buildings, optical satellite images showed high accuracy.
Key Words: Satellite, Inundation Trace Map, Sentinel-1, PlanetScope, DSM
요지
본 연구는 위성영상자료와 지형자료를 동시에 활용하여 2018년 10월초 발생한 태풍 콩레이에 의한 경북 영덕군의 침수피해지역을 판별 및 검증하였다. 위성영상자료는 ESA의 Sentinel-1 합성개구레이더(SAR)영상과 PlanetLab의 PlanetScope 광학영상을 활용하였고, 검증을 위한 지상관측자료는 CCTV 자료를 활용하였다. 침수심과 침수규모를 확인하기 위해 사용한 지형자료는 드론촬영을 통해 얻은 0.02 m, 0.1 m, 0.5 m, 1 m, 3 m, 5 m, 10 m의 DSM 자료이다. 인공위성영상에서 침수전후의 색상차가 큰 지역을 우선적 침수지역으로 정한후, DSM 자료와 비교하여 이보다 낮은 지역을 최종 침수지역으로 판별하였다. 교집합 대 합집합 방법으로 산출한 정확도는 지형자료의 해상도의 증가에 따라 함께 증가하였으며 분석 지역에 따라 62 퍼센트에서 97 퍼센트 사이의 값을 보였다. 평지의 경우 SAR 영상을 활용시 정확도가 높았으며, 건물이 밀집되어있는 경우 광학위성영상을 활용시 정확도가 높았다.
핵심용어: 인공위성, 침수흔적도, Sentinel-1, PlanetScope, DSM


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