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Research Article

Estimation of soil moisture based on Sentinel-1 SAR data: Assessment of soil moisture estimation in different vegetation condition

Sentinel-1 SAR 토양수분 산정 연구: 식생에 따른 토양수분 모의평가

Seongkeun Choa
,
Jaehwan Jeongb
,
Seulchan Leec
,
Minha Choid†
조 성근a
,
정 재환b
,
이 슬찬c
,
최 민하d†
aGraduate Student, Department of Water Resources, Sungkyunkwan University, Suwon, Korea
bPh.D Candidate, Department of Water Resources, Sungkyunkwan University, Suwon, Korea
cGraduate Student, Department of Water Resources, Sungkyunkwan University, Suwon, Korea
dProfessor, Department of Water Resources, Sungkyunkwan University, Suwon, Korea
a성균관대학교 수자원학과 석박통합과정
b성균관대학교 수자원학과 박사수료생
c성균관대학교 수자원학과 석박통합과정
d성균관대학교 수자원학과 교수
*mhchoi@skku.edu
28 February 2021. pp. 81-91
PDF XML Citation
Abstract

Synthetic Apreture Radar (SAR) is attracting attentions with its possibility of producing high resolution data that can be used for soil moisture estimation. High resolution soil moisture data enables more specific observation of soil moisture than existing soil moisture products from other satellites. It can also be used for studies of wildfire, landslide, and flood. The SAR based soil moisture estimation should be conducted considering vegetation, which affects backscattering signals from the SAR sensor. In this study, a SAR based soil moisture estimation at regions covered with various vegetation types on the middle area of Korea (Cropland, Grassland, Forest) is conducted. The representative backscattering model, Water Cloud Model (WCM) is used for soil moisture estimation over vegetated areas. Radar Vegetation Index (RVI) and in-situ soil moisture data are used as input factors for the model. Total 6 study areas are selected for 3 vegetation types according to land cover classification with 2 sites per each vegetation type. Soil moisture evaluation result shows that the accuracy of each site stands out in the order of grassland, forest, and cropland. Forested area shows correlation coefficient value higher than 0.5 even with the most dense vegetation, while cropland shows correlation coefficient value lower than 0.3. The proper vegetation and soil moisture conditions for SAR based soil moisture estimation are suggested through the results of the study. Future study, which utilizes additional ancillary vegetation data (vegetation height, vegetation type) is thought to be necessary.

Keywords
Soil moisture
Synthetic aperture radar
Vegetation
Water cloud model
Backscattering coefficient

Synthetic Aperture Radar (SAR)를 활용하여 토양수분을 산출 할 시 기존의 위성기반 자료에 비해 고해상도의 공간 자료를 생산할 수 있다. 고해상도의 광역 토양수분 자료는 기존의 위성 기반 토양수분 대비 보다 세밀한 지표면 토양수분 변동 관측이 가능하게 하므로, 산사태, 산불 및 홍수와 같은 자연재해 연구에 활용성이 뛰어나다. 하지만 SAR 신호인 후방산란계수는 토양수분 뿐만 아니라, 식생에 의한 영향도 포함하기 때문에 정확한 토양수분을 산정하기 위해서는 이러한 영향을 고려하는 단계가 요구된다. 본 연구에서는 한반도 중부의 농지, 산지, 및 초지의 식생조건 하에서 Sentinel-1 위성 SAR 자료를 활용하여 토양수분을 산정하기 위한 연구를 수행하였다. 식생의 영향을 고려하기 위해 대표적인 지표면 레이더 신호 산란 모형인 Water Cloud Model (WCM)을 사용하였으며, 식생 인자로 Radar Vegetation Index (RVI)를 활용하였다. 연구 지역으로는 토지피복도에 따라 농지와 초지, 산지 각각 2개 지역, 총 6개 대상 지역을 선정하였다. WCM의 매개변수 모의를 위해 지상 관측 토양수분 자료를 활용하였다. 관측 토양수분과의 검증 결과 초지, 산지, 농지 순으로 높은 정확도가 나타났으며, 특히 산지에서는 짙은 식생에도 불구하고 상관계수 값이 0.5 이상으로 나타난 반면 농지에서는 0.3 미만의 매우 낮은 값이 관측되었다. 연구 결과를 통해 다양한 식생 피복에서 SAR 기반 토양수분 산정에 적합한 관측 토양수분 조건을 제시 하였다. 향후 식생 높이, 식생 종류 등 과 융합한 연구가 수행된다면 보다 정확한 토양수분을 산정 할 수 있을 것으로 판단된다.

키워드
토양수분
합성개구레이더
식생
Water Cloud 모형
후방산란계수
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Information
  • Publisher :KOREA WATER RESOURECES ASSOCIATION
  • Publisher(Ko) :한국수자원학회
  • Journal Title :Journal of Korea Water Resources Association
  • Journal Title(Ko) :한국수자원학회 논문집
  • Volume : 54
  • No :2
  • Pages :81-91
  • Received Date : 2020-10-30
  • Revised Date : 2020-12-23
  • Accepted Date : 2020-12-23
  • DOI :https://doi.org/10.3741/JKWRA.2021.54.2.81
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