한국농공학회논문집 (Journal of The Korean Society of Agricultural Engineers)

  • 제62권6호
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  • Pages.11-20
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  • 2020
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  • 1738-3692(pISSN)
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  • 2093-7709(eISSN)
한국농공학회 (The Korean Society of Agricultural Engineers)
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Sentinel-1A/B SAR와 토양수분자료동화기법을 이용한 고해상도 토양수분 산정

Estimation of High-Resolution Soil Moisture Using Sentinel-1A/B SAR and Soil Moisture Data Assimilation Scheme

  • Kim, Sangwoo (Department of Agricultural Civil Engineering, Kyungpook National University) ;
  • Lee, Taehwa (Department of Agricultural Civil Engineering, Kyungpook National University) ;
  • Chun, Beomseok (Department of Agricultural Civil Engineering, Kyungpook National University) ;
  • Jung, Younghun (Department of Advanced Science and Technology Convergence, Kyungpook National University) ;
  • Jang, Won Seok (Division of Public Infrastructure Assessment, Environmental Assessment Group, Korea Environment Institute) ;
  • Sur, Chanyang (Department of Civil and Environmental Engineering, Sejong University) ;
  • Shin, Yongchul (Department of Agricultural Civil Engineering, Kyungpook National University)
  • 투고 : 2020.07.13
  • 심사 : 2020.10.20
  • 발행 : 2020.11.30
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초록

We estimated the spatio-temporally distributed soil moisture using Sentinel-1A/B SAR (Synthetic Aperture Radar) sensor images and soil moisture data assimilation technique in South Korea. Soil moisture data assimilation technique can extract the hydraulic parameters of soils using observed soil moisture and GA (Genetic Algorithm). The SWAP (Soil Water Atmosphere Plant) model associated with a soil moisture assimilation technique simulates the soil moisture using the soil hydraulic parameters and meteorological data as input data. The soil moisture based on Sentinel-1A/B was validated and evaluated using the pearson correlation and RMSE (Root Mean Square Error) analysis between estimated soil moisture and TDR soil moisture. The soil moisture data assimilation technique derived the soil hydraulic parameters using Sentinel-1A/B based soil moisture images, ASOS (Automated Synoptic Observing System) weather data and TRMM (Tropical Rainfall Measuring Mission)/GPM (Global Precipitation Measurement) rainfall data. The derived soil hydrological parameters as the input data to SWAP were used to simulate the daily soil moisture values at the spatial domain from 2001 to 2018 using the TRMM/GPM satellite rainfall data. Overall, the simulated soil moisture estimates matched well with the TDR measurements and Sentinel-1A/B based soil moisture under various land surface conditions (bare soil, crop, forest, and urban).

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참고문헌

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