Journal of The Korean Society of Agricultural Engineers (한국농공학회논문집)

The Korean Society of Agricultural Engineers (한국농공학회)
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RNN-LSTM Based Soil Moisture Estimation Using Terra MODIS NDVI and LST

Terra MODIS NDVI 및 LST 자료와 RNN-LSTM을 활용한 토양수분 산정

  • Jang, Wonjin (Department of Civil, Environmental, and Plant Engineering, Konkuk University) ;
  • Lee, Yonggwan (Department of Civil, Environmental, and Plant Engineering, Konkuk University) ;
  • Lee, Jiwan (Department of Civil, Environmental, and Plant Engineering, Konkuk University) ;
  • Kim, Seongjoon (School of Civil, Environmental, and Plant Engineering, Konkuk University)
  • Received : 2019.10.31
  • Accepted : 2019.11.22
  • Published : 2019.11.30
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Abstract

This study is to estimate the spatial soil moisture using Terra MODIS (Moderate Resolution Imaging Spectroradiometer) satellite data and machine learning technique. Using the 3 years (2015~2017) data of MODIS 16 days composite NDVI (Normalized Difference Vegetation Index) and daily Land Surface Temperature (LST), ground measured precipitation and sunshine hour of KMA (Korea Meteorological Administration), the RDA (Rural Development Administration) 10 cm~30 cm average TDR (Time Domain Reflectometry) measured soil moisture at 78 locations was tested. For daily analysis, the missing values of MODIS LST by clouds were interpolated by conditional merging method using KMA surface temperature observation data, and the 16 days NDVI was linearly interpolated to 1 day interval. By applying the RNN-LSTM (Recurrent Neural Network-Long Short Term Memory) artificial neural network model, 70% of the total period was trained and the rest 30% period was verified. The results showed that the coefficient of determination ($R^2$), Root Mean Square Error (RMSE), and Nash-Sutcliffe Efficiency were 0.78, 2.76%, and 0.75 respectively. In average, the clay soil moisture was estimated well comparing with the other soil types of silt, loam, and sand. This is because the clay has the intrinsic physical property for having narrow range of soil moisture variation between field capacity and wilting point.

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References

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