Generation of continuous surface soil moisture dataset using combined optical and thermal infrared images

作者: Pei Leng , Xiaoning Song , Si-Bo Duan , Zhao-Liang Li

DOI: 10.1002/HYP.11113

关键词:

摘要: Surface soil moisture (SSM) is a critical variable for understanding water and energy flux between the atmosphere Earth's surface. An easy to apply algorithm deriving SSM time series that primarily uses temporal parameters derived from simulated in situ datasets has recently been reported. This must be assessed different biophysical atmospheric conditions by using actual geostationary satellite images. In present study, two currently available coarse-scale (microwave reanalysis product) aggregated measurements were implemented calibrate time-invariable coefficients of retrieval which conventional observations are rare. These subsequently used obtain directly Meteosat Second Generation (MSG) images over study area well-organized network named REMEDHUS Spain. The results show high degree consistency estimated values when three dataset-calibrated retrieve SSM, with determination (R2) varying 0.304 0.534 root mean square errors (RMSE) ranging 0.020 m3/m3 0.029 m3/m3. Further evaluation land use types acceptable debiased RMSE 0.021 m3/m3 0.048 m3/m3 comparing MSG pixel-scale measurements. indicate investigated method practical publicly accessed datasets, beneficial generating continuous dataset at pixel scale.

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