Review Article

Remote Sensing of Soil Moisture

Table 1

Studies on downscaling soil moisture using various remote sensing and modeling techniques [41].

AuthorMethodologyTime and regionResult

Merlin et al., [49]Based on the relationship between soil evaporative efficiency and soil moistureNAFE 2006 (Oct-Nov), Yanco, Southeastern AustraliaMean correlation slope between simulated and measured data is 0.94, the most accuracy with an error of 0.012
Piles et al., [50]Build model between LST, NDVI, and soil moistureJan-Feb 2010, Murrumbidgee catchment, Yanco, Southeastern Australia is between 0.14~0.21 and RMSE 0.9~0.17
Merlin et al., [51]Downscaling algorithm is derived from MODIS and physical-based soil evaporative efficiency modelNAFE 2006 (Oct-Nov), Murrumbidgee catchment, Yanco, Southeastern AustraliaOverall RMSE is between 1.4%~1.8% v/v
Merlin et al., [51]Based on two soil moisture indices EF and AEFJune and August 1990 (Monsoon' 90 experiment), USDA-ARS WGEW in southeastern ArizonaTotal accuracy is 3% vol. for EF and 2% vol. for AEF, and correlation coefficient is 0.66~0.79 for EF and 0.71~0.81 for AEF
Merlin et al., [52]Sequential modelNAFE 2006 (Oct-Nov), Yanco, Southeastern AustraliaRMSE is −0.062 vol./vol. and the bias is 0.045 vol./vol.