Evaluation of the OPTRAM Model to Retrieve Soil Moisture in the Sanjiang Plain of Northeast China
Mingxing Chen, Yuhu Zhang, Yunjun Yao, Jing Lu, Xiao Pu, Tao Hu, Peng Wang
Abstract
Abstract Soil moisture is a key factor affecting crop growth and crop yield. Information on soil moisture is critical for crop growth monitoring and yield estimation. This study evaluated the OPtical TRApezoid Model (OPTRAM) on soil moisture estimates in the Sanjiang Plain, China, using Moderate Resolution Imaging Spectroradiometer (MODIS) data and in situ soil moisture data acquired from May to September in 2016 and 2017. This model was empirically calculated by parameterizing the relationship between the normalized difference vegetation index (NDVI) and shortwave infrared transformed reflectance (STR). In addition, the precipitation data were collected and used for verification of the results. According to the scatterplots of STR and NDVI, OPTRAM can estimate soil moisture from July to September, while it's inapplicable in May and June. Evaluation results indicated that OPTRAM‐based soil moisture estimates provide overall RMSE from 0.05 to 0.13 cm 3 /cm 3 , bias from −0.11 to 0.06 cm 3 /cm 3 , and R 2 from 0.10 to 0.50, respectively, for all investigated sites. The performance of OPTRAM compared with the precipitation data showed good agreement. In conclusion, OPTRAM could be used to estimate soil moisture with reasonable accuracy in most areas from July to September in Sanjiang Plain.