ZHANG You-jing, WANG Jun-zhan, BAO Yan-song. Soil moisture retrieval from multi-resource remotely sensed images over a wheat area[J]. Advances in Water Science, 2010, 21(2): 222-228.
Citation: ZHANG You-jing, WANG Jun-zhan, BAO Yan-song. Soil moisture retrieval from multi-resource remotely sensed images over a wheat area[J]. Advances in Water Science, 2010, 21(2): 222-228.

Soil moisture retrieval from multi-resource remotely sensed images over a wheat area

  • The aim of this study is to use the multi-resource remotely sensed images over land surfaces in a semi-arid region in northern China to infer the soil moisture content (SMC) in the presence of wheat.The multi-images include Advanced Synthetic Aperture Radar (ASAR),Landsat Thematic Mapper (TM) and Moderate-resolution Imaging Spectroradiometer (MODIS).The influence of vegetation on the satellite signal can be described by a water-cloud model.The vegetation water content (Mv),an important parameter in the water-cloud model,was synchronously measured with the corresponding satellite passes over the wheat area.The evaluation of the relationship between Mvand four satellite-derived vegetation indices (VIs) shows that the NDWI (normalized difference water index) from TM has the closest relationship with Mvas revealed by the correlation coefficient of 0.87.Based on the established Mv-NDWI relationship,combining the water-cloud model with the soil moisture retrieval over bare soil conditions,a semi-empirical model is developed for estimating SMC over a wheat area.A sensitivity analysis is also performed on the model parameters.In comparison with the insitu soil moisture observation,a satisfactory result is obtained in the soil moisture retrieval using the semi-empirical model as revealed by the RMSE (root mean squared error) of 3.83% and the correlation coefficient of 0.9.The spatial distribution of soil moisture deficits in the study area is also produced.
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