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Spectral behaviour of soil is strongly influenced by the soil texture as well as its nutrient content. Many attempts have so far been made to assess the soil moisture using soil reflectance in different bands of satellite images. In this paper, the investigations showed that the coarse texture soils did not show a profound relationship with the reflectance values that was in part due to its weak water storage capacity. Fine texture soils, on the contrary, showed better results which could be attributed to their higher water storage capacity and the capillary phenomenon. Finally, a linear regression model made of a combination of Land Surface Temperature (LST), Normalized Difference Water Index (NDWI) and Visible and Short-wave infrared Drought Index (VSDI) indices was proposed. The suggested method has improved the accuracy of the soil moisture content estimation up to 1% in general and the medium texture soil in particular. The results were compared with the performance of seven conventional soil moisture estimators method all using the Moderate Resolution Imaging Spectroradiometer (MODIS) data.
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Bidkhani et al. (2018) studied this question.
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