An improved approach for soil moisture estimation by employing illumination-corrected data in a modified Ts-VI method
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Abstract
There are a great number of publications that apply different methods to estimate soil moisture from optical satellite imagery. However, none of the proposed methods have considered correcting solar illumination error that is caused by variation in topography before estimating soil moisture.
In this research, an integrated approach is developed to improve the estimation of soil moisture. The integration is represented by removing the solar-illumination error from the data. Several modifications were made in the Ts-VI space based on the Universal Triangle Relationship. The data used in the research are obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite.
The research results show that the surface-illumination error, which is caused by variation in topography, misleads the estimation of soil moisture index. Based on statistical and visual analysis, the results are improved with removing error. The method is further enhanced with the application of enhanced vegetation index (EVI) to the Ts-VI relationship.