Abstract
In the last few years’ digital agriculture has bloomed at new height. In the digital agriculture formers receive information of different parameters related to their crops in their mobile, and take steps accordingly. The knowledge of the soil moisture (SM) is one of the key parameter related to the agriculture field, and therefore SM is a key parameter for digital agriculture. In the agriculture field, SM varies very frequently, so for digital agriculture, near real time SM needs to be closely observed. For this purpose, microwave sensors which have very high temporal resolution are needed. Recently launched Scatsat-1 Scatterometer, by ISRO, may be an apt data source because of its daily acquisition. However it has some limitations due to its spatial resolution. Therefore, in this paper an attempt has been made to develop such a methodology by which one can retrieve the SM with coarse resolution data. To overcome coarse resolution issue, a methodology is proposed, which considers the vegetation fraction cover (FVC) in every resolution cell. With the help of FVC, backscattering signal of soil (σ soil ) is segregated from the total backscattered signal and, this σ soil is inverted to SM using Dubois model. Retrieved SM is compared with ground measured SM, and obtained RMSE is 0.105 m3/m3. Retrieved SM is also compared with available SMAP SM product and observed that retrieved SM is very close to SMAP SM.
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