A statistical model for estimation of soil moisture in paddy field using microwave satellite data

Estimation of soil moisture using Synthetic Aperture Radar (SAR) backscatter values, over agricultural area, is still difficult. SAR backscatter is sensitive to the surface properties like roughness, crop cover, and soil type, along with its strong sensitivity to soil moisture. Hence, to develop a methodology for agricultural area soil moisture estimation using SAR, it is necessary to incorporate the effects of crop cover and soil texture in the soil moisture retrieval model. A field experiment was conducted by the authors and used along with Sentinel 1A SAR data to estimate the soil moisture in the paddy agricultural fields. Generally, the water used for irrigation in the study region was obtained from ground water. As in the hot climate conditions ground water level would be reduced, and the water for irrigation must be supplied optimally. Hence, available soil moisture in the field was estimated from SAR data on the day of satellite passing the crop fields and utilized for deciding the amount of water to be supplied. The soil moisture values of soil samples that are collected from the agricultural field are calculated with the laboratory experiments. A soil moisture retrieval model is derived and proposed in this paper after a comparative analysis of experimental soil moisture values and satellite values. The feasibility of above model for paddy agricultural fields is validated using the field measurements. © 2020, Electromagnetics Academy. All rights reserved.