Integrated modelling of soil moisture by evaluating backscattering models Dubois, Oh and IoT sensor development for field moisture estimation

This research work presents details about various soil moisture models, analysis of radar backscatter models Dubois and Oh using microwave polarization backscattering coefficients, i.e. σ_hh , σ_vv , σ_hv and σ_vh and IoT (internet of things) sensor development. The soil moisture models are investigated based on various factors affecting backscattering coefficients like incidence angle ( θ ), wavelength ( λ ), frequency ( v ), root mean square ( RMS) height, frequency bands, and surface roughness. Dubois model investigates moisture content considering horizontal–horizontal ( σ_hh ) and vertical–vertical ( σ_vv ) polarization. Similarly, the Oh model examines moisture content along with σ_hh , σ_vv , and horizontal–vertical ( σ_hv ) polarization, respectively. These models are investigated for RMS height varying from 0.42≤RMS≤ 3.0 cm , incidence angle ranging from 10^^∘≤θ≤70^^∘ and dielectric constant ( ∈ ) range 1–40 for the Dubois model and 3–30 for the Oh model, respectively. A IoT -based model of a soil moisture sensor is also created and tested for four different soil samples. The sensor produces output in terms of voltage value and moisture (