Mohammed Magfurar Rahman

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Surface roughness is a crucial input for radar backscatter models. Roughness measurements of root meansquared height (hrms) of the same surface can vary depending on the measuring instrument and how the data are processed. This letter addresses the error in hrms associated with instrument bias and instrument deployment issues such as number and length of(More)
[1] Four approaches for deriving estimates of near-surface soil moisture from radar imagery in a semiarid, sparsely vegetated rangeland were evaluated against in situ measurements of soil moisture. The approaches were based on empirical, physical, semiempirical, and image difference techniques. The empirical approach involved simple linear regression of(More)
The Integral Equation Method (IEM) model and a newly defined delta index were used to estimate near surface soil moisture from C-band radar satellite imagery in a semi-arid rangeland in southern Arizona, USA. Model results were validated against soil moisture measurements made in the field at the time of satellite overpass. The IEM model performed poorly in(More)
The Integral Equation Model (IEM) is the most widely-used, physically based radar backscatter model for sparsely vegetated landscapes. In general, IEM quantifies the magnitude of backscattering as a function of moisture content and surface roughness, which are unknown, and the known radar configurations. Estimating surface roughness or soil moisture by(More)
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