Habib Mazaheri, from the Department of Geomatics Engineering at the University of Calgary, discusses soil moisture estimation using polarimetric Radarsat-2 data. Traditionally, soil moisture estimation work has been done through time-intensive field work, but remote sensing is fast, cost-effective and can cover a wide area. Synthetic aperature radar (SAR) for soil moisture shows significant potential for this purpose.
With SAR, the differences in the electromagnetic dielectric properties of soil and water are used to determine different levels of moisture. To establish the relationship between moisture levels in typical soil and SAR observations, physical tests, or an empirical or semi-empirical mathematical model is used.
The study area to test SAR for soil moisture information was done in Carman, Manitoba in 2008. It was a single look complex done in fine quad-polarization mode. Mazaheri concludes that fractal analysis of the IEM output may help in establishing a robust calibration model for soil moisture. Nonlinear calibration models may work best. The effect of speckle filtering and incidence angle needs more research.
This presentation was a part of Alberta Terrestrial Imaging Centre's LiDAR/SAR Wetland and Water Monitoring Workshop, from June of 2014.
