Estimation of Soil Moisture in the Southern United States in 2003 Using Multi-Satellite Remote Sensing Measurements




Soriano, Melissa

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Soil moisture is a critical parameter for predicting and detecting floods and droughts, as well as indicating crop and vegetation health. Current indicators utilize surrogate or modeled measures of soil moisture. Actual observed soil moisture measurements have the potential to improve understanding of floods, droughts, and crop health. In this study, ground soil moisture daily average values were compared to estimates obtained from two microwave sensors, the EOS Aqua Advanced Microwave Scanning Radiometer (AMSR-E) and the Tropical Rainfall Measurement Mission Microwave Scanning Radiometer (TMI), as well as one optical sensor, the EOS Aqua Moderate Resolution Imaging Spectroradiometer (MODIS). The study areas were the Little Washita River Experimental Watershed in Oklahoma and the Little River Experimental Watershed in Georgia. This research compared AMSR-E, TMI, and MODIS data to ground data from the Little Washita Berg station and also compared AMSR-E and TMI data to ground data from the Little River Soil Climate Analysis Network station. AMSR-E and TMI performed better in Little Washita than in Little River during the crop-covered season. This may be due to the vegetation type, distribution, and density at Little River. AMSR-E exhibited a smaller range of variability than the TMI or in-situ measurements at both study sites for all time periods. In the crop-covered season of June, July, and August of 2003, MODIS soil moisture retrieval at the Little Washita site correlated better (R^2 = 0.772) with the in-situ measurements than AMSR-E or TMI soil moisture retrievals. The spatial resolution of MODIS (1 km) is finer than the spatial resolution of AMSR-E (~25 km) or TMI. Spatial resolution is an important factor because topography, soil properties, and vegetation cover may vary significantly over satellite footprints. Both microwave sensors are limited by their coarse spatial resolution. However, optical measurements are limited to cloud-free conditions. Future work includes research on algorithms which combine optical and microwave measurements to provide the advantages of each.



Soil moisture, AMSR-E, MODIS, Remote sensing, TMI, Little Washita