Abstract

The current remote sensing systems designed to measure soil moisture have a relatively coarse spatial resolution ranging from 25 to 50 km. The Advanced Microwave Scanning Radiometer 2 (AMSR2) is a passive sensor that measures soil moisture through C-band (6.9 and 7.3 GHz) observation of brightness temperature (BT). AMSR2 uses land parameter retrieval model to retrieve surface soil moisture and vegetation optical depth. This model partitions the microwave observation into its respective soil and vegetation emission components. AMSR2 loses sensitivity to soil moisture as vegetation density increases, during the growing season. Field observations show that AMSR2 tends to overestimate the soil moisture when the vegetation intensity increases and covers the soil. We address two existing issues in the use of soil moisture products of the AMSR2: (1) spatial resolution of the soil moisture product and (2) the impact of vegetation cover on the radiative transfer. We used a vegetative index to estimate when soil moisture retrieval is not sufficiently accurate and how the optical data can be used to improve soil moisture estimation. The land surface temperature and vegetation index products of the Visible Infrared Imaging Radiometer Suite are used to downscale the AMSR2 soil moisture products to 1 km. A series of soil moisture data collected in the field were used to analyze the accuracy of the downscaled soil moisture values and the results indicated that introduction of the BT in the downscaling model improves the accuracy of the soil moisture products over the vegetated areas. The mean absolute error (MAE) of the downscaled soil moisture values is ∼5.6 % —an improvement to 8.0% of original AMSR2 soil moisture products. In the presence of vegetation, however, the MAE is still greater than that of a similar analysis of AMSR2 product over semiarid areas.

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