Integrating Optical and Microwave Satellite Observations for High Resolution Soil Moisture Estimate and Applications in CONUS Drought Analyses

Donglian Sun; Yu Li; Xiwu Zhan; Chaowei Yang; Ruixin Yang

doi:10.18282/rs.v7i1.500

Donglian Sun 1 Dept. of Geography and Geoinformation Science, George Mason University, Fairfax, VA 22030, USA
Yu Li 1 Dept. of Geography and Geoinformation Science, George Mason University, Fairfax, VA 22030, USA
Xiwu Zhan 2 NOAA/NESDIS Center for Satellite Applications and Research, College Park, MD 20742, USA
Chaowei Yang 1 Dept. of Geography and Geoinformation Science, George Mason University, Fairfax, VA 22030, USA
Ruixin Yang 1 Dept. of Geography and Geoinformation Science, George Mason University, Fairfax, VA 22030, USA

Article ID: 500

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DOI: https://doi.org/10.18282/rs.v7i1.500

Keywords: Soil moisture, high spatial resolution, regional drought, microwave and optical satellite remote sensing

Abstract

In this study, optical and microwave satellite observations are integrated to estimate soil moisture at high spatial resolution and applied for drought analysis in the continental United States. Â To estimate soil moisture, a new refined model is proposed to estimate soil moisture (SM) with auxiliary data like soil texture, topography, surface types, accumulated precipitation, in addition to Normalized Difference Vegetation Index and Land Surface Temperature (LST) used in the traditional universal triangle method. It is found the new proposed SM model using accumulated precipitation demonstrated close agreements with the U.S. Drought Monitor (USDM) spatial patterns.Â Currently, the USDM is providing a weekly map. Â Recently, â€œflashâ€ drought concept appears. To obtain drought map on daily basis, LST is derived from microwave observations and downscaled to the same resolution as the thermal infrared LST product and used to fill the gaps due to clouds in optical LST data. With the integrated daily LST available under nearly all weather conditions, daily soil moisture can be estimated at relatively high spatial resolution, thus drought maps based on soil moisture anomalies can be obtained at high spatial resolution on daily basis and made the flash drought analysis and monitoring become possible.

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