Ebrahim Babaeian1, Morteza Sadeghi2, Scott B. Jones2 and Markus Tuller1, (1)Department of Soil, Water and Environmental Science, University of Arizona, Tucson, AZ (2)Department of Plants, Soils and Climate, Utah State University, Logan, UT
A recently developed novel physically-based Optical TRApezoid Model (OPTRAM) for remote sensing of soil moisture will be evaluated based on satellite remote sensing data and ground-based cosmic-ray measurements. OPTRAM relies on shortwave infrared (SWIR) data and is based on the pixel distribution within the Normalized Difference Vegetation Index (NDVI) – Shortwave Infrared Transformed Reflectance (STR) space. The main advantages of OPTRAM when compared to standard trapezoid or triangle methods are its applicability to satellites that only provide optical data such as ESA’s Sentinel-2 (i.e., no thermal observations are required) and its amenability to universal parameterization for a given location. For the presented study, the NDVI–STR space was generated from long-term MODIS data for semi-arid (e.g., Walnut Gulch, AZ) regions with different land use and cover. To bridge the scale gap between coarse resolution soil moisture estimates (i.e., 500 m from MODIS observations) and ground soil moisture point data the soil moisture estimates from MODIS data were compared with cosmic-ray ground observations and other coarse resolution satellite soil moisture products that include SMAP, SMOS, and ASCAT. Preliminary results demonstrate the reliable performance of OPTRAM for large-scale estimation of soil moisture from MODIS optical data.