Using Image Reconstruction to Improve SMAP Radiometer Spatial Resolution

Launched in January 2015, NASA's SMAP mission was originallydesigned with a radar and radiometer, expecting to use the radardata to improve the radiometer spatial resolution. Our presentation will describe work that allows enhancement of the spatial resolution of the radiometer data in the absence of the radar feed. All techniques to transform radiometer data from irregularly-spaced swath format to griddedformat are characterized by a tradeoff between noise andspatio-temporal resolution. Conventional techniques, like theones considered and implemented in the SMAP L1C radiometer data products,(nearest-neighbor, drop-in-the-bucket and inverse-distancesquared), produce relatively smooth (low-noise) output, but alsoonly produce low-resolution products. Our team has been fundedby NASA to leverage image reconstruction techniques that we areusing on the historical satellite passive microwave record. Weare using the same technique, a radiometer version of the Scatterometer ImageReconstruction (rSIR) algorithm, to improve SMAP radiometerresolution. In related studies on passive microwave data, wedetermined that exact knowledge of the antenna pattern is notrequired; effective Enhanced-resolution SMAP soil moistureresolution improvement can be achieved with an approximateantenna pattern that models the true pattern. This presentationwill describe early work that applies the rSIR algorithm to improve the resolutionof SMAP radiometer data.