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Soil moisture maps provide quantitative information that, along with climate and energy balance, is critical to integrate with hydrologic processes for characterizing landscape conditions. However, soil moisture maps are difficult to produce for natural landscapes because of vegetation cover and complex topography. Satellite-based L-band microwave sensors are commonly used to develop spatial soil moisture data products, but most existing L-band satellites provide only coarse scale (one to tens of kilometers grid size), information that is unsuitable for measuring soil moisture variation at hillslope or watershed-scales. L-band sensors are typically deployed on satellite platforms and aircraft but have been too large to deploy on small uncrewed aircraft systems (UAS). There is a need for greater spatial resolution and development of effective measures of soil moisture across a variety of natural vegetation types. To address these challenges, a novel UAS-based L-band radiometer system was evaluated that has recently been tested in agricultural settings. In this study, L-band UAS was used to map soil moisture at 3–50-m (m) resolution in a 13 square kilometer (km2) mixed grassland-forested landscape in Sonoma County, California. The results represent the first application of this technology in a natural landscape with complex topography and vegetation. The L-band inversion of the radiative transfer model produced soil moisture maps with an average unbiased root mean squared error (ubRMSE) of 0.07 m3/m3 and a bias of 0.02 m3/m3. Improved fine-scale soil moisture maps developed using UAS-based systems may be used to help inform wildfire risk, improve hydrologic models, streamflow forecasting, and early detection of landslides.

Although satellite-based soil moisture products are useful at regional and global scales, they do not meet the needs of users who require high-resolution information for applications such as precision agriculture or catchment hydrologic modeling. The advent of uncrewed aerial systems (UASs) has opened new opportunities for bridging this need. We offer one of the very first validation studies on a dry-down event captured by a novel L-band radiometer onboard a Black Swift Technologies fixed-wing S2 UAS. A fallow cornfield at the Beltsville Agricultural Research Center was selected as a study area to validate volumetric soil moisture estimates in mid-April. By leveraging a comparable radiative transfer model to that of soil moisture active passive and soil moisture ocean salinity derived products, brightness temperature retrievals from this sensor are shown to successfully capture a week of dry-down poststorm event, as validated by HydraGO probe estimates (calibrated with gravimetric samples) and a nearby soil climate analysis network station. However, with a reported spatially averaged bias of −0.107 m3/m3 (compared to calibrated moisture values) and an ubRMSE of 0.028 m3/m3 potential concerns remain regarding the sensor calibration, vegetation and surface roughness corrections, and georeferencing. Nevertheless, given the potential of UAS for on-demand, high-resolution soil moisture retrievals, this collaborative effort provides critical feedback for informing future applications and improvements in the field of passive microwave remote sensing.