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A persistent challenge in the measurement of soil moisture from satellites stems from the inherently low spatial resolution using active or passive system. The lobe differencing correlation radiometer (LDCR) on a small unmanned aerial system (sUAS) is shown to provide a capability to measure soil moisture at high spatial resolution for a range of scientific and operational purposes. Flight tests of LDCR on a fixed wing sUAS were performed at the Canton, Oklahoma Soilscape site in September 2015, and Irrigation Research Foundation (IRF) in Yuma, Colorado, in June 2016. The LDCR design and performance are discussed, and the calibration using both preflight lab test data and in-flight data over a calm pond was performed to calibrate the radiometer. Radio frequency interference (RFI) from the sUAS platform was observed and mitigated. The LDCR sampling processes are detailed and an implementation of the $\tau -\omega $ vegetation correction model along with a semiempirical surface roughness correction model incorporating a full-domain soil moisture mapping algorithm is presented. The algorithm uses a weakly nonlinear observation operator suitable for irregular sUAS flight trajectories that maps volumetric soil moisture (VSM) on a user-defined product grid from the sUAS sampling grid. Using LDCR radiometric and thermal measurements, along with Landsat-based vegetation water content (VWC) and soil texture information, soil moisture was mapped at decameter spatial resolution. The retrieved VSM data are favorably compared with in situ VSM measurements and irrigation records. A method for determining LDCR VSM estimation errors is developed to quantify the mapping algorithm accuracy and assess the impact of error sources.

The Lobe Differencing Correlating Radiometer (LDCR) developed at Center for Environmental Technology (CET) at CU, Boulder is a lightweight payload for small unmanned aerial systems (sUAS) enabling remote soil moisture measurement for precision agriculture applications. The second revision of the payload (LDCR Rev B) includes a digital correlation detector for which the data processing flow, instrument calibration, and test data analysis is presented. Cross frequency peak detection, time and frequency domain kurtosis, and complex coherence phase are used to detect radio frequency interference (RFI) in the high spectral resolution radiometric data. A quiescent state performance analysis using matched loads and antennas revealing RFI generated from the radiometer high speed data acquisition system, and the sUAS communication system is discussed.

The Lobe Differencing Correlating Radiometer (LDCR) developed at Center for Environmental Technology (CET) at CU, Boulder is a lightweight payload for small unmanned aerial systems (sUAS) enabling remote soil moisture measurement for precision agriculture applications. The second revision of the payload (LDCR Rev B) includes a digital correlation detector for which the data processing flow, instrument calibration, and test data analysis is presented. Cross frequency peak detection, time and frequency domain kurtosis, and complex coherence phase were used to characterize radio frequency interference (RFI) in the high spectral resolution radiometric data. A quiescent state performance analysis using matched loads and antennas revealing RFI generated from the radiometer high speed data acquisition system, and the sUAS communication system is discussed.