Inter-Comparison of Thermal Measurements Using Ground-Based Sensors, UAV Thermal Cameras, and Eddy Covariance Radiometers
Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping III
SPIE - International Society for Optical Engineering
NASA, National Aeronautics and Space Administration NNX17AF51G
NASA, National Aeronautics and Space Administration
With the increasing availability of thermal proximity sensors, UAV-borne cameras, and eddy covariance radiometers there may be an assumption that information produced by these sensors is interchangeable or compatible. This assumption is often held for estimation of agricultural parameters such as canopy and soil temperature, energy balance components, and evapotranspiration. Nevertheless, environmental conditions, calibration, and ground settings may affect the relationship between measurements from each of these thermal sensors. This work presents a comparison between proximity infrared radiometer (IRT) sensors, microbolometer thermal cameras used in UAVs, and thermal radiometers used in eddy covariance towers in an agricultural setting. The information was collected in the 2015 and 2016 irrigation seasons at a commercial vineyard located in California for the USDA Agricultural Research Service Grape Remote Sensing Atmospheric Profile and Evapotranspiration Experiment (GRAPEX) Program. Information was captured at different times during diurnal cycles, and IRT and radiometer footprint areas were calculated for comparison with UAV thermal raster information. Issues such as sensor accuracy, the location of IRT sensors, diurnal temperature changes, and surface characterizations are presented.
Alfonso Torres-Rua, Hector Nieto, Chistopher Parry, Manal Elarab, Wesley Collatz, Calvin Coopmans, Lynn McKee, Mac McKee, William Kustas, "Inter-comparison of thermal measurements using ground-based sensors, UAV thermal cameras, and eddy covariance radiometers," Proc. SPIE 10664, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping III, 106640E (16 July 2018); doi: 10.1117/12.2305832
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