International Journal of Remote Sensing · 2008 · 61 citations · 22 references
Natural SciencesEarth SciencesEnvironmental SciencesAtmospheric ScienceHeat TransferRemote SensingInfrared Remote SensingLand Surface MonitoringRemote Sensing ImagerySatellite SensorsSurface Temperature RetrievalThermal Remote SensingAirborne Hyperspectral SensingAirborne Remote SensingField MeasurementsLand Surface EmissivityLand Surface Temperature RetrievalsTemperature-emissivity SeparationThermal Infrared ObservationsThermal Infrared Sensors
A description of thermal radiometric field measurements carried out in the \nframework of the European project SENtinel-2 and Fluorescence Experiment \n(SEN2FLEX) is presented. The field campaign was developed in the region of \nBarrax (Spain) during June and July 2005. The purpose of the thermal \nmeasurements was to retrieve biogeophysical parameters such as land surface \nemissivity (LSE) and temperature (LST) to validate airborne-based methodologies \nand to characterize different surfaces. Thermal measurements were carried \nout using two multiband field radiometers and several broadband field \nradiometers, pointing at different targets. High-resolution images acquired with \nthe Airborne Hyperspectral Scanner (AHS) sensor were used to retrieve LST and \nLSE, applying the Temperature and Emissivity Separation (TES) algorithm as \nwell as single-channel (SC) and two-channel (TC) methods. To this purpose, 10 \nAHS thermal infrared (TIR) bands (8–13 mm) were considered. LST and LSE \nestimations derived from AHS data were used to obtain heat fluxes and \nevapotranspiration (ET) as an application of thermal remote sensing in the \ncontext of agriculture and water management. To this end, an energy balance \nequation was solved using the evaporative fraction concept involved in the \nSimplified Surface Energy Balance Index (S-SEBI) model. The test of the \ndifferent algorithms and methods against ground-based measurements showed root mean square errors (RMSE) lower than 1.8K for temperature and lower \nthan 1.1 mm/day for daily ET.
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The journal of geophysical research
Quarterly Journal of the Royal Meteorological Society · 1949 · 1.5K citations
Alan R. Gillespie, Shuichi Rokugawa, Tsuneo Matsunaga et al. · IEEE Transactions on Geoscience and Remote Sensing · 1998 · 1.4K citations