IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · 2016 · 11 citations · 30 references
Environmental MonitoringEngineeringEmissivity RetrievalTerrestrial SensingThermal RadiationEarth ScienceEmissivity SeparationOptical PropertiesAtmospheric ScienceThermal AnalysisThermodynamicsThermal Infrared Remote SensingThermal Inertia MappingMaterials SciencePhysicsRadiative AbsorptionRadiation MeasurementSpectral Smoothness MethodRadiometryHeat TransferEarth Observation DataLand Surface TemperatureSpectral SmoothnessClimatologyNatural SciencesSpectroscopyApplied PhysicsRemote SensingLow-emissivity MaterialsThermal EngineeringThermal PropertyEmissivity
Land surface temperature and emissivity separation (TES) is a key problem in thermal infrared (TIR) remote sensing. Along with the development of civil applications, increasing numbers of man-made low-emissivity materials can be found around our living environment. In addition, the characteristics and variation in properties of those materials should also be concerned. However, there are still few TES methods for low-emissivity materials reported in the literature. This paper addresses the performance of the automatic retrieval of temperature and emissivity using spectral smoothness (ARTEMISS) method proposed by Borel (2008) for the retrieval of temperature and emissivity from hyperspectral TIR data for low-emissivity materials. The results show that those modeling errors are less than 0.11 K for temperature and 0.3% for emissivity as shown in the ARTEMISS algorithm if atmospheric parameters and the mean emissivity of material spectra are known. A sensitivity analysis has been performed, and the results show that the retrieval accuracy will be degraded with the increase of instrument noises, the errors of the atmospheric parameters, and the coarser spectral resolution. ARTEMISS can give a reasonable estimation of the temperature and emissivity for high- and low-emissivity materials; however, the performance of the algorithm is more seriously influenced by the atmospheric compensation than by the instrument noises. Our results show that the errors of temperature and emissivity become approximately three times than that when the instrument spectral properties are 1 cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> of sampling interval and 2 cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> of FWHM, and 4 cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> of sampling interval and 8 cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> of FWHM, respectively.
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Satellite-derived land surface temperature: Current status and perspectives
Zhao-Liang Li, Bo‐Hui Tang, Hua Wu et al. · Remote Sensing of Environment · 2013 · 2.1K citations · Full text
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Zhao-Liang Li, Hua Wu, Ning Wang et al. · International Journal of Remote Sensing · 2012 · 480 citations