Land surface temperature and emissivity retrieval from airborne hyperspectral thermal infrared hyperspectral data and application

  • role: First author第一作者
  • Affiliation:

    Institute of Remote Sensing and Geographical Information System, School of Earth and Space Sciences, Peking University, Beijing 100871, China

    Beijing Institute of Remote Sensing Information, Beijing 100192, China

  • Email:niejing92@pku.edu.cn
  • Introduction:1992E-mailniejing92@pku.edu.cn
NIE Jing12,  
  • role: Corresponding author通信作者
  • Affiliation:

    Institute of Remote Sensing and Geographical Information System, School of Earth and Space Sciences, Peking University, Beijing 100871, China

  • Email:renhuazhong@pku.edu.cn
  • Introduction:1985E-mailrenhuazhong@pku.edu.cn
REN Huazhong1*,  
  • Affiliation:

    Institute of Remote Sensing and Geographical Information System, School of Earth and Space Sciences, Peking University, Beijing 100871, China

ZHENG Yitong1,  
  • Affiliation:

    Beijing Research Institute of Uranium Geology, Beijing 100029, China

LIU Hongcheng3,  
  • Affiliation:

    Institute of Remote Sensing and Geographical Information System, School of Earth and Space Sciences, Peking University, Beijing 100871, China

ZHU Jinshun1

résumé

The spectral emissivity of high-resolution hyperspectral thermal infrared data can be used for mineral identification, and is regarded as an effective complement to optical remote sensing for land surface object recognition. Thermal Airborne Hyperspectral Imager (TASI) has 32 bands in the wavelength range of 8—11.5 μm, and thus can provide useful information for the retrieval of land surface temperature and emissivity spectrum. Therefore, TASI has been widely used in the fields of land surface thermal emission parameters estimate and mineral identification. On basis of the TASI images collected on October 2018 in Fuyun of Xinjiang province, this paper first performed atmospheric correction on the TASI image using the reanalysis atmospheric profiles from National Centers for Environmental Prediction (NCEP) dataset and the MODTRAN package, and then developed a Temperature and Emissivity Separation (TES) method to synchronously retrieve temperature and spectral emissivity from the surface-leaving radiance after the atmospheric correction. Ground multiple-band emissivity from the radiometer CE312 was applied for the verification of retrieved emissivity result, indicating a high accuracy of the retrieval result from TASI image, with an emissivity error about 0.01 for bands with wavelength larger than 0.96 μm. Finally, the spectral emissivity retrieved from TASI image was used to illustrate the spatial distribution of the kaolinite in the study area. It is thought that the algorithms and application results in this paper can provide an important reference for the airborne hyperspectral thermal infrared sensor in the coming future.

mots-clés

remote sensing;airborne thermal infrared hyperspectral data;land surface temperature;Thermal Airborne Hyperspectral Imager (TASI);emissivity spectrum;mineral identification

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