Land Surface Temperature Retrieval Using Satellite Remote Sensing

Dear Colleagues,

Land surface temperature (LST) is a good indicator of energy partitioning at the land surface–atmosphere boundary, and is sensitive to changing surface conditions. Satellite remote sensing provides opportunities to estimate global and continuous LSTs. The key challenges to retrieve LST using satellite remote sensing are the removal of the atmospheric attenuation, the decoupling between LST and land surface emissivity (LSE), and topography. Over the past four decades, dozens of LST retrieval algorithms have been developed and expanded from the traditional thermal infrared and hyperspectral infrared remote sensing to microwave remote sensing. Meanwhile, to fill the gaps in the derived LSTs, many scientists are devoted to the extension of LST retrievals under all-weather conditions. So far, many LST products have been generated from satellite data, such as the Advanced Spaceborne Thermal Emission Reflection Radiometer (ASTER) and MODerate resolution Imaging Spectroradiometer (MODIS) LST products. The validation of LST products is fundamental for their further applications. Additionally, the LSTs estimated from satellite data are inconsistent due to different observation local times and viewing zenith angles. To tackle the problems of inconsistency, the LSTs derived from satellite data should be temporally and angularly normalized. For these reasons, this Special Issue mainly aims to collect updated algorithms for LST estimation, validation, temporal and angular normalization, and the correlation between LST and surface air temperature.

Topics of interest for this Special Issue include but are not limited to:

• Decoupling between LST and LSE;
• LST estimation from satellite infrared and microwave measurements;
• Temporal and angular normalization of LSTs;
• LST validation;
• Correlation between LST and surface air temperature.

Dr. Geng-Ming Jiang
Dr. Bo-Hui Tang
Guest Editors

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