Retrieval of Rugged Mountainous Areas Land Surface Temperature From High-Spatial-Resolution Thermal Infrared Remote Sensing Data

• Published in: IEEE transactions on geoscience and remote sensing Vol. 61; pp. 1 - 16
• Main Authors: He, Zhi-Wei, Tang, Bo-Hui
• Format: Journal Article
• Language: English
• Published: New York IEEE 2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adjacent effect; Algorithms; Atmosphere; Atmospheric modeling; Atmospheric water; Brightness temperature; Canopies; Canopy; Climate change; Data analysis; Emissivity; Infrared imagery; Land surface; Land surface temperature; Landsat; Landsat-9 data; Mathematical models; Mountain regions; Mountainous areas; mountainous surface temperature; Mountains; Parameters; Pixels; Plant cover; Radiance; Radiation; Radiative transfer; Remote sensing; Retrieval; Root-mean-square errors; Rough surfaces; Satellite imagery; Scattering; Spatial distribution; Surface radiation temperature; Surface roughness; Surface temperature; Surface topography; thermal infrared (TIR) remote sensing; Thermal radiation; topographic effect; Topographic effects; Water vapor; Water vapour

Mountainous land surface temperature (MLST) is one of the key surface feature parameters in studying mountainous climate change. However, for the high-spatial-resolution thermal infrared (TIR) remote sensing images, the current land surface temperature (LST) retrieval algorithms were developed witho...