Applications of Hyperspectral Thermal Infrared Data in Land Surface

Dear Colleagues,

Hyperspectral thermal infrared data contain rich long-wave spectral information, which can precisely reflect the unique diagnostic characteristics of the thermal infrared spectrum. At the same time, the hyperspectral characteristics can also provide more reasonable assumptions and constraints for the ill-posed inversion of the key thermal infrared characteristic parameters. Therefore, the hyperspectral thermal infrared remote sensing has important research value and application prospects.

Since its conception, hyperspectral thermal infrared remote sensing technology has rapidly developed on the basis of absorbing multispectral thermal infrared remote sensing technology, and has become an important research direction and breakthrough point in thermal infrared remote sensing research. With the development of sensors and remote sensing data, the application of hyperspectral thermal infrared remote sensing has begun to take shape. Specifically, there is a wide range of land surface applications, including land surface temperature and land surface emissivity retrieval, mineral identification and geological mapping, petroleum hydrocarbon compound detection, fire remote sensing monitoring, vegetation water stress detection, and others. We are facing the rapid development of hyperspectral infrared remote sensing applications. This is a good opportunity to present the land surface applications of hyperspectral thermal infrared data.

This Special Issue aims to demonstrate recent efforts in and contributions to the applications of hyperspectral thermal infrared data in land surface, including but not limited to:

• Advances and pre-research in hyperspectral thermal infrared remote sensing sensors;
• Approaches to dealing with hyperspectral thermal infrared remote sensing data, such as atmospheric effect correction, land surface temperature and emissivity separation, and the integrated inversion of surface and atmospheric parameters;
• Studies for target detection and identification, as well as resources and environment monitoring using hyperspectral thermal infrared remote sensing;
  Methodologies for multi-source data integration or fusion, i.e., the combination of NIR, SWIR, multispectral TIR or hyperspectral TIR data;
• Scientifical reports of hyperspectral thermal infrared campaigns, including calibration and validation.

Dr. Hua Wu
Dr. Bohui Tang
Dr. Sibo Duan
Dr. Yonggang Qian
Guest Editors

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• hyperspectral thermal infrared sensors
• atmospheric effect correction
• land surface temperature and emissivity separation
• target detection and identification
• resources and environment monitoring
• data fusion