Remote Sensing of Land Surface Temperature: Retrieval, Modeling, and Applications
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Atmospheric Remote Sensing".
Deadline for manuscript submissions: 31 March 2025 | Viewed by 2084
Special Issue Editors
Interests: thermal remote sensing; urban thermal environment; land surface temperature
Interests: thermal remote sensing; land surface temperature; retrieval and validation
Interests: thermal remote sensing; urban thermal environment
Special Issue Information
Dear Colleagues,
Land surface temperature (LST) plays a central role in many research fields, including climatology, urban studies, hydrology, ecology and biophysical chemistry. In recent years, the rapid development of remote sensing technology has provided unprecedented opportunities for deriving LST with high precision and spatio-temporal resolution. However, the particular technique used to sample satellites, the variability of atmospheric conditions, the intricate surface characteristics present and the intrinsic complexity of the coupled surface–atmosphere system continues to pose significant challenges to the accurate retrieval, modelling and application of LST.
The aim of this Special Issue is to review the latest developments and challenges in LST retrieval, modelling and applications. In particular, it will address the following topics: enhancing the accuracy of LST retrieval in complex surface environments, especially in highly heterogeneous urban areas; improving the spatial and temporal resolution of LST products through the application of advanced physical models and statistical and learning models; and expanding the potential applications of LST in diverse fields, including urban climate, urban planning, climate change, vegetation monitoring, weather forecasting, drought monitoring, agricultural monitoring, and carbon cycle and balance.
The scope of this Special Issue includes, but is not limited to, the following topics:
- LST retrieval;
- LST modelling;
- All-weather LST production;
- Temporal and spatial downscaling approach;
- Reasonable validation method;
- Physical model;
- Machine learning model;
- Deep learning model;
- Urban heat island;
- Urban warming;
- Heatwave and heat stress;
- Phenology monitoring;
- Weather forecasting;
- Drought monitoring;
- Agricultural monitoring;
- Carbon cycle and balance.
Dr. Zihan Liu
Dr. Jin Ma
Dr. Kangning Li
Dr. Lluís Pérez-Planells
Guest Editors
Manuscript Submission Information
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Keywords
- thermal infrared remote sensing
- land surface temperature (LST)
- urban thermal environment
- climate change
- urbanization
- agriculture application
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