Remote Sensing for Land Surface Temperature (LST) Estimation, Generation, and Analysis
A special issue of Remote Sensing (ISSN 2072-4292).
Deadline for manuscript submissions: closed (31 December 2018) | Viewed by 145798
Special Issue Editors
Interests: thermal infrared remote sensing; land surface temperature; land surface emissivity; evapotranspiration; scaling problem; hyperspectral analysis; radiative transfer modelling
Special Issues, Collections and Topics in MDPI journals
2. State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Interests: retrieval and validation of land surface temperature/emissivity; retrieval and validation of net surface radiation; radiative transfer modeling; quantitative estimation of land surface variables from middle infrared data; hyperspectral thermal infrared data analysis
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
As the direct driving force in the exchange of long-wave radiation and turbulent heat fluxes at the surface–atmosphere interface, land surface temperature (LST) is one of the most important parameters in the physical processes of surface energy and water balance at local to global scales. Knowledge of reliable estimates of LST is crucial because many applications such as evapotranspiration, climate change, hydrological cycle, vegetation monitoring, urban climate and environmental studies, etc., rely on it.
With the development of remote sensing from space, satellite data offer the only possibility for measuring LST over the entire globe with sufficiently high temporal resolution and with complete spatially averaged rather than ground point-based values. Consequently, many efforts have been carried out to estimate LST from satellite thermal infrared (TIR) data. Up to now, many methods have been developed for retrieving LST from polar-orbit and geostationary satellite TIR data, and several methods are used to generate global LST products with fine spatial resolution, such as MODIS and ASTER LST products. However, there is still no “best method” for retrieving LST from space. All of the methods either rely on statistical relationships or assumptions and constraints to solve the inherent, ill-posed retrieval problem. Currently, TIR remote sensing measurements have been greatly improved in terms of spectral, spatial, and temporal resolution. These improvements will soon produce a clearer picture of the land surface than ever before. This is a good opportunity and also a big challenge to solve the inherent, ill-posed problem of retrieving LST from satellite data.
On the other hand, TIR data lose efficiency when the land surface is fully or partly covered by clouds. The passive microwave can observe the Earth’s surface under all-weather conditions but with a coarser spatial resolution. Its measurements are proposed to retrieve LST over cloudy skies and an effective model of combining LSTs retrieved from TIR and passive microwave satellite data is attempted to generate an all-weather high spatial LST product. This Special Issue plans to demonstrate the state-of-the-art reflecting the retrieval of LST from space measurements and the growing interest in generation and analyses of this parameter.
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Dr. Zhao-Liang Li
Dr. Bo-Hui Tang
Guest Editors
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Keywords
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Land surface temperature
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Land surface emissivity
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Thermal infrared data
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Passive microwave data
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LST product generation
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LST validation
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LST analysis
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Atmospheric corrections
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Temperature and emissivity separation
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Scaling
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