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Determination of optimum viewing angles for the angular normalization of land surface temperature over vegetated
Huazhong Ren1,2,3, Guangjian Yan4, Rongyuan Liu5,6
1State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, Beijing 100875, China. f.nerry@unistra.fr.
Sensors (Basel, Switzerland)
|April 1, 2015
Summary
Multi-angular thermal observations can normalize land surface temperature (LST) data. Reliable LST retrieval requires only 3-4 viewing angles, simplifying future remote sensing sensor development.
Area of Science:
- Remote Sensing
- Earth Observation
- Thermal Infrared Physics
Background:
- Multi-angular observation is key for angular normalization of land surface temperature (LST) from remote sensing data.
- Accurate LST retrieval is crucial for various Earth science applications.
Purpose of the Study:
- To investigate the minimum viewing angle requirements for LST angular normalization.
- To develop and validate a thermal infrared Bidirectional Reflectance Distribution Function (TIR-BRDF) model.
Main Methods:
- Extended the kernel-driven BRDF model to the thermal infrared (TIR) domain (TIR-BRDF).
- Verified the TIR-BRDF model's accuracy and identified optimal viewing angle combinations.
- Applied the TIR-BRDF model to airborne multi-angular data for LST retrieval.
Main Results:
- The TIR-BRDF model demonstrated an uncertainty of less than 0.3 K.
- Reliable nadir LST (Te-nadir) retrieval was achieved with 3-4 directional observations.
- Te-nadir was consistently higher than slant-direction temperatures, with differences of 0.5-2.0 K (vegetated) and up to several Kelvins (non-vegetated).
Conclusions:
- A minimum of 3-4 viewing angles with large intervals are sufficient for reliable LST normalization.
- The developed TIR-BRDF model effectively retrieves nadir LST from multi-angular thermal data.
- Findings support the development of future multi-angular thermal infrared sensors.
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