Title
Determination of optimum viewing angles for the angular normalization of land surface temperature over vegetated surface.
Abstract
Multi-angular observation of land surface thermal radiation is considered to be a promising method of performing the angular normalization of land surface temperature (LST) retrieved from remote sensing data. This paper focuses on an investigation of the minimum requirements of viewing angles to perform such normalizations on LST. The normally kernel-driven bi-directional reflectance distribution function (BRDF) is first extended to the thermal infrared (TIR) domain as TIR-BRDF model, and its uncertainty is shown to be less than 0.3 K when used to fit the hemispheric directional thermal radiation. A local optimum three-angle combination is found and verified using the TIR-BRDF model based on two patterns: the single-point pattern and the linear-array pattern. The TIR-BRDF is applied to an airborne multi-angular dataset to retrieve LST at nadir (T-e-nadir) from different viewing directions, and the results show that this model can obtain reliable T-e-nadir from 3 to 4 directional observations with large angle intervals, thus corresponding to large temperature angular variations. The T-e-nadir is generally larger than temperature of the slant direction, with a difference of approximately 0.5~2.0 K for vegetated pixels and up to several Kelvins for non-vegetated pixels. The findings of this paper will facilitate the future development of multi-angular thermal infrared sensors.
Year
DOI
Venue
2015
10.3390/s150407537
SENSORS
Keywords
Field
DocType
brdf
Bidirectional reflectance distribution function,Nadir,Normalization (statistics),Thermal radiation,Local optimum,Remote sensing,Optics,Pixel,Engineering,Kelvin,Distribution function
Journal
Volume
Issue
ISSN
15
4.0
1424-8220
Citations 
PageRank 
References 
4
0.42
14
Authors
7
Name
Order
Citations
PageRank
Huazhong Ren17323.56
Yan, G.2910.04
Rongyuan Liu340.42
Zhao-Liang Li4416127.21
Qiming Qin5212.74
Françoise Nerry640.76
Qiang Liu77311.01