Determination of Optimum Viewing Angles for the Angular Normalization of Land Surface Temperature over Vegetated Surface

作者:Ren, HZ (Ren, Huazhong)[ 1,2,4 ] ; Yan, GJ (Yan, Guangjian)[ 1 ] ; Liu, RY (Liu, Rongyuan)[ 1,4 ] ; Li, ZL (Li, Zhao-Liang)[ 3,4 ] ; Qin, QM (Qin, Qiming)[ 2 ] ; Nerry, F (Nerry, Francoise)[ 4 ] ; Liu, Q (Liu, Qiang)[ 5 ]

SENSORS

卷: 15  期: 4  页: 7537-7570

DOI: 10.3390/s150407537

出版年: APR 2015

摘要

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.

通讯作者地址: Yan, GJ (通讯作者)

Beijing Normal Univ, Sch Geog, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China.

地址:

[ 1 ] Beijing Normal Univ, Sch Geog, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China

[ 2 ] Peking Univ, Inst Remote Sensing & Geog Informat Syst, Beijing 100871, Peoples R China

[ 3 ] Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, Minist Agr, Key Lab Agriinformat, Beijing 100081, Peoples R China

[ 4 ] Univ Strasbourg, ICube Lab, F-67412 Illkirch Graffenstaden, France

[ 5 ] Beijing Normal Univ, Coll Global Change & Earth Syst Sci, Beijing 100875, Peoples R China