文献类型：期刊文献

英文题名：The Potential of Forest Biomass Inversion Based on Vegetation Indices Using Multi-Angle CHRIS/PROBA Data

作者：Wang, Qiang[1,2,3] Pang, Yong[4] Li, Zengyuan[4] Sun, Guoqing[5] Chen, Erxue[4] Ni-Meister, Wenge[3]

第一作者：Wang, Qiang

通信作者：Wang, Q[1];Wang, Q[2];Wang, Q[3]

机构：[1]Harbin Inst Technol, Sch Elect Informat Engn, Harbin 150001, Peoples R China;[2]Heilongjiang Inst Technol, Dept Surveying Engn, Harbin 150040, Peoples R China;[3]CUNY Hunter Coll, Dept Geog, New York, NY 10065 USA;[4]Chinese Acad Forestry, Inst Forest Resource Informat Tech, Beijing 100091, Peoples R China;[5]Univ Maryland, Dept Geog, College Pk, MD 20742 USA

年份：2016

卷号：8

期号：11

外文期刊名：REMOTE SENSING

收录：;EI(收录号：20164703032540);Scopus(收录号：2-s2.0-84995469347);WOS:【SCI-EXPANDED(收录号:WOS:000388798400012)】；

基金：The research undertaken for this paper was funded by National Program on Key Basic Research Project-973 Program(Grant No. 2013CB733404), the National Natural Science Foundation of China (Grant No. 41471311, 41201435), Spatial Geography Information Laboratory Open Fund(Grant No. KJKF-12-02).

语种：英文

外文关键词：multi-angle remote sensing; forest structure information; vegetation indices; forest biomass; Bidirectional Reflectance Distribution Factor

摘要：Multi-angle remote sensing can either be regarded as an added source of uncertainty for variable retrieval, or as a source of additional information, which enhances variable retrieval compared to traditional single-angle observation. However, the magnitude of these angular and band effects for forest structure parameters is difficult to quantify. We used the Discrete Anisotropic Radiative Transfer (DART) model and the Zelig model to simulate the forest canopy Bidirectional Reflectance Distribution Factor (BRDF) in order to build a look-up table, and eight vegetation indices were used to assess the relationship between BRDF and forest biomass in order to find the sensitive angles and bands. Further, the European Space Agency (ESA) mission, Compact High Resolution Imaging Spectrometer onboard the Project for On-board Autonomy (CHRIS-PROBA) and field sample measurements, were selected to test the angular and band effects on forest biomass retrieval. The results showed that the off-nadir vegetation indices could predict the forest biomass more accurately than the nadir. Additionally, we found that the viewing angle effect is more important, but the band effect could not be ignored, and the sensitive angles for extracting forest biomass are greater viewing angles, especially around the hot and dark spot directions. This work highlighted the combination of angles and bands, and found a new index based on the traditional vegetation index, Atmospherically Resistant Vegetation Index (ARVI), which is calculated by combining sensitive angles and sensitive bands, such as blue band 490 nm/-55 degrees, green band 530 nm/55 degrees, and the red band 697 nm/55 degrees, and the new index was tested to improve the accuracy of forest biomass retrieval. This is a step forward in multi-angle remote sensing applications for mining the hidden relationship between BRDF and forest structure information, in order to increase the utilization efficiency of remote sensing data.