
Proceedings Paper
An impact study of NDVI on the BPDF model under different atmosphere and multi-angles conditionsFormat | Member Price | Non-Member Price |
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Paper Abstract
Normalized Differential Vegetation Index (NDVI), usually calculated by surface reflectance at red and near-infrared bands (NDVI_Surf), which is an essential index in remote sensing. NDVI_Surf is generally used to discriminate different surface cover types and adopted in many surface models as a vital adjustable parameter to estimate the surface reflectance in remote sensing aerosol retrieval. However, NDVI_Surf is challenging to obtained directly and usually calculated by the red and near-infrared reflectance at the top of atmosphere (NDVI_TOA). NDVI_TOA is very susceptible to the atmosphere with different angles. If NDVI_Surf is replaced by the NDVI_TOA, it will cause an error of surface reflectance estimation and then make the wrong aerosol retrieval. In this study, Second Simulation of a Satellite Signal in the Solar Spectrum, Vector version (6SV) radiative transfer code was used to analyze the effects of NDVI_TOA on a surface Bidirectional Polarization Distribution Function (BPDF) model under different atmosphere and multi-angles conditions. The results display that the NDVI_TOA decreases with the rise of AOD. Within scattering angle (SA) of 60° to 115°, the influences of NDVI_TOA on BPDF are great and increases with the AOD reduces. Within the SA between 115° to 180°, the effects of NDVI_TOA on BPDF are small and remain unchanged with the AOD decreases. The simulation and analysis results have a great significance for polarized aerosol retrieval.
Paper Details
Date Published: 18 December 2019
PDF: 7 pages
Proc. SPIE 11338, AOPC 2019: Optical Sensing and Imaging Technology, 1133834 (18 December 2019); doi: 10.1117/12.2547899
Published in SPIE Proceedings Vol. 11338:
AOPC 2019: Optical Sensing and Imaging Technology
John E. Greivenkamp; Jun Tanida; Yadong Jiang; HaiMei Gong; Jin Lu; Dong Liu, Editor(s)
PDF: 7 pages
Proc. SPIE 11338, AOPC 2019: Optical Sensing and Imaging Technology, 1133834 (18 December 2019); doi: 10.1117/12.2547899
Show Author Affiliations
Bangyu Ge, Institute of Remote Sensing and Digital Earth (China)
Univ. of Chinese Academy of Sciences (China)
Zhengqiang Li, Institute of Remote Sensing and Digital Earth (China)
Weizhen Hou, Institute of Remote Sensing and Digital Earth (China)
State Key Lab. of Remote Sensing Science (China)
Yan Ma, Institute of Remote Sensing and Digital Earth (China)
Univ. of Chinese Academy of Sciences (China)
Zhengqiang Li, Institute of Remote Sensing and Digital Earth (China)
Weizhen Hou, Institute of Remote Sensing and Digital Earth (China)
State Key Lab. of Remote Sensing Science (China)
Yan Ma, Institute of Remote Sensing and Digital Earth (China)
Yisong Xie, Institute of Remote Sensing and Digital Earth (China)
Haofei Wang, Institute of Remote Sensing and Digital Earth (China)
Univ. of Chinese Academy of Sciences (China)
Sifeng Zhu, Institute of Remote Sensing and Digital Earth (China)
Univ. of Chinese Academy of Sciences (China)
Jie Chen, Institute of Remote Sensing and Digital Earth (China)
Univ. of Chinese Academy of Sciences (China)
Haofei Wang, Institute of Remote Sensing and Digital Earth (China)
Univ. of Chinese Academy of Sciences (China)
Sifeng Zhu, Institute of Remote Sensing and Digital Earth (China)
Univ. of Chinese Academy of Sciences (China)
Jie Chen, Institute of Remote Sensing and Digital Earth (China)
Univ. of Chinese Academy of Sciences (China)
Published in SPIE Proceedings Vol. 11338:
AOPC 2019: Optical Sensing and Imaging Technology
John E. Greivenkamp; Jun Tanida; Yadong Jiang; HaiMei Gong; Jin Lu; Dong Liu, Editor(s)
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