A PROSAIL-based spectral unmixing algorithm for solving vegetation spectral variability problem

Qianqian Li; Wenfei Luo; Fangfang Wang

doi:10.1117/12.2283462

19 February 2018 A PROSAIL-based spectral unmixing algorithm for solving vegetation spectral variability problem

Qianqian Li, Wenfei Luo, Fangfang Wang

Proceedings Volume 10607, MIPPR 2017: Multispectral Image Acquisition, Processing, and Analysis; 106070L (2018) https://doi.org/10.1117/12.2283462
Event: Tenth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2017), 2017, Xiangyang, China

Abstract

The spectral signature of vegetation in the image is easily affected by background soil reflectance and spectral variability of vegetation reflectance, spectral variability is one of the major error sources of unmixing. The traditional algorithms do not solve spectral variability problem from the mechanism. In this paper, we take advantage of radiative transfer model, in order to describe the spectral variability of endmember. As a result, the spectral variability can be quantitatively described. The experimental results show that the PROSAIL Model Spectral Unmixing (PMSU) algorithm has higher unmixing precision than the other algorithms.

Citation Download Citation

Qianqian Li, Wenfei Luo, and Fangfang Wang "A PROSAIL-based spectral unmixing algorithm for solving vegetation spectral variability problem", Proc. SPIE 10607, MIPPR 2017: Multispectral Image Acquisition, Processing, and Analysis, 106070L (19 February 2018); https://doi.org/10.1117/12.2283462

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