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Proceedings Paper

Extraction of the vegetation fraction based on a stepwise spectral mixture analysis for the central and eastern area of source region of Yangtze, Yellow and Lantsang Rivers
Author(s): Xiaoxue Li; Ru An; Chunmei Qu; Renmin Yang; Tianyu Gong; Hong Wu; Ling Lu; Yingying Liu; Xin Liang
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Paper Abstract

Vegetation cover is an important parameter used in monitoring ecological changes of the source region of Yangtze, Yellow and Lantsang Rivers and understanding human activities. Thus, how to extract the large area's vegetation fraction quickly effectively is an open question. The traditional linear spectral mixture analysis (LSMA) assumes that the spectral reflectance is a mixture of several fixed endmember spectral values, which ignores considerable within-class variability. However, multiple endmember spectral mixture analysis (MESMA) overcomes the disadvantage by allowing the number and types to vary on a per-pixel basis. This paper proposes a stepwise spectral mixture analysis (SSMA) containing two steps of MESMA and adding the endmember fraction rationality rule in each step. The aim of the first step is to detect the pixels that didn't contain vegetation information at all and these pixels would be masked out. In the second step, MESMA is used to unmix the pixels only reserved in previous process. The results show that SSMA is more accurate than LSMA in extracting the vegetation fraction for the Three-Rivers. This means that SSMA is a good substitute for LSMA in studies on ecological changes. The concept of SSMA also can be applied for other large study areas.

Paper Details

Date Published: 24 October 2011
PDF: 7 pages
Proc. SPIE 8286, International Symposium on Lidar and Radar Mapping 2011: Technologies and Applications, 82861I (24 October 2011); doi: 10.1117/12.912343
Show Author Affiliations
Xiaoxue Li, Hohai Univ. (China)
Ru An, Hohai Univ. (China)
Chunmei Qu, Hohai Univ. (China)
Renmin Yang, Hohai Univ. (China)
Tianyu Gong, Hohai Univ. (China)
Hong Wu, Hohai Univ. (China)
Ling Lu, Hohai Univ. (China)
Yingying Liu, Hohai Univ. (China)
Xin Liang, Hohai Univ. (China)


Published in SPIE Proceedings Vol. 8286:
International Symposium on Lidar and Radar Mapping 2011: Technologies and Applications
Jonathan Li, Editor(s)

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