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Journal of Applied Remote Sensing

Fractional snow-cover mapping using an improved endmember extraction algorithm
Author(s): Ying Zhang; Xiaodong Huang; Xiaohua Hao; Jie Wang; Wei Wang; Tiangang Liang
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Paper Abstract

We describe and validate an improved endmember extraction method to improve the fractional snow-cover mapping based on the algorithm for fast autonomous spectral endmember determination (N-FINDR) maximizing volume iteration algorithm and orthogonal subspace projection theory. A spectral library time series is first established by choosing the expected spectra information using prior knowledge, and the fractional snow cover (FSC) is then retrieved by a fully constrained least squares linear spectral mixture analysis. The retrieved fractional snow-cover products are validated by the FSC derived from Landsat imagery. Our results indicate that the improved algorithm can obtain the endmember information accurately, and the retrieved FSC has better accuracy than the MODIS standard fractional snow-cover product (MOD10A1).

Paper Details

Date Published: 21 May 2014
PDF: 11 pages
J. Appl. Remote Sens. 8(1) 084691 doi: 10.1117/1.JRS.8.084691
Published in: Journal of Applied Remote Sensing Volume 8, Issue 1
Show Author Affiliations
Ying Zhang, Lanzhou Univ. (China)
Xiaodong Huang, Lanzhou Univ. (China)
Xiaohua Hao, Cold and Arid Regions Environmental and Engineering Research Institute (China)
Jie Wang, Cold and Arid Regions Environmental and Engineering Research Institute (China)
Wei Wang, Lanzhou Univ. (China)
Institute of Arid Meteorology (China)
Tiangang Liang, Lanzhou Univ. (China)


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