Fractional snow-cover mapping using an improved endmember extraction algorithm

Ying Zhang; Xiaodong Huang; Xiaohua Hao; Jie Wang; Wei Wang; Tiangang Liang

doi:10.1117/1.JRS.8.084691

21 May 2014 Fractional snow-cover mapping using an improved endmember extraction algorithm

Ying Zhang, Xiaodong Huang, Xiaohua Hao, Jie Wang, Wei Wang, Tiangang Liang

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 8, Issue 1, 084691 (May 2014). https://doi.org/10.1117/1.JRS.8.084691

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).

Citation Download Citation

Ying Zhang, Xiaodong Huang, Xiaohua Hao, Jie Wang, Wei Wang, and Tiangang Liang "Fractional snow-cover mapping using an improved endmember extraction algorithm," Journal of Applied Remote Sensing 8(1), 084691 (21 May 2014). https://doi.org/10.1117/1.JRS.8.084691

Published: 21 May 2014

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