Fractional snow-cover mapping using an improved endmember extraction algorithm

被引：9

作者：

Zhang, Ying ^{[1
]}

Huang, Xiaodong ^{[1
]}

Hao, Xiaohua ^{[2
]}

Wang, Jie ^{[2
]}

Wang, Wei ^{[1
,3
]}

Liang, Tiangang ^{[1
]}

机构：

[1] Lanzhou Univ, Coll Pastoral Agr Sci & Technol, State Key Lab Grassland Agroecosyst, Lanzhou 730020, Peoples R China

[2] Chinese Acad Sci, Cold & Arid Reg Environm & Engn Res Inst, Lanzhou 730000, Gansu, Peoples R China

[3] China Meteorol Adm, Inst Arid Meteorol, Lanzhou 730020, Peoples R China

来源：

JOURNAL OF APPLIED REMOTE SENSING | 2014年 / 8卷

基金：

中国国家自然科学基金;

关键词：

N-FINDR; orthogonal subspace projection; spectral unmixing algorithm; fully constrained least squares; SATELLITE DATA; MODIS; VALIDATION; ALBEDO;

D O I：

10.1117/1.JRS.8.084691

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

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). (C) 2014 Society of Photo-Optical Instrumentation Engineers (SPIE)

引用

页数：11

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