A new vegetation index based on the universal pattern decomposition method

被引:43
作者
Zhang, Lifu
Furumi, S.
Muramatsu, K.
Fujiwara, N.
Daigo, M.
Zhang, Liangpei
机构
[1] Wuhan Univ, Natl Key Lab Informat Engn Surveying Mapping & Re, Wuhan 430079, Peoples R China
[2] Nara Womens Univ, Dept Informat & Comp Sci, Lab Nat Informat Sci, Nara 6308506, Japan
[3] Nara Womens Univ, KYOUSEI Sci Ctr Life & Nat, Nara 6308506, Japan
[4] Doshisha Univ, Dept Econ, Kyoto 6028580, Japan
基金
中国博士后科学基金;
关键词
vegetation index; hyperspectral data; sensor-independent; sensitivity analysis;
D O I
10.1080/01431160600857402
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
This study examined a new vegetation index, based on the universal pattern decomposition method (VIUPD). The universal pattern decomposition method (UPDM) allows for sensor-independent spectral analysis. Each pixel is expressed as the linear sum of standard spectral patterns for water, vegetation and soil, with supplementary patterns included when necessary. Pattern decomposition coefficients for each pixel contain almost all the sensor-derived information, while having the benefit of sensor independence. The VIUPD is expressed as a linear sum of the pattern decomposition coefficients; thus, the VIUPD is a sensor-independent index. Here, the VIUPD was used to examine vegetation amounts and degree of terrestrial vegetation vigor; VIUPD results were compared with results by the normalized difference vegetation index (NDVI), an enhanced vegetation index (EVI) and a conventional vegetation index based on pattern decomposition (VIPD). The results showed that the VIUPD reflects vegetation and vegetation activity more sensitively than the NDVI and EVI.
引用
收藏
页码:107 / 124
页数:18
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