抄録
In this paper, principal component analysis is applied to multitemporal global normalized vegetation index (NVI) data for extracting combined vegetation features which are uncorrelated combinations of multitemporal global NVI data. The monthly NVI data are prepared by selecting maximum value in pixels of weekly NVI data for removing cloud effect. The averaged monthly NVI data are made by averaging monthly NVI data through 3 years (82.4-85.3), and are used for principal component analysis. As the result, 7 components from PC1 to PC7 are extracted, and the meanings of these 7 principal components are also discussed.
