Abstract :
Principal component analysis (PCA) has been applied to a temporal series 1999-2002 of a yearly maximum value composite of the SPOT/VEGETATION normalized difference vegetation index for the Sardinia Island for extracting interannual variations affecting vegetation covers. Both naturally vegetated areas (forest, shrub-land, and herbaceous cover) and agricultural lands have been investigated in order to obtain information on the most prominent natural and/or man-induced alterations affecting vegetation behavior. Although a correct interpretation of PCA results generally requires additional information, such as geographical knowledge, climatological data, and field surveys, the main finding of the current investigation suggests that PCA can be a feasible tool to separately map areas showing different degrees of interannual variability, providing valuable information for discriminating unidirectional changes
Keywords :
agriculture; principal component analysis; time series; vegetation; vegetation mapping; AD 1999 to 2002; SPOT/VEGETATION NDVI temporal series; Sardinia Island; agricultural lands; forest; herbaceous cover; interannual variation; man-induced alterations; normalized difference vegetation index; principal component analysis; shrubland; unidirectional changes; vegetated areas; vegetation covers; Data mining; Floods; Hazards; Pollution measurement; Principal component analysis; Rain; Satellites; Stress; Time series analysis; Vegetation mapping; Principal component analysis (PCA); SPOT-VEGETATION normalized difference vegetation index (SPOT-VGT NDVI); time series analysis;
