Title of article :
Comparison of single-year and multiyear NDVI time series principal components in cold temperate biomes
Author/Authors :
M.، Hall-Beyer, نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2003
Abstract :
Standardized principal components analysis (SPCA) is performed on normalized difference vegetation index (NDVI) time series of a 10(degree) latitude by 10(degree) longitude area of western Canada including grassland, parkland, and forest ecosystems. When used with input from a single growing season (April-October), early components correspond closely to ecoregional mapping based on long-term vegetation composition. Later components isolate areas showing agricultural practice or climatic stress particular to the year. When three yearsʹ growing seasons are input together into a multiyear SPCA, similar patterns occur in the first component. However, components occur early in the series that discriminate areas having different seasonality patterns associated with plant phenology. Deciduous-dominated areas are well distinguished from grasslands. Multiyear SPCA includes an early component apparently related to latitudinal variation in day length, which does not appear in single-year component series. An early component unrelated to any known geographical or climatological pattern or event appears, which may relate to sensor degradation. Both single-year and multiyear SPCA isolate NDVI variability in higher numbered components that is limited in space and/or in time. This allows interpretation of transient or localized events using detailed local data, separating them from regional trends that occur in earlier (lower numbered) components of the series. These results demonstrate the possibility of refining ecoregion mapping based on selected early components to incorporate actual interannual variability for selected time periods as well as the longterm stable elements of biogeoclimatic regions. Longer time series could potentially quantify observed unidirectional trends resulting from climate change.
Keywords :
Data fusion , multiband optical , unsupervised segmentation , multitemporal synthetic aperture radar (SAR)
Journal title :
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
Journal title :
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING