Abstract

The change history of vegetation cover and its relations to growing season precipitation (GSP) and average growing season temperature (AGST) in the source region of the Yellow River (SRYR) during 1990–2000 was retrieved based on the 1 km Advanced Very High‐Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) data and meteorological records. The results show an overall warming and drying trend of the climate and a common degradation tendency of the ecosystem, with a greening trend in higher rugged regions. The pixel‐by‐pixel correlations between NDVI and climate factors indicate that a decrease in GSP mainly affects ecosystems with low precipitation and worse vegetation condition, and superimposes on the effects of increasing AGST which further deteriorate the climate background of these ecosystems. However, the positive correlations between AGST and NDVI in some higher/rugged regions suggest that the raising temperature can ameliorate vegetation growth conditions in these areas. Comparison and combination of the results of three change detection algorithms, i.e. post‐classification comparison (PCC), principal components analysis (PCA) and a newly developed multi‐temporal image difference (MTID) method, show that the integration of different methods can give a more comprehensive understanding of vegetation changes than any single method.

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