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The study uses 30 years of the third generation of Advanced Very-High-Resolution Radiometer (AVHRR) NDVI3g monthly data from 1982 to 2012 to identify the natural clusters and important driving factors of the upstream watersheds in Taiwan through hierarchical cluster analysis (HCA) and redundancy analysis (RDA), respectively. Subsequently, as a result of HCA, six clusters were identified based on the 30 years of monthly NDVI data, delineating unique NDVI characteristics of the upstream watersheds. Additionally, based on the RDA results, environmental factors, including precipitation, temperature, slope, and aspect, can explain approximately 52% of the NDVI variance over the entire time series. Among environmental factors, nine factors were identified significantly through RDA analysis for explaining NDVI variance: average slope, temperature, flat slope, northeast-facing slope, rainfall, east-facing slope, southeast-facing slope, west-facing slope, and northwest-facing slope, which reflect an intimate connection between climatic and orthographic factors with vegetation. Furthermore, the rainfall and temperature represent different variations in all scenarios and seasons. With consideration of the characteristics of the clusters and significant environmental factors, corresponding climate change adaptation strategies are proposed for each cluster under climate change scenarios. Thus, the results provide insight to assess the natural clustering of the upstream watersheds in Taiwan, benefitting future sustainable watershed management.

Cluster and Redundancy Analyses of Taiwan Upstream Watersheds Based on Monthly 30 Years AVHRR NDVI3g Data