K-means classification of long-term global vegetation index variation

Recent global warming has driven substantial changes in terrestrial vegetation, yet long-term global patterns remain insufficiently characterized. The Normalized Difference Vegetation Index (NDVI) provides a robust measure for assessing vegetation dynamics, and previous studies have reported regionally varying greening and browning trends. To further clarify these global-scale vegetation responses, this study examined NDVI changes from 1982 to 2022 and classified long-term NDVI variability using a frequency-based k-means clustering approach. Analyses revealed increasing NDVI trends in Europe, western Russia, India, China, and Central Africa, while declines were observed in Canada, South America, South Africa, and eastern Central Asia. Arid and semi-arid regions maintained persistently low NDVI values, whereas high-latitude tundra and transitional ecosystems showed strong seasonal variability and extended growing seasons associated with rising temperatures. Subtropic–midlatitude humid regions exhibited seasonal cycles linked to cropping activities, and tropical rainforests maintained high NDVI levels but showed increasing temporal variability. The k-means classification further indicated that vegetation functional diversity has increased under warming and hydrological intensification, alongside a general extension of vegetation growth periods—including earlier spring green-up and delayed autumn senescence. These findings highlight distinct global patterns of vegetation–climate interactions and provide an improved basis for interpreting ecosystem responses to ongoing climate change. Future research incorporating process-based models and climate feedback mechanisms will be essential for understanding the long-term implications of these observed shifts.