Spatio-temporal assessment of NDVI response to climate change in a Mediterranean Cereal-Producing System

In recent decades, climate change has increasingly affected Mediterranean agricultural systems, which are dependent on climatic variability and water availability. This study investigates the spatio-temporal dynamics of vegetation activity and its relationship with key climatic drivers in the Alto Bradano area (north-eastern Basilicata, southern Italy) over the period 2000–2024. Vegetation dynamics were analysed using the Normalised Difference Vegetation Index (NDVI) derived from MODIS imagery, while total rainfall and mean air temperature were obtained from the CHIRPS and ERA5-Land datasets, respectively. The climatic datasets were also validated against the available ground-based meteorological observations. Annual and seasonal NDVI patterns were examined, temporal trends were assessed using Sen’s slope estimator and the Mann–Kendall test, and relationships between NDVI and climatic variables were explored through correlation analysis. Results reveal marked spatial and seasonal variability in NDVI, controlled by land use and climatic conditions. Forested areas exhibit higher and more stable NDVI values, whereas non-irrigated arable land shows pronounced seasonal and interannual variability. Within the scope of the present analysis, rainfall appears to play a key role in regulating vegetation activity in spring, while in autumn its influence is more spatially heterogeneous and less consistently significant. High temperatures tend to exert a limiting effect during summer, particularly in agricultural areas. Overall, the findings highlight the high sensitivity of Mediterranean agro-ecosystems to hydrothermal variability and emphasise the value of integrated satellite and climatic data for investigating climate–vegetation interactions in data-scarce environments and for supporting climate adaptation and sustainable land management strategies. • High climate sensitivity of Mediterranean cereal-producing agro-ecosystems. • Spatio-temporal vegetation trends assessed via non-parametric tests. • Precipitation driving vegetation dynamics during growth phases. • Summer thermal stress associated with reduced vegetation activity. • Integration of satellite-based and climatic indicators for climate–vegetation analysis.