Satellite-Based Analysis of Vegetation Dynamics and Their Relationship with Rainfall Variability and Population Pressure in the Tiendaga Watershed, Mali

Global monitoring of vegetation using geospatial datasets provides valuable insights into the interactions between vegetation dynamics, rainfall variability, and demographic change. In many regions, environmental transformations driven by demographic growth and climatic fluctuations have intensified scientific research interest in understanding the causal and spatial relationships among these factors. This study aims to characterise the spatiotemporal variability of vegetation productivity and its relationships with rainfall variability and demographic growth in the Tiendaga watershed, southern Mali. A 16-day MODIS-Terra NDVI time series at 250 m resolution was analysed for the period 2000-2024 to assess vegetation dynamics. In addition, daily rainfall data from CHIRPS v3 with 5 km resolution (2000-2024) and demographic data from WorldPop with 1 km resolution (2000-2020) were used. Vegetation and rainfall trends were evaluated using the Mann-Kendall test, while the relationships between vegetation, rainfall, and population density were assessed using Spearman’s correlation analysis. The results indicate an overall positive trend in both vegetation greening and rainfall across the watershed over the study period, suggesting progressive vegetation recovery. Correlation analysis reveals a strong positive relationship between NDVI and rainfall, confirming that vegetation dynamics are highly sensitive to precipitation variability. In contrast, the relationship between vegetation and population density is moderate, suggesting that areas of higher demographic concentration may, in some cases, be associated with more effective land management practices, including agroforestry and plantations. This study provides updated evidence on environmental dynamics in the Tiendaga watershed and highlights the combined influence of climatic variability and demographic processes on vegetation change. The findings offer useful guidance for policymakers in designing climate adaptation strategies and sustainable land and natural resource management policies.