Spatiotemporal trends in cropland phenology in the Nigerian sahel derived from MODIS NDVI

This project presents a spatiotemporal analysis of vegetation phenology dynamics in the Nigerian Sahel using long-term satellite-derived NDVI data. The study examines temporal trends, variability, and spatial heterogeneity in key seasonality metrics, including start of season (SOS), end of season (EOS), length of season (LOS), and vegetation vigor (GSA), over a 22-year period. The analysis focuses on detecting shifts in growing season timing and structure across cropland systems, with particular attention to spatial variation across states and ecological gradients. Pixel-level time series were analyzed using smoothing-based phenology extraction methods and linear trend estimation, complemented by mixed-effects modeling to separate long-term temporal trends from location-specific variability. Sensitivity analyses were conducted to evaluate the robustness of results to sampling design and smoothing parameters, and spatial autocorrelation tests were performed to assess residual spatial dependence. The findings provide baseline empirical evidence of changing vegetation dynamics in the Nigerian Sahel, highlighting patterns of delayed season onset, stable end-of-season timing, and shortening growing seasons. The datasets, processing scripts, and analytical outputs provide a reproducible foundation for future research linking vegetation dynamics to climate drivers such as rainfall variability, temperature trends, and extreme events, and support further work on climate impacts, agricultural systems, and adaptation planning in semi-arid regions.