Land Degradation and its Drivers in Northern Ghana

Abstract

This study analyzes vegetation degradation, a proxy for land degradation, across Northern Ghana and quantifies the relative influence of climatic and anthropogenic drivers. To identify significant vegetation degradation trends, a 500 m resolution Normalized Difference Vegetation Index (NDVI) time series from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor ranging from 2004 to 2024 was analyzed using Sen’s slope and the Mann-Kendall test. A principal component analysis (PCA) of climate (precipitation, temperature, solar radiation, soil moisture, actual evapotranspiration), anthropogenic factors (population density, built-area extent, night-lights) and surface topography data (slope and elevation) variables was performed to extract the main gradients associated with variance in NDVI. A multiple linear regression of NDVI against the first three principal components yielded NDVI residual maps showing where observed vegetation change diverges from what would be expected using these drivers. Results indicated that 64.6% of the study area is heavily degraded, 26.9% restored, and 8.5% is stable. The PCA analysis implied that the first two components, mostly determined by moisture availability and temperature variation, explained 67.35% of the total variance, while the third, determined by population density, explained 14.28%. The residual mapping reveals local greening within known irrigation schemes and protected-area boundaries, explicitly highlighting the importance of targeted land-management practices. By incorporating trend analysis with multivariate driver decomposition and residual mapping, the framework presented in this study provides a replicable method for disentangling natural and anthropogenic drivers of land-change processes, even in relatively data-poor regions, and will help better inform land-restoration efforts.