Landsat NDVI-based vegetation degradation dynamics and its response to rainfall variability and anthropogenic stressors in Southern Bui Plateau, Cameroon

Abstract

Land degradation is a serious problem affecting the livelihoods of people leaving in marginal lands. Its assessment has been made easy by a plethora of remote sensing techniques. This study seeks to establish the spatiotemporal trends in vegetation degradation and its response to climate change and anthropogenic stressors in Southern Bui Plateau, Cameroon. The study used mean annual Landsat-derived NDVI of cloud-free months to model vegetation degradation dynamics over 37 years (1984–2021) based on Ordinary Least Square (OLS) Regression and Pearson's Product Correlation of NDVI with Rainfall Anomaly Index (RAI) on a pixel-by-pixel basis. Areas undergoing significant degradation are estimated at 10.81% (1469.08 km2) and slight degradation, 23.57% (3202.39 km2). Total degraded lands accounted for 34.38% (either 4671.47 km2). Areas with slight improvement in vegetation cover accounted for 24.88%, while 9.69% area showed significant improvement. NDVI-Rainfall relationship revealed that areas significantly impacted by human activities and pressures (r ≤ -0.50) driving vegetation changes covered 24.67% (either 3352.03 km2), while those under climatic variability and change influence (r ≥ 0.50 ≥ 0.90) accounted for 55.84% (either 7587.26 km2), under both climatic and human stressors (r ≥ 0.50 < 0.70), 13.09% (either 1779.01 km2) and areas not significantly impacted, i.e., somewhat stable nature over the years accounted for 6.40% (869.04 km2). Areas under human vegetation pressures occupy the heavily grazed landscapes, the transhumance paths, and forested areas of the Kilum-Ijim forest. The practice of sustainable land management and landscape restoration initiatives are key to achieving land degradation neutrality at watershed scale.

Keywords

• Landsat NDVI
• Climate change
• Greening and browning trends
• Overgrazing