What question did this study set out to answer?

The research aims to assess land degradation patterns in Nigeria's Guinea Savannah using default and adapted earth observation methods for SDG 15.3.1 reporting.

April 7, 2026Open Access

Fine-Scale Land Degradation Assessment in Nigeria’s Guinea Savannah: Enhancing SDG 15.3.1 Reporting through Default and Adapted Earth Observation Methods

Key Points

The research aims to assess land degradation patterns in Nigeria's Guinea Savannah using default and adapted earth observation methods for SDG 15.3.1 reporting.
Conducted spatiotemporal analysis using national data and UNCCD-endorsed Default and Adapted Methods.
Assessed land degradation at subnational scales in the Nigerian Guinea Savannah.
Monitored baseline and periods to evaluate degradation levels.
The Adapted Method detected 6% to 28% more degraded areas compared to the Default Method.
Degraded areas decreased from 0.70% to 0.38% under the Default Method; the Adapted Method increased from 26.00% to 28.68%.
Biomass loss indicated declining land productivity: from 22.55% to 10.20% under Default and from 5.15% to 3.84% under Adapted.

Abstract

Land degradation (LD) is a major barrier toward achieving the Sustainable Development Goals (SDGs), particularly in Sub-Saharan Africa (SSA), due to challenges in national assessments. A comprehensive spatiotemporal analysis integrating all three UNCCD-recommended indicators at critical subnational scales remains absent in Nigeria, despite global reporting frameworks. In the Nigerian Guinea Savannah (NGS), LD severely threatens livelihoods, ecosystem services, and sustainability efforts. To support SDG 15.3.1, this study aims to provide a comparative assessment and enhanced context for subnational LD patterns and status in the NGS, using available national data and the UNCCD-endorsed Default Method (DM) and its Adapted Method (AM), across defined baseline and monitoring periods. Results reveal that the AM detected between 6% and 28% more degraded areas than the DM, demonstrating greater sensitivity to localized degradation. Based on the LULC indicator, degraded areas declined from 0.70% to 0.38% under the DM, whereas the AM increased from 26.00% to 28.68% of the NGS. Biomass loss showed declining land productivity, from 22.55% to 10.20% under DM and from 5.15% to 3.84% under AM. Both methods confirmed widespread degradation in key frontline states in the NGS, with consistent convergence in degradation patterns. However, the AM proved more capable of identifying degradation masked by coarse-resolution data, especially under prevailing unsustainable conditions such as widespread insecurity-induced land abandonment. This study presents a robust, locally adapted EO-based framework for assessing SDG 15.3.1 in Nigeria and, by extension, across SSA, providing actionable insights to close management gaps and inform policy interventions at multi-levels. • First fine-scale comparison of UNCCD Default and Adapted methods for the NGS • Adapted method detected 6–28% more degradation than Default due to coarse data • Cropland expansion, tree cover loss, and urban growth dominate land degradation drivers • Conflict-driven land abandonment complicates land status signals • A scalable, locally adapted EO framework to strengthen(sub)national LDN reporting

Fine-Scale Land Degradation Assessment in Nigeria’s Guinea Savannah: Enhancing SDG 15.3.1 Reporting through Default and Adapted Earth Observation Methods

Key Points

Abstract

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