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Fine-scale land degradation assessment in Nigeria's Guinea Savannah: Enhancing SDG 15.3.1 reporting using default and adapted Earth Observation methods
Department of Geography, University of Bergen, Bergen, Norway Department of Geography, Federal University of Technology, Minna, Nigeria Department of Earth System Sciences, University of Hamburg, Germany.
Department of Earth System Sciences, University of Hamburg, Germany.
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Environmental and Life Sciences (from 2013). Karlstad University, Faculty of Arts and Social Sciences (starting 2013), Center for Societal Risk Research, CSR (from 2020). Land Systems and Sustainable Land Management, Institute of Geography, University of Bern, Bern, Switzerland.ORCID iD: 0000-0001-6248-7430
Department of Earth System Sciences, University of Hamburg, Germany.
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2026 (English)In: Environmental and Sustainability Indicators, ISSN 2665-9727, Vol. 30, article id 101250Article in journal (Refereed) Published
Abstract [en]

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. 

Place, publisher, year, edition, pages
Elsevier, 2026. Vol. 30, article id 101250
Keywords [en]
Africa, Earth observation, Guinea savannah, Land degradation, Method, Nigeria, SDG
National Category
Environmental Sciences
Research subject
Environmental Science
Identifiers
URN: urn:nbn:se:kau:diva-109763DOI: 10.1016/j.indic.2026.101250ISI: 001745549900001Scopus ID: 2-s2.0-105035160497OAI: oai:DiVA.org:kau-109763DiVA, id: diva2:2054255
Available from: 2026-04-20 Created: 2026-04-20 Last updated: 2026-05-08Bibliographically approved

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Akinyemi, Felicia O.

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