Land Statistics in Africa: Status and Implications for Policy

Date
Section
OoD
Document Type
Concept Notes
Keywords Description Executive Summary
The effective measurement of land resources is fundamental for sustainable development in Africa. Yet, most African countries face serious challenges in producing comprehensive, timely and harmonized land statistics. This concept note assesses the status of land statistics in Africa and proposes ways to improve measurement systems.
Land statistics consist of four inter-linked domains: land cover, land cover change, land tenure and land productivity. These combine to produce a cohesive nexus for land statistics that is critical for agricultural planning, environmental management, climate action, natural capital accounting and SDG monitoring, in particular SDG 15 (Life on Land).
Although there have been breakthroughs in remote sensing and geographic information systems (GIS) technology, land data in Africa are still disjointed. There are several incompatible datasets across ministries, with various harmonization techniques, reference periods, and methodologies. Land cover maps are outdated (2-to-10-year cycles); land registries cover only tiny fractions of national territory, with minimal acknowledgment of customary tenure and women’s land rights; agricultural surveys are uncommon; and many countries rely on global modeled data for SDG reporting, with limited national validation.
The policy consequences of these gaps are severe. Agricultural GDP statistics are often based on outdated assumptions, despite agriculture contributing 15-25% of GDP in many African nations. Land records are incomplete, limiting access to financing. There are attempts at natural capital accounting in Botswana, Rwanda, Uganda, Kenya, South Africa, and Ethiopia, which show they are feasible but are constrained by capacity and data limitations for scaling up.
This concept note complements ECA’s leadership through the former African Land Policy Centre. It relies on credible data sources, harmonized procedures consistent with international frameworks (SEEA, SDG monitoring, FAO LCCS, VGGT, UNCCD advice) and multi-stakeholder cooperation. It identifies options for strengthening conventional sources, using emerging technologies (cloud platforms, machine learning, drones), researching synthetic data and imputation, and boosting regional harmonization. It also proposes practical commitments at strategic, tactical and operational levels to modernize land statistics systems.
Additional Notes

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