Landscape Character Assessment of Nigeria: A machine-assisted Learning Approach

Landscape Character Assessment (LCA) is a systematically structured approach to identifying and understanding the distinct features of a place, offering a basis for informed decision-making as may be required for landscape planning, conservation, and resource management. In this exposition, we present a machine-assisted LCA of Nigeria using open-access geospatial datasets and computational techniques to classify and analyze landscape typologies that inherently define the country. We also present an open, transparent, scalable and transferable framework that balances data-driven objectivity with an inclusive, systematic perspective on landscape classification. This approach ensures that landscape character is assessed beyond traditional subjective interpretations and, to some extent, supports evidence-based decision-making in landscape policy development, monitoring, and management. Additionally, we shared all our research outputs, including access to our GitHub repository, Tableau Dashboards, LCA Data of Nigeria and the Project on Open Science Framework (OSF), thus providing a replicable and flexible methodology for large-scale landscape assessments. All materials, including presentation slides and supporting files, are provided in our slides under an open-access license to facilitate knowledge sharing and encourage further applications, adaptation or transfer of our methods in different geographical contexts.