Dashboard of the Landscape Character of Nigeria
Every area of the earth's surface expresses some degree of spatial variations and understanding and delineating it could be a starting point for different levels of environmental investigations or model/result transfers. Inspired by the European Landscape Character Assessment (LCA), this dashboard presents a FAIRly Open interactive visualization of the LCA of Nigeria, leveraging machine learning and geospatial techniques to analyze and reveal spatial patterns across the country. The dashboard offers users a comprehensive view of the data through multiple layers of geospatial results, each representing different findings from the analyses. Users can explore and filter the data (interactively) to uncover deeper insights and patterns specific to Nigeria's various regions and landscape types. The Map layer feature included in the dashboard allows easy navigation between different analytical outputs, such as climate, altitude, land cover, and other landscape structure metrics that were assessed. Thus, this dashboard is expected to facilitate a deeper insight into the diverse landscape characteristics in the country, beyond its politico-administrative boundaries. As such, it is an actionable tool designed for researchers, policymakers, and environmental managers interested in visualizing and interpreting the spatial landscape characteristics of Nigeria, or other parts of the world where such is non-existent. Further details of the Dashboard (Tableau workbook package), including the methodology, dataset and codes, are available in the project’s Open Science Framework (OSF) entry, and the corresponding GitHub repository is stated in this submission. Access: Dashboard link: Tableau Public OSF Link: 10.17605/OSF.IO/E2K73 or osf.io/b3puh GitHub: Repository Note: This publication is expected to be updated as soon as it is due. The authors are committed to developing a broad landscape typology that can be implemented in different countries where none exists, globally. This project is open to collaboration with diverse and interested stakeholders and researchers. Feel free to contact the creator or any of the contributors.
Institutions
- University of Twente (NL)
Publication Details
- Journal
- University of Twente Research Information
- Published
- 2024-10-17
- DOI
- https://doi.org/10.5281/zenodo.13880381
- Citations
- 1
- Primary Topic
- Cancer, Hypoxia, and Metabolism
- Type
- article
- Field-Weighted Citation Impact
- 0.29