Spatial Intelligence

GIS &
Spatial Analysis

Systematic conservation prioritization using Marxan and Zonation algorithms across six West African countries, integrating biodiversity, threat, and feasibility layers.

Explore Methodology →
Client Profile

Client

Anonymous Conservation Organization — West Africa Priority Mapping Initiative

Project Scope

Spatial prioritization across 6 West African countries to identify conservation areas maximizing biodiversity representation while minimizing land-use conflict.

The Challenge

Systematic Conservation Planning

Conservation resources are finite. Systematic spatial analysis identifies where protection yields the greatest biodiversity return per unit investment.

Data Fragmentation

Biodiversity occurrence data is sparse and unevenly distributed across West Africa, requiring careful gap-filling and spatial interpolation.

Conflicting Land Uses

Agricultural expansion, mining concessions, and urban development overlap with high-biodiversity areas, creating complex trade-offs.

Stakeholder Alignment

Priority maps must be defensible to government agencies, local communities, and international donors. Transparency is essential.

Methodology

Spatial Prioritization Pipeline

Our workflow follows the systematic conservation planning framework (Margules & Pressey, 2000), adapted for West African data availability.

1

Data Collection

Species occurrence data from GBIF, IUCN Red List range maps, forest cover from Hansen GFW, and elevation from SRTM.

2

Standardization

All layers projected to WGS84 / UTM zones, resampled to 1 km resolution, and normalized to 0-1 range for compatibility.

3

Gap Analysis

Species representation evaluated against existing protected areas; representation gaps identified for endemic and threatened taxa.

4

Marxan / Zonation

Spatial prioritization algorithms run with biodiversity features, cost layers, and boundary length modifiers for compact solutions.

5

Stakeholder Validation

Workshops with national forestry services, NGOs, and community representatives to validate and refine priority area boundaries.

6

Output Maps

Final priority maps, sensitivity analysis, and scenario comparisons delivered as QGIS projects, GeoPDFs, and web services.

QGIS 3.28 ArcGIS Pro OpenStreetMap GBIF Occurrence IUCN Red List Hansen GFW SRTM Elevation
Data Visualization

Conservation Priority by Region

Interactive D3.js stacked bar chart showing conservation priority scores decomposed by biodiversity value, threat level, and feasibility across six West African countries.

Figure 1: Stacked conservation priority scores by country. Higher values indicate greater urgency for protection, driven by endemic species richness, deforestation pressure, and current protection gap.

3D Priority Area Elevation Model

Three.js interactive terrain model of West Africa showing priority conservation areas overlaid on elevation and topographic features.

Figure 2: 3D elevation model of West African priority conservation regions. Colored rings indicate priority conservation areas; terrain color encodes elevation from coastal lowlands to Guinea Highlands.

Project Results

Key Performance Metrics

0
Countries Analyzed
0
Species Mapped
0
Priority Areas Identified
0
Recommended for Protection
Academic Foundation

Peer-Reviewed Literature

Our systematic conservation planning approach is grounded in foundational and contemporary literature in conservation biology and spatial ecology.

Margules, C.R. & Pressey, R.L. (2000). "Systematic conservation planning." Nature, 405(6783), 243-253.

DOI: 10.1038/35012251

Myers, N., Mittermeier, R.A., Mittermeier, C.G., da Fonseca, G.A.B., & Kent, J. (2000). "Biodiversity hotspots for conservation priorities." Nature, 403(6772), 853-858.

DOI: 10.1038/35002501

Moilanen, A., Wilson, K.A., & Possingham, H.P. (2009). Spatial Conservation Prioritization: Quantitative Methods and Computational Tools. Oxford University Press.

DOI: 10.1093/oso/9780199547776.001.0001
Project Timeline

Execution Phases

Phase 1
Data Compilation & QA
Collection of 1,247 species occurrence datasets, remote sensing layers, and socioeconomic data from six national databases. Rigorous QA for spatial accuracy and taxonomic consistency.
Phase 2
Spatial Analysis & Modeling
Marxan and Zonation runs across multiple scenarios (species representation, climate refugia, cost minimization). Sensitivity analysis performed for key parameters.
Phase 3
Stakeholder Workshops
Three regional workshops in Dakar, Abidjan, and Yaoundé with government representatives, NGOs, and community leaders to validate and refine priority area boundaries.
Phase 4
Deliverables & Policy Integration
Final priority maps, technical report, and policy briefs delivered to national environment ministries and the ECOWAS Commission for integration into regional planning frameworks.