Integrating community mapping and biodiversity conservation for landslides risk reduction in Ngororero district

Abstract

Conventional top-down mapping approaches often overlook localized vulnerabilities and fail to actively engage communities in preparedness planning, leading to less effective strategies for disaster risk reduction. This study explores how community-based participatory mapping can strengthen landslide preparedness, enhance natural resource management, and support biodiversity conservation in Ngororero District, Rwanda. Between March and July 2024, a purposive sample of 30 community members mainly youth was trained to identify and map disaster hotspots using open-source tools such as OpenStreetMap, HOT Tasking Manager, and the Vespucci mobile application. The process combined local field data collection with geospatial analysis to assess landslide-prone areas, validate indigenous knowledge, and inform conservation-oriented land use planning. Data reliability was ensured through ground-truthing and expert verification. The results demonstrated that participatory mapping is both technically effective and socially transformative. Community mappers digitized 89% of identified hotspots (covering 87% of highrisk zones), and documented 101,780 buildings, 907 km of roads, and 310.10 km of waterways with an accuracy rate of 97%. Spatial analysis confirmed that 72% of recorded landslides occurred on slopes steeper than 80° within the 1,800–2,300m elevation range, aligning with community perceptions. Importantly, the integration of 500 slope-stabilizing native trees into the mapped areas provided ecological co-benefits improving slope stability, restoring biodiversity, and enhancing ecosystem services. This thesis positions community-driven mapping not only as a tool for risk reduction but also as an enabler of sustainable natural resource management, a driver of biodiversity conservation through native tree restoration, and a catalyst for open mapping innovation. The findings suggest that embedding participatory mapping into national disaster and conservation policies can generate hyper-local data, foster community ownership, and bridge the gap between scientific risk assessments and locally grounded action. By linking geospatial technologies, ecological restoration, and community engagement, this research contributes to the global discourse on climate adaptation and demonstrates a replicable model for mountain regions facing landslide threats.