Bridging Local Knowledge and Remote Sensing in Southeast Angola: The Power of Participatory Mapping in Understudied Landscapes

Remote sensing-based vegetation mapping approaches play a crucial role in guiding conservation efforts. However, these methods often rely on large-scale data which can lead to overlooking fine-scale environmental and socio-ecological dynamics, potentially undermining local livelihoods. This work explores the classification of vegetation based on local perceptions in the highlands of southeast Angola, emphasizing the limitations of remote-sensing-only based methods for mapping lived landscapes. This region, one of the most remote and isolated of Angola, harbors some of Africa’s best-preserved woodlands and plays a vital role in sustaining southern Africa’s water systems. The region is an ideal candidate for conservation interventions but, we argue here, local livelihoods must play a central role in shaping these strategies. This study employs a mixed-methods approach, conducting remote sensing analyses, participatory mapping, transect walks, and surveys in five rural villages in southeast Angola to incorporate local knowledge into maps. Our findings reveal that locals possess detailed ecological knowledge, identifying five woodland types and two grassland types based on tree density, species composition, fire regimes, and resource use. Vegetation types are multi-functional, meeting diverse subsistence needs. Integrating remote sensing data with participatory methods fosters a holistic understanding of the landscape and highlighting vegetation uses supports local land rights and promotes inclusive, people-centered conservation strategies.