Claude Tatuebu Tagne

Remote sensing (RS) techniques and Geographic Information Systems (GIS) for earth observation have significantly improved the ability to map and measure forest composition, estimate height and biomass, detect degradation and deforestation, implement land use planning, track land use changes as well as monitoring the implementation and respect of land development policies at a finer scale. Machine learning approaches further enhance these capabilities by integrating multiple data sources to produce improved maps of forest attributes and track changes over time. Recent advances in remote sensing techniques and artificial intelligence (AI) now enable detailed mapping and modelling of conservation areas especially the demarcation of High Valued Conservation Forest. National governments follow an administrative procedure for national map design, validation, and standardization. National governments together with the national mapping institutions select particular government officials, the private sector, civil society organizations, and foreign partners to produce national maps. On the other hand, scientists use a rigorous methodology that combines cutting-edge tools and peer review approaches. Even if some of the maps mentioned have not undergone the validation process by the various governments of the sub-region, they are widely used or referred to in international negotiations and discussions. Adopting innovative policies on mapping (Indonesia’s one map policy, Rwanda National land registry) and spatial data management (Geoportal for the Region, The INSPIRE Directive) will be very helpful in planning and conserving the Congo Basin. Non the less, Gabon, the DRC and Cameroon have made exceptions by producing and using renowned National Geoportal.

Land and resource use patterns in coastal areas play a key role in the resilience of ecosystems and populations to climate change. Knowing their spatiotemporal dynamics therefore constitutes a strategic tool to help decision-makers. Based on documentary research, geographic information system (GIS), image processing, and field work, this article maps land use on Manoka Island between 1986 and 2018 and identifies the drivers of change and avenues for intervention with a view to strengthening climate change mitigation. The results show a decrease of 4% in forest area on Manoka Island, representing an average of 112 ha of inland forest and 267 ha of mangrove converted between 1986 and 2018. This increases the degraded forest area by 268% (degraded mangrove and degraded inland forest) and exposes some camps to erosion and flooding. Reduction in forest area is mainly linked to the harvesting of fuelwood and the conversion of forests into farmland and residential areas. Settlements have increased in area from 15 ha in 1986 to 90.4 ha in 2018 to the detriment of natural spaces.