Combining satellite and field data reveals Congo's forest types structure, functioning and composition

Picard Juliette, Nungi-Pambu Maïalicah, Barbier Nicolas, Cornu Guillaume, Couteron Pierre, Forni Eric, Gibbon Gwili, Lim Felix, Ploton Pierre, Pouteau Robin, Tresson Paul, Van Loon Tom, Viennois Gaëlle, Rejou-Mechain Maxime. 2024. Combining satellite and field data reveals Congo's forest types structure, functioning and composition. Remote Sensing in Ecology and Conservation, 21 p.

Résumé : Tropical moist forests are not the homogeneous green carpet often illustrated in maps or considered by global models. They harbour a complex mixture of forest types organized at different spatial scales that can now be more accurately mapped thanks to remote sensing products and artificial intelligence. In this study, we built a large-scale vegetation map of the North of Congo and assessed the environmental drivers of the main forest types, their forest structure, their floristic and functional compositions and their faunistic composition. To build the map, we used Sentinel-2 satellite images and recent deep learning architec- tures. We tested the effect of topographically determined water availability on vegetation type distribution by linking the map with a water drainage depth proxy (HAND, height above the nearest drainage index). We also described vegetation type structure and composition (floristic, functional and associated fauna) by linking the map with data from large inventories and derived from satellite images. We found that water drainage depth is a major driver of forest type distribution and that the different forest types are characterized by differ- ent structure, composition and functions, bringing new insights about their ori- gins and successional dynamics. We discuss not only the crucial role of soil–water depth, but also the importance of consistently reproducing such maps through time to develop an accurate monitoring of tropical forest types and functions, and we provide insights on peculiar forest types (Marantaceae forests and monodominant Gilbertiodendron forests) on which future studies should focus more. Under the current context of global change, expected to trigger major forest structural and compositional changes in the tropics, an appropriate monitoring strategy of the spatio-temporal dynamics of forest types and their associated floristic and faunistic composition would considerably help anticipate detrimental shifts.

Mots-clés Agrovoc : forêt tropicale, composition botanique, télédétection, forêt, intelligence artificielle, aménagement forestier, cartographie, port artificiel, Marantaceae, déboisement, inventaire forestier, végétation, faune

Mots-clés géographiques Agrovoc : Congo, Afrique centrale

Mots-clés libres : Deep Learning, North Congo, Satellite data, Tropical forest, Vegetation map, Water drainage dept

Agences de financement hors UE : Agence Nationale de la Recherche

Projets sur financement : (FRA) Etats stables dégradés en forêts tropicales

Auteurs et affiliations

• Picard Juliette, IRD (FRA) - auteur correspondant
• Nungi-Pambu Maïalicah, INRAE (FRA)
• Barbier Nicolas, IRD (FRA)
• Cornu Guillaume, CIRAD-ES-UPR Forêts et sociétés (FRA) ORCID: 0000-0002-7523-5176
• Couteron Pierre, IRD (FRA)
• Forni Eric, CIRAD-ES-UPR Forêts et sociétés (COG)
• Gibbon Gwili, Odzala-Kokoua National Park (COG)
• Lim Felix, Royal Botanic Gardens (GBR)
• Ploton Pierre, IRD (FRA)
• Pouteau Robin, IRD (FRA)
• Tresson Paul, CIRAD-BIOS-UMR AMAP (FRA)
• Van Loon Tom, Interholco (CHE)
• Viennois Gaëlle, CNRS (FRA)
• Rejou-Mechain Maxime, IRD (FRA)

Source : Cirad-Agritrop (https://agritrop.cirad.fr/611785/)

Métriques

[ Page générée et mise en cache le 2025-01-29 ]