Partenaires
Localisation
DR Congo
BUDGET
Période
CONTACT
If you would like more information about AFRO-CARDS, please contact: Professors Hans Verbeeck, Marijn Bauters or Félicien Meunier at: [email protected], [email protected], [email protected]
Aperçu du projet
The Congo Basin plays a pivotal role in the global carbon cycle. However, increasing human disturbance due to huge population expansion is generating large uncertainties in the regional carbon balance. This uncertainty mainly stems from a lack of understanding of forest regrowth trajectories.
The main objective of AFRO-CARDS is to improve understanding of the current and future carbon cycle of the Congo rainforests post-disturbance, with a specific focus on the long-term forest dynamics and recovery of carbon stocks and functional diversity following slash-and-burn agriculture. Especially in the context of increasing anthropogenic pressure, a better understanding of what drives the variability of forest regrowth after such disturbances is key. This will allow a significant reduction of the uncertainties in the projected changes of the regional carbon balance of rainforests in central Africa.
AFRO-CARDS will link ground-based and UAV carbon recovery quantification to satellite remote sensing in a unique reference multiscale forest chronosequence observatory in focused landscapes areas across the Congo Basin. The project will quantify and map forest degradation/regrowth across the entire Congo basin (satellite multi-sensor decametric time series).
This data and knowledge will be assimilated into a state-of-the-art land surface model to make more constrained projections of forest disturbance intensification and climate change scenarios.
Quantifying and mapping forest degradation/regrowth requires the development of advanced remote sensing methods, combining data from various remote sensing sensors and rich descriptions of calibration and validation sites. The scientific challenge lies in exploiting in a synergistic way the diversity of data types available today from remote sensing instruments in a consistent and relevant manner. This will be possible by focusing specifically on the post-disturbance forest regrowth in tropical moist forests and in-depth knowledge acquired on the ground, by developing dedicated data collection methodology through UAV (drone) and by taking advantage of the latest development in machine learning and artificial intelligence for upscaling.
Résultats attendus
- A state-of-the-art monitoring tool and products that assess landscape-level recovery dynamics across the basin;
- A new reference model for projecting the impacts of climate change and anthropogenic pressure on tropical forest functions.
Synergies avec le CBSI
Our project directly supports the CBSI Science and Capacity Plan on three core fronts:
1. Advancing Priority Science Themes
CBSI emphasises understanding ecosystem function, disturbance impacts, and climate resilience in the Congo Basin. Our project contributes directly to CBSI’s goals on carbon cycle science, climate-ecosystem feedbacks, and land-use change dynamics. It focuses on: (i) quantifying forest recovery trajectories after shifting cultivation, currently the dominant—and least monitored—driver of forest degradation in the Congo Basin; (ii) integrating field, UAV and multi-sensor satellite data into process-based ecosystem models to improve predictions of carbon storage and forest resilience under future climate and land-use scenarios.
2. Building Basin-Wide Monitoring Infrastructure
The CBSI plan calls for long-term, scalable monitoring systems with open data access. Our project delivers: (i) a network of high-resolution regrowth observatories across key ecological gradients; (ii) a basin-scale annual mapping system for post-disturbance forest recovery based on Sentinel, Planet, GEDI; (iii) open access products that can plug into national platforms.
3. Strengthening Local Scientific and Technical Capacity
In line with CBSI’s commitment to African-led research and training, we: (i) embed ERAIFT and Congolese PhD/MSc researchers at the core of the project, ensuring that capacity stays in the region and that results inform policy and restoration planning; (ii) train local partners in UAV forest monitoring, satellite analytics, and model-data fusion workflows; (iii) train at least 2 MSc students in drone and remote sensing work; (iv) Ensure data sovereignty and co-authorship from Central African scientists.
Partenaires
Financement
