AFRO-CARDS - African Forest RecOvery and CArbon Dynamics monitoring through Remote Sensing

Context and objectives

The Congo Basin plays a pivotal role in the global carbon cycle. However, increasing human disturbance due to the 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.

Project outcome

Expected scientific results

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.
AFRO-CARDS will quantify and map forest degradation/regrowth across the entire Congo basin (satellite multi-sensor decametric time series).
AFRO-CARDS will assimilate this data and knowledge into a state-of-the-art land surface model to make more constrained projections of forest disturbance intensification and climate change scenarios.
Each specific objective requires the development of advanced methods. In particular, 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.

Expected products and services

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.