The Congo Basin rainforest, the second largest on Earth, covers more than 600 million ha. The rainforest stores up to 66 Pg of carbon and is a persistent carbon sink (0.34 Pg C yr-1). The African rainforests also contribute significantly to GDP through the forestry sector, with most foreign export directed to Europe. Despite this relevance, predictions regarding forest resilience under challenging climate scenarios remain uncertain, in part due to a lack of long-term data to provide the necessary climatological and ecological context for current research in the Congo Basin. Much of the necessary baseline information is available in historic paper archives from the colonial era, yet this data is practically inaccessible for contemporary research reliant on accessibility through digital data repositories.
The COBECORE project aimed to establish baseline measurements necessary for long-term (retrospective) ecological and climatological research through the recovery and valorisation of unexplored historical data collected in the Congo Basin by Belgian scientists during the colonial period. The project generated three main data streams through the completion of its four objectives: (1) data recovery of the historical climate record for the central Congo basin; (2) historic metrics of forest structure through digitization of aerial photographs; (3) data recovery of historic leaf traits from herbarium specimens; and (4) data integration and dissemination.
Through the development of a multi-faceted database, COBECORE contributed to the digital accessibility of the analog archives of the Institut National pour l’Etude Agronomique du Congo Belge (INEAC), in addition to extracting eco-physiologically relevant plant traits from historical herbarium specimens. The COBECORE project implemented state-of-the-art digitization techniques, including machine learning, citizen science and several European collaborations, resulting in practical insights for future digitization projects, outreach for secondary schools and public interest, and numerous publications in A1 scientific journals. The data recovered during COBECORE continues to inspire new research opportunities and remains a valuable reference for contemporary research.
This project (COBECORE, contract BR/175/A3/COBECORE - 584K EURO) was led by BlueGreen Labs partner Koen Hufkens as Principal Investigator in collaborations with partners at various Belgian research institutes and successfully completed in September 2022.
- Digitized all tabulated climate data stored in the Royal Archives (~75K scans)
- Transcribed a subset using a highly successful citizen science project (Jungle Weather)
- Extracted leaf traits using Machine Learning from herbarium specimen
- A spin-off Machine Learning for high-school students (KIKS)
- Recovered and valorized historical remote sensing data combining Structure-from-Motion and Machine Learning.
- All workflows and most data are openly available (if not upon request due to data volumes)
- Brönniman et al. 2019 - Unlocking pre-1850 instrumental meteorological records: A global inventory
- Hufkens et al. 2020 - Historical Aerial Surveys Map Long-Term Changes of Forest Cover and Structure in the Central Congo Basin
- Meeus et al. 2020 - From Leaf to Label : A Robust Automated Workflow for Stomata Detection
- Bauters et al. 2020 - Century‐long Apparent Decrease in IWUE with No Evidence of Progressive Nutrient Limitation in African Tropical Forests
- A browsable index of recovered Agricultural Research Archive resources
- The KIKS Machine Learning course for secondary school students using stomata data