Forest carbon science has long relied on canopy-surface metrics, and these remain fundamental. Spaceborne LiDAR (GEDI, ICESat-2) now adds a new dimension: for the first time, we can quantify how vertical forest structure shapes carbon dynamics at global scale. I develop the open-source data infrastructure (gediDB, icesat2db, alsdb) to make this possible, and use it to understand how forest age, disturbance, and 3D structure drive the terrestrial carbon cycle.
Professional Experience
2023-Present
Senior Researcher
GFZ Helmholtz Centre Potsdam, Germany
Leading research on large-scale land process monitoring using remote sensing and machine learning. Developed open-source data curation infrastructure including gediDB (GEDI data ingestion and standardization) and the EO Forest STAC catalog (STAC-based unified metadata and cloud-native access layer for heterogeneous forest EO datasets). Contributor to Helmholtz Imaging CONNECT; coordinating across international projects including NextGenCarbon, FORWARDS, and OpenEarthMonitor.
2022-2023
Lead Data Scientist, Nature-based Solutions
South Pole, The Netherlands
Developed and integrated data-driven models into digital MRV systems for nature-based solution projects globally. Led a cross-functional team delivering production-grade AI pipelines for carbon monitoring.
2019-2022
Postdoctoral Researcher
Max Planck Institute for Biogeochemistry, Germany
Integrated long-term above-ground biomass time-series into carbon cycle modeling frameworks. Co-developed the FLUXCOM upscaling framework and contributed to the FluxnetEO dataset pipeline.
2013-2014
Consultant — REDD+ MRV & Carbon Markets
GIZ GmbH · Ecosystem Marketplace, France
Developed recommendations to align GIZ REDD+ MRV activities with UNFCCC modalities; contributed to State of the Voluntary Carbon Markets and Forest Markets reports.
2012
Research Intern
Environmental Defense Fund, United States
Researched soil carbon sequestration offset policy design and implementation strategies.
2011
Project Manager
Global Green Carbon, Nicaragua
Implemented reforestation/afforestation carbon offset projects using forestry and agroforestry systems.
Software & Datasets
2025
gediDB
Toolbox for processing and providing GEDI L2A-B and L4A-C LiDAR data at scale. Published in Journal of Open Source Software.
doi.org/10.21105/joss.08593
2025
EO Forest STAC Catalog
STAC-based unified metadata and cloud-native access layer for heterogeneous forest EO datasets hosted on GFZ S3/Ceph.
simonbesnard1.github.io/eoforeststac
2026
icesat2DB
Toolbox for processing and managing ICESat-2 ATL08 canopy height data at scale, with TileDB integration for scalable storage and querying.
icesat2db.readthedocs.io
2026
alsDB
Python package for ingesting, storing and processing Airborne Laser Scanning (ALS/LiDAR) point clouds at scale.
alsdb.readthedocs.io
2024
GAMI Dataset
Global Age Mapping Integration - harmonized global forest age dataset. GFZ Data Services.
doi.org/10.5880/GFZ.1.4.2023.006
2021
MPI-BGC Forest Age Datasets
Global forest age datasets underpinning carbon cycle modeling at the Max Planck Institute for Biogeochemistry.
doi.org/10.17871/ForestAgeBGI.2021
Selected Publications
2025
Besnard, S., et al. Natural disturbances increasingly affect Europe’s most mature and carbon-rich forests. In review, Biogeosciences. doi.org/10.5194/egusphere-2025-6288
2025
Besnard, S., et al. Global covariation of forest age transitions with the net carbon balance. Nature Ecology & Evolution. doi.org/10.1038/s41559-025-02821-5
2024
Ciais, P., Yao, Y., Besnard, S., et al. The global carbon balance of forests based on flux towers and forest age data. In review, Nature Geoscience. doi.org/10.21203/rs.3.rs-5183310/v1
2023
Fan, N., Santoro, M., Besnard, S., et al. Implications of the steady-state assumption for global vegetation carbon turnover. Environmental Research Letters. doi.org/10.1088/1748-9326/acfb22
2023
Yang, H., Ciais, P., Besnard, S., et al. Global increase in biomass carbon stock dominated by growth of northern young forests. Nature Geoscience. doi.org/10.1038/s41561-023-01274-4
2022
Santoro, M., Cartus, O., Besnard, S., et al. Global estimation of above-ground biomass from spaceborne C-band scatterometer observations aided by LiDAR. Remote Sensing of Environment. doi.org/10.1016/j.rse.2022.113114
2021
Walther, S., Besnard, S., et al. A view from space on global flux towers by MODIS and Landsat: The FluxnetEO dataset. Biogeosciences. doi.org/10.5194/bg-2021-314
2021
Besnard, S., et al. Global sensitivities of forest carbon changes to environmental conditions. Global Change Biology. doi.org/10.1111/gcb.15877
2021
Besnard, S., et al. Mapping global forest age from forest inventories, biomass and climate data. Earth System Science Data. doi.org/10.5194/essd-2021-77
2021
Kraft, B., Besnard, S., & Koirala, S. Emulating Ecological Memory with Recurrent Neural Networks. Deep Learning for the Earth Sciences, Wiley & Sons. doi.org/10.1002/9781119646181.ch18
2019
Jung, M., et al. (incl. Besnard, S.) Scaling carbon fluxes from eddy covariance sites to globe: the FLUXCOM approach. Biogeosciences. doi.org/10.5194/bg-2019-368
2019
Besnard, S., et al. Memory effects of climate and vegetation affecting net ecosystem CO₂ fluxes in global forests. PLoS ONE 14(2). doi.org/10.1371/journal.pone.0211510
2018
Besnard, S., et al. Quantifying the effect of forest age in annual net forest carbon balance. Environmental Research Letters 13(12). doi.org/10.1088/1748-9326/aaeaeb
2018
Reichstein, M., Besnard, S., et al. Modelling Land-surface Time-Series with Recurrent Neural Nets. IGARSS 2018. doi.org/10.1109/IGARSS.2018.8518007
References
Dr. Nuno Carvalhais
Max Planck Institute for Biogeochemistry, Germany
ncarval@bgc-jena.mpg.de
Prof. Dr. Markus Reichstein
Max Planck Institute for Biogeochemistry, Germany
mreichstein@bgc-jena.mpg.de
Prof. Dr. Martin Herold
GFZ Helmholtz Centre Potsdam, Germany
herold@gfz.de
Dr. Philippe Ciais
Laboratoire des Sciences du Climat et de l'Environnement, France
philippe.ciais@lsce.ipsl.fr