Published April 1, 2026 | Version v2
Dataset Open

Advancing Ecosystem Monitoring: Global Annual Maps of Biophysical Vegetation Properties (LAIe, FAPAR, FCOVER) for 2019-2025

  • 1. Institute of Integrative Biology, Department of Environmental Systems Science, ETH Zurich, Switzerland
  • 2. Montana State University, Department of Land Resources and Environmental Sciences, Bozeman, MT, United States
  • 3. TETIS, INRAE, AgroParisTech, CIRAD, CNRS, Université Montpellier, Montpellier, France
  • 4. Department of Geography, King's College London, London, WC2R 2LS, United Kingdom
  • 5. Swiss Federal Research Institute WSL, Birmensdorf, 8903 Switzerland
  • 6. School of Science, Engineering & Environment, University of Salford, Manchester, M5 4WT, United Kingdom
  • 7. ACRI-ST, F-06904, Sophia-Antipolis, France
  • 8. Plants and Ecosystems (PLECO), Department of Biology, University of Antwerp, B-2610, Wilrijk, Belgium
  • 9. Biological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Kingdom of Saudi Arabia

Description

Subdataset: LAIe 2022 [mean]

Mean LAIe predictions for 2022 at 100m resolution. See base deposition for more information: 10.5281/zenodo.19366930

Files

00_laie_rtm.mlp.v02_mean_100m_s_20220101_20221231_go_epsg.4326_v03_preview.png

Additional details

Related works

Continues
Dataset: 10.5281/zenodo.19367252 (DOI)
Is continued by
Dataset: 10.5281/zenodo.19367551 (DOI)
Is part of
Dataset: 10.5281/zenodo.19366930 (DOI)

Funding

European Commission
OEMC - Open-Earth-Monitor Cyberinfrastructure 101059548