Table · dataset · 2026
Dataset corresponding to "A Global Dataset of Forest Disturbance Regimes Derived from Satellite Biomass Observations"
Listed in Edmond
This dataset provides globally continuous, observationally constrained estimates of four forest Disturbance Regime Parameters (DRPs): disturbance rate (μ), gap-size distribution (α), disturbance severity (β), and background mortality (Kb).
Description
The parameters were inferred using a Random Forest inversion framework trained on more than 8 million synthetic forest simulations and applied to landscape-scale spatial features derived from satellite above-ground biomass observations and GPP constraints.
The dataset includes three biomass-based products: GlobBiomass 2010 , ESA CCI Biomass v7 2010, and ESA CCI Biomass v7 2005–2011 mean. The data are provided in two formats: - Tile-Level (CSV): Predictions for individual 25 × 25 km forest landscape tiles, including all 10 cross-validation fold predictions, ensemble means, and parameter-specific Dissimilarity Index (DIK) values. - Gridded Global (NetCDF): Corresponding 0.25° × 0.25° area-weighted global products containing mean DRP estimates and associated uncertainty and spatial-variability layers.
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These parameters characterize long-term, landscape-scale forest disturbance regimes rather than individual disturbance events, and provide a globally consistent dataset for large-scale disturbance analysis and potential integration with ecosystem and Earth system models. This dataset accompanies the study “A Global Dataset of Forest Disturbance Regimes Derived from Satellite Biomass Observations” by Wang et al.
Links
Where it is published
- Dataverse dataset page edmond.mpg.de/dataset.xhtml?persistentId=doi%3A10.17617%2F3.EF4QGR ↗
landing page · from edmond mpdl mpg de
- DOI doi.org/10.17617/3.ef4qgr ↗
DOI / persistent id · from edmond mpdl mpg de
Catalogue records · 1
- Dataverse API edmond.mpg.de/api/datasets/:persistentId/?persistentId=doi%3A10.17617%2F3.EF… ↗
metadata API · from edmond mpdl mpg de
Topics
- Stated by source
- Geosciences · Geosciences
- From keywords
- Astronomy & Astrophysics · Chemistry · Computer Science & AI · Computer Science & AI · Earth & Environmental Science · Earth & Environmental Science · Economics & Finance · Engineering · Humanities · Life Sciences · Life Sciences · Machine learning · Machine learning · Materials Science · Medicine & Health · Ocean & Atmospheric Science · Photogrammetry and remote sensing · Photogrammetry and remote sensing · Physics · Satellite remote sensing · Satellite remote sensing · Social Science
Provenance · 2 source records, 30 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Edmond | doi:10.17617/3.EF4QGR | 13 d ago | JSON v1 |
| Edmond | doi:10.17617/3.EF4QGR | 11 d ago | JSON v1 |
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|---|---|---|---|
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