- Dataset Availability
- 2020-01-01T00:00:00Z–2020-12-31T00:00:00Z
- Dataset Provider
- NASA ORNL DAAC at Oak Ridge National Laboratory
- Tags
Description
This dataset provides classes of global forests delineated by status/condition in 2020 at approximately 30m resolution. The data support generating Tier 1 estimates for Aboveground dry woody Biomass Density (AGBD) in natural forests in the 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories. Forest classes include primary, young secondary (<=20 years), and old secondary forests (>20 years). Classification was based on a Boolean combination of a suite of existing Earth Observation (EO) products of forest tree cover, height, age, and land use classification layers representing years 2000 to 2020. This forest status/condition classification prioritizes the reduction of potential errors of commission in the delineations by minimizing the inclusion of ambiguous pixels. Hence, it provides a conservative estimate of global forest area, identifying approximately 3.26 billion ha of forests worldwide.
Quality Assessment
These data provide a comprehensive compilation of the latest published datasets on forest conditions, but the nonexistence of any independent sample of global data that would enable the validation of these delineations is a constraint. Hence, the global forest status/condition classification has not been validated.
Data Acquisition, Materials, and Methods
The forest status/condition classification is created by conducting a Boolean analysis of a suite of existing datasets (see Table 1, Hunka et al., 2024), including satellite-derived forest tree cover, height, age, and land use classification layers. In this approach, layers that identify a potential forest status/condition class (e.g. primary forests) are merged, and layers that identify sources of disagreement (e.g. presence of plantations or deforestation detected in the delineated primary forests) are used to remove areas of potential commission errors.
The primary forest class is established using datasets identifying intact/primary forests, with a high forest integrity index, the presence of tree cover and forest heights ≥5 m and no known forest loss events, planted forests or plantations.
The young secondary forest class captures pixels that had changes in forest height or cover between 2000 and 2020, excluding planted forests and plantations. These forests were identified by heights ≥5 m in 2020 and either (a) heights <5 m in 2000 or (b) heights ≥5 m in 2000 but having experienced tree cover loss after 2000.
The old secondary forest class captures the remainder of pixels with forests after excluding the primary and young secondary forest classes. These pixels had forest heights ≥5 m in both 2000 and 2020 with no tree cover loss nor forest disturbances detected after 2000, nor any planted forests or plantations.
Bands
Pixel Size
30 meters
Bands
| Name | Pixel Size | Description |
|---|---|---|
classification |
meters | Forest Type |
classification Class Table
| Value | Color | Description |
|---|---|---|
| 1 | #00ff00 | Primary Forest |
| 2 | #ff0000 | Young Secondary Forest |
| 3 | #6666ff | Old Secondary Forest |
Terms of Use
Terms of Use
This dataset is in the public domain and is available without restriction on use and distribution. See NASA's Earth Science Data & Information Policy for additional information.
Citations
Hunka, N., L. Duncanson, J. Armston, R.O. Dubayah, S.P. Healey, M. Santoro, P. May, A. Araza, C. Bourgain, P.M. Montesano, C.S. Neigh, H. Grantham, V. Potapov, S. Turubanova, A. Tyukavina, J. Richter, N. Harris, M. Urbazaev, A. Pascual, D. Requena Suarez, M. Herold, B. Poulter, S.N. Wilson, G. Grassi, S. Federici, M.J. Sanz Sanchez, and J. Melo. 2024. Classification of Global Forests for IPCC Aboveground Biomass Tier 1 Estimates, 2020. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/2345
Hunka, N., Duncanson, L., Armston, J. et al. Intergovernmental Panel on Climate Change (IPCC) Tier 1 forest biomass estimates from Earth Observation. Sci Data 11, 1127 (2024). https://doi.org/10.1038/s41597-024-03930-9 doi:10.1038/s41597-024-03930-9
DOIs
Explore with Earth Engine
Code Editor (JavaScript)
var dataset = ee.ImageCollection('NASA/ORNL/global_forest_classification_2020/V1'); var visualization = { bands: ['classification'], min: 1.0, max: 3.0, palette: ['00ff00', 'ff0000', '6666ff'], }; Map.setCenter(-53, -5, 6); Map.addLayer(dataset, visualization, 'Forest Type');