T. W. Crowther, Yale University
H. B. Glick, Yale University
K. R. Covey, Yale University
C. Bettigole, Yale University
D. S. Maynard, Yale University
S. M. Thomas, University of Helsinki
J. R. Smith, Yale University
G. Hintler, Yale University
M. C. Duguid, Yale University
G. Amatulli, Yale University
M.-N. Tuanmu, Yale University
W. Jetz, Yale University
C. Salas, Universidad de La Frontera
C. Stam, RedCastle Resources
D. Piotto, Universidade Federal do Sul da Bahia
R. Tavani, Food and Agriculture Organization of the United Nations
S. Green, University of Kent at Canterbury - U.K.
G. Bruce, Operation Wallacea
S. J. Williams, Molecular Imaging Research Center MIRCen/CEA
S. K. Wiser, Landcare Research
M. O. Huber, WSL, Swiss Federal Institute for Forest, Snow and Landscape Research
G. M. Hengeveld, Wageningen University & Research Centre
G.-J. Nabuurs, Wageningen University & Research Centre
E. Tikhonova, Russian Academy of Sciences
P. Borchardt, University of Hamburg
C.-F. Li, Masaryk University
L. W. Powrie, Kirstenbosch Research Centre
M. Fischer, University of Bern
A. Hemp, University of Bayreuth
J. Homeier, Georg August University of Göttingen
P. Cho, Lancaster University
A. C. Vibrans, Universidade Regional de Blumenau
P. M. Umunay, Yale University
S. Piao, Peking University
C. W. Rowe, Yale University
M. S. Ashton, Yale University
P. R. Crane, Yale University
M. A. Bradford, Yale University
This description pertains to the primary download. Details on revised (newer) versions of the datasets are listed below under Additional Files. -- Two global maps (raster files) of tree density. These maps highlight how the number of trees varies across the world. One map was generated using biome-level models of tree density, and applied at the biome scale. The other map was generated using ecoregion-level models of tree density, and applied at the ecoregion scale. For this reason, transitions between biomes or between ecoregions may be unrealistically harsh, but large-scale estimates are robust (see Crowther et al. 2015). At the outset, this study was intended to generate reliable estimates at broad spatial scales, which inherently comes at the cost of fine-scale precision. For this reason, country-scale (or larger) estimates are generally more robust than individual pixel-level estimates. These two maps initially appeared in Crowther et al. (2015), with the biome map being featured more prominently. As they are produced, updated versions of these datasets, as well as alternative formats, will be made available under Additional Files.
We collected over 420,000 ground-sources estimates of tree density from around the world. We then constructed linear regression models using vegetative, climatic, topographic, and anthropogenic variables to produce forest tree density estimates for all locations globally (see Crowther et al. 2015). All modeling was done in R. Mapping was done using R and ArcGIS 10.1.
Load the files into an appropriate geographic information system (GIS). For the primary download (ArcGIS geodatabase files), load the files into ArcGIS to view or export the data to other formats. Because these datasets are large and have a unique coordinate system that is not read by many GIS, we suggest loading them into an ArcGIS dataframe whose coordinate system matches that of the data (see File Format). For GeoTiff files available under Additional Files, load them into any compatible GIS or image management program.
Yale Climate and Energy Institute; British Ecological Society
DOI of Related Publication
Crowther, T. W., Glick, H. B., Covey, K. R., et al. (2015). Mapping tree density at a global scale. Nature, 525(7568), 201-205. Available online: 10.1038/nature14967
Creative Commons License
This work is licensed under a Creative Commons Attribution-No Derivative Works 4.0 International License.
Crowther, T., Glick, H., Covey, K.,
"Global tree density map" (2015).
Crowther_Nature_Files_Revision_01 contains tree density predictions for small islands that are not included in the data available through the primary Download button. These predictions were not taken into consideration in production of maps and figures presented in the official publication, with the exception of the values presented in Supplemental Table 2 (see Crowther et al. 2015). The file structure follows that of the original data.Crowther_Nature_Files_Revision_01.zip includes tree density predictions for small islands that are not included in the data available through the primary Download button. These predictions were not taken into consideration in production of maps and figures presented in the official publication, with the exception of the values presented in Supplemental Table 2 (see Crowther et al. 2015). The file structure follows that of the original data.
Crowther_Nature_Files_Revision_01_WGS84_GeoTiff.zip (1237665 kB)
Crowther_Nature_Files_Revision_01_WGS84_GeoTiff.zip contains Revision_01 of the biome-level model, but stored in WGS84 and GeoTiff format. This file was produced by reprojecting the original Goode Homolosine files to WGS84 using nearest neighbor resampling in ArcMap. All areal computations presented in the manuscript were computed using the Goode Homolosine projection. This means that comparable computations made with projected versions of this WGS84 data are likely to differ slightly as a product of the resampling. Included in this .zip file are the primary .tif and its visualization support files.