Data to "Global to regional ecozone classifications from multivariate clustering models"
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Data and code to Michael Kempf* (2026) Global to regional ecozone classifications from multivariate clustering models Ecological Informatics Corresponding author: mk2145@cam.ac.uk Department of Geography, University of Cambridge, Cambridge, UK ORCID: 0000-0002-9474-4670 ### This code produces global ecozones using k-means cluster analysis and Gaussian Mixture Models (GMM).All data underlying the code is freely available from the internet. Description: Kempf Ecozone Code: is the code to reproduce the analysis, partially based on the data provided here and/or on the data freely available from the cited sources. dem_5km.tif -> is a Digital Elevation Model of the globe with 5 km resolution and with EPSG:8857 code (meter) mask.7z -> is a zipped shapefile of the study area mask (global landmass) CHELSA.7z: CMI_mean_1980_2018_4326.tif -> mean raster of the Climatic Water Balance /Climatic Moisture Index from CHELSA in EPSG4326 CMI_mean_1980_2018_8857.tif -> mean raster of the Climatic Water Balance /Climatic Moisture Index from CHELSA in EPSG8857 TAS_mean_1980_2018_4326.tif -> mean raster of the average temperature from CHELSA in EPSG4326 (degree) TAS_mean_1980_2018_8857.tif -> mean raster of the average temperature from CHELSA in EPSG8857 (meter) Kempf_Ecozones_Kmeans/GMM: the final Ecozone cluster results of both analyses Data source: DEM downloaded from: https://dap.ceda.ac.uk/bodc/gebco/global/gebco_2025/sub_ice_topography_bathymetry/netcdf/gebco_2025_sub_ice_topo.zip?download=1(last accessed 9th Feb 2026) Get temperature and CMI from CHELSA (Karger et al 2017; 2021). https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fchelsav2%2F&prefix=%2F (last accessed 15th May 2026). MODIS NDVI (code to bulk download ALL single tiles is attached to this repository) download MODIS data from here after registration:https://lpdaac.usgs.gov/products/mod13a3v061/MOD13A3 v061 (Didan 2021) (last accessed 15th May 2026) References: Danielson, J.J., and Gesch, D.B.(2011) Global multi-resolution terrain elevation data 2010 (GMTED2010): U.S. Geo-logical Survey Open-File Report 2011–1073, 26 p. https://doi.org/10.3133/ofr20111073 Didan, K. (2021). MODIS/Terra Vegetation Indices Monthly L3 Global 1km SIN Grid V061 [Data set]. NASA Land Processes Distributed Active Archive Center. https://doi.org/10.5067/MODIS/MOD13A3.061 Date Accessed: 2026-05-15 Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann,N.E., Linder, H.P. & Kessler, M. (2017) Climatologies at high resolution for the earth’sland surface areas. Scientific Data 4, 170122. https://doi.org/10.1038/sdata.2017.122Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann,N.E., Linder, H.P. & Kessler, M. (2021) Climatologies at high resolution for the earth’sland surface areas. EnviDat. https://doi.org/ 10.16904/envidat.228.v2.1
