DOI: 10.5281/zenodo.18331917
title: Key Characteristics of Global DEMIX Tiles

description: This data set was created for section 2.4 of Guth and others (2025) to show how the test tiles in the latest DEMIX database (version 4) provide a representative sample of the earth’s diversity.  The figure below shows the distribution of percentage of the earth’s 1.5 million tiles, in 18 bins based on average slope and the percent of the tile that is barren.  Bins have between 0.13 and 20.01% of the total.  They highlight the question, if the test tile distribution should match the distribution on earth, or if the test tiles should include representative samples of all major environments, even less common ones.



 

The DEMIX tiles provide roughly 10x10 km sampling regions covering the entire earth.  The original tiles were based on geographic quadrangles, with the longitudinal spacing adjusted to keep the sizes relatively close to 100 km² (Guth and others, 2023; Bielski and others, 2024).  A later refinement bases the tiles on map tiles produced by national mapping agencies using projected coordinates (Guth and others, 2025).  The grids created for this data set use 0.1x0.1° tiles at all latitudes to simplify the grid data model, and are not intended to precisely match the DEMIX tiles.  They should provide a statistical sample for the approximately 1.5 million tiles that cover the earth.  For users that want a precise match, the various iterations of the DEMIX database have the tile characteristics for all of the test tiles used.

 






 



This dataset



DEMIX DBs





GIS model



Geotiff grid



CSV vector





Tile size



0.1x0.1°



Approximately 100 km²

·         Originally geographic

·         Now based on national DEM tiles





DEM source



Copernicus DSM



DTM derived from HRDEM





Landcover



GLC100 version 3, 2019, N70 to S56



Originally GLC100, now GLC10





 

The four grids in this dataset include characteristics of the terrain which most affect the computation of LSPs from DEMs.  There is also a graphic of each grid in PNG format.



Average tile slope in percent, computed from the Copernicus 1 arc second DSM.

 Landcover computed from 100 m pixels in the Copernicus GLC100 (Buchhorn and others, 2020).


o   Percent of tile barren (land cover codes 30,60,70)

o   Percent of tile forested

o   Percent of tile urban

 

Acknowledgments

·         Copernicus DEM © DLR e.V. 2010-2014 and © Airbus Defence and Space GmbH 2014-2018 provided under COPERNICUS by the European Union and ESA; all rights reserved.

·         GLC10 Land cover: © ESA WorldCover project / Contains modified Copernicus Sentinel data (2021) processed by ESA WorldCover consortium, provided free of charge, without restriction of use. For the full license information see the Creative Commons Attribution 4.0 International License.

·         GLC10 Land cover: As official product of the global component of the Copernicus Land Service, access to this land cover dataset is fully free and open to all users.

References

·         Bielski, C.; López-Vázquez, C.; Grohmann, C.H.; Guth. P.L.; Hawker, L.; Gesch, D.; Trevisani, S.; Herrera-Cruz, V.; Riazanoff, S.; Corseaux, A.; Reuter, H.; Strobl, P., 2024. Novel approach for ranking DEMs: Copernicus DEM improves one arc second open global topography. IEEE Transactions on Geoscience & Remote Sensing. vol. 62, pp. 1-22, 2024, Art no. 4503922, https://doi.org/10.1109/TGRS.2024.3368015

·         Marcel Buchhorn, Bruno Smets, Luc Bertels, Bert De Roo, Myroslava Lesiv, Nandin-Erdene Tsendbazar, Martin Herold, & Steffen Fritz. (2020). Copernicus Global Land Service: Land Cover 100m: collection 3: epoch 2019: Globe (V3.0.1) [Data set]. Zenodo https://doi.org/10.5281/zenodo.3939050

·         Guth, P.L., Peter Strobl, Kevin Gross, & Serge Riazanoff. (2023). DEMIX 10k Tile Data Set (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7504791

·         Guth, P.L.; and others 2025 (Trevisani, S.; Grohmann, C.H.; Lindsay, J.B.; Reuter, H.I. ) Benchmarking Elevation Plus Land Surface Parameters Finds FathomDEM and Copernicus DEM Win as Best Global DEMs. Remote Sens. 2025, 17, 3919. https://doi.org/10.3390/rs17233919

Main DEMIX database



Guth, P.L., 2023. DEMIX GIS Database Version 2 [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8062008

Guth, P. (2024). DEMIX GIS Database Version 3 [Data set]. Zenodo. https://doi.org/10.5281/zenodo.13331458 

Guth, P. (2025). DEMIX GIS Database Version 3.5 [Data set]. Zenodo. https://doi.org/10.5281/zenodo.17247343

Guth, P. (2025). DEMIX GIS Database Version 4 [Data set]. Zenodo. https://doi.org/10.5281/zenodo.17538186