Published April 30, 2025 | Version 1.0
Dataset Open

Geomorphic Distribution Modeling of Desert Pavements: Towards a Global Desert Pavement Potential Index

  • 1. ROR icon Friedrich Schiller University Jena
  • 2. Freie Universität Berlin
  • 3. ROR icon University of Göttingen
  • 4. ROR icon University of Giessen

Description

Desert pavements, characterized by a stone layer over fine eolian materials, are key geomorphological features in arid regions and play a critical role in the global dust cycle. Despite their importance, quantitative evidence regarding their global distribution remains limited. This digital object contains raster files and R scripts providing a preliminary assessment of desert pavement distribution using a GIS-based multiple-criteria decision analysis (GIS–MCDA) framework. Key environmental factors, including climate, topography, vegetation, soil texture, and anthropogenic disturbance, were incorporated into a global favorability index at a 1 km × 1 km resolution. Validation against 20 documented desert-pavement research sites revealed a significant association with high index values, with 15% of sites exhibiting an index ≥0.90 and 80% ≥0.75. The model estimates that up to 25.7 million km², or 19.0% of the Earth’s land surface, holds potential for desert pavements. These results provide a foundation for future studies, emphasizing the need for localized, high-resolution research and the integration of geomorphometric and remote-sensing techniques with machine-learning models. This initial global assessment underscores the utility of GIS–MCDA in geomorphic distribution modeling and highlights the importance of refining global environmental datasets for arid landscapes.

Table of contents

Files:

  • dpindex_mod.tif: Main results file with global desert pavement potential index (DPPI); areas with DPPI < 0.75 have been set to zero, and terrestrial no-data regions filled with 0.
  • dpindex_raw.tif: Raw output of index calculation, with values ranging from 0 to 1 and possible small gaps.
  • *_index.tif: Intermediate results of subindex calculations.
  • *.R: R scripts used to process the raw data, calculate subindices, combine them into the final index, generate statistics and plot maps for the associated paper.

The methodology of this analysis is described in the paper by Brenning et al. (2025), https://zenodo.org/records/15014982, where additional results and maps can also be found.

Information on raw input data (not provided due to size and copyright restrictions) is available in the 01_subindex_calculation.R script file.

Files

barren_index.tif

Files (631.9 MB)

Name Size Download all
md5:cd23022d0ccf75ee27b1a40dc37b5d48
9.7 kB Download
md5:ca7d160ac19283857f0a957c780a94d7
2.5 kB Download
md5:4f7cf2852b1c5f198ae38ef8f27ab47f
275 Bytes Download
md5:db00aa04e30ac55375ce1fada5746e88
2.0 kB Download
md5:47a08cb838185946765a82ee13228581
3.1 kB Download
md5:d6702decb91af91eef761e2ad3ea1641
3.6 kB Download
md5:6a97ba07e3bb17c20d63db086e2dacc9
20.3 MB Preview Download
md5:b5b1f827e697233167a9ebcf3f99f888
69.1 MB Preview Download
md5:d32b461e8d5759e7037ef0b404d7e583
2.8 kB Download
md5:3b14ca4a12880c44eddac37e8aec4846
52.1 MB Preview Download
md5:165aa113fdba63b84ed5cbf02a8fe480
124.4 MB Preview Download
md5:e4ab59570b1b1d44e09d2f1fb73eb5fb
64.2 MB Preview Download
md5:253a442dd77d6e623fe3ed91557b0f1c
49.0 MB Preview Download
md5:a8c12d72ab72d7d859dc33e1e33ece44
43.4 MB Preview Download
md5:88dec9314926817ce14ec8e1e46dc5fe
60.5 MB Preview Download
md5:76bbc6fbf801232419bbd1b6ed30ba24
63.2 MB Preview Download
md5:7204c2daeb94cfb612f59427a1a07cfa
45.1 MB Preview Download
md5:f5deb1eeea3cdaaffcd0ee292b4fcae4
2.4 kB Download
md5:3b7b36f0b111bca653dd9f15c6071754
40.5 MB Preview Download

Additional details

Related works

Is supplement to
Conference paper: 10.5281/zenodo.15014981 (DOI)

Dates

Submitted
2025-04-30

Software

Programming language
R

References

  • Brenning, A., Güldner, L., Schepanski, K., Dietze, M., & Fuchs, M. (2025). Geomorphic Distribution Modeling of Desert Pavements: Towards a Global Assessment. Geomorphometry 2025, Perugia, Italy. https://doi.org/10.5281/zenodo.15014982