Earth System Science Data
Earth System Science Data
Earth System Science Data
Articles | Volume 18, issue 8
Articles | Volume 18, issue 8
https://doi.org/10.5194/essd-18-5969-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-18-5969-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 8
Data description article
 | 
25 Aug 2026
Data description article |  | 25 Aug 2026

Geospatial micro-estimates of slum populations in 129 Global South countries using machine learning and public data

Dan Li, Laixiang Sun, Yang Yu, and Peipei Tian

Viewed

Total article views: 4,165 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
3,130 746 289 4,165 274 216 273
  • HTML: 3,130
  • PDF: 746
  • XML: 289
  • Total: 4,165
  • Supplement: 274
  • BibTeX: 216
  • EndNote: 273
Views and downloads (calculated since 28 May 2025)
Cumulative views and downloads (calculated since 28 May 2025)

Viewed (geographical distribution)

Total article views: 4,165 (including HTML, PDF, and XML) Thereof 4,065 with geography defined and 100 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved (final revised paper)

Latest update: 01 Nov 2026
Download
Short summary
We develop a generalized bottom-up framework for producing spatially explicit estimates of slum populations in data-sparse environments. The resulting dataset provides the first comprehensive inventory at an approximate spatial resolution of 6.72 km across 129 Global South countries. It addresses the underestimation in prior studies and supports national- and regional-scale assessments of urban sustainability and vulnerable populations, with potential applications for improving human well-being.
Read more
Share
Altmetrics
Final-revised paper
Preprint