Earth System Science Data
Earth System Science Data
Earth System Science Data
Articles | Volume 16, issue 11
Articles | Volume 16, issue 11
https://doi.org/10.5194/essd-16-5375-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-16-5375-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 16, issue 11
Data description paper
 | 
26 Nov 2024
Data description paper |  | 26 Nov 2024

Mapping rangeland health indicators in eastern Africa from 2000 to 2022

Gerardo E. Soto, Steven W. Wilcox, Patrick E. Clark, Francesco P. Fava, Nathaniel D. Jensen, Njoki Kahiu, Chuan Liao, Benjamin Porter, Ying Sun, and Christopher B. Barrett

Viewed

Total article views: 2,942 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,183 675 84 2,942 108 132
  • HTML: 2,183
  • PDF: 675
  • XML: 84
  • Total: 2,942
  • BibTeX: 108
  • EndNote: 132
Views and downloads (calculated since 20 Nov 2023)
Cumulative views and downloads (calculated since 20 Nov 2023)

Viewed (geographical distribution)

Total article views: 2,942 (including HTML, PDF, and XML) Thereof 2,902 with geography defined and 40 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 22 Nov 2025
Download
Short summary
This paper uses machine learning and linear unmixing to produce rangeland health indicators: Landsat time series of land cover classes and vegetation fractional cover of photosynthetic vegetation, non-photosynthetic vegetation, and bare ground in arid and semi-arid Kenya, Ethiopia, and Somalia. This represents the first multi-decadal Landsat-resolution dataset specifically designed for mapping and monitoring rangeland health in the arid and semi-arid rangelands of this portion of eastern Africa.
Read more
Share
Altmetrics
Final-revised paper
Preprint