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.
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.
the Creative Commons Attribution 4.0 License.
Mapping rangeland health indicators in eastern Africa from 2000 to 2022
Instituto de Estadística, Facultad de Ciencias Económicas y Administrativas, Universidad Austral de Chile, Valdivia, Chile
School of Integrative Plant Science, Soil and Crop Sciences Section, Cornell University, Ithaca, NY, USA
Steven W. Wilcox
Department of Applied Economics, Utah State University, Logan, UT, USA
Patrick E. Clark
Northwest Watershed Research Center, USDA Agricultural Research Service, Boise, ID, USA
Francesco P. Fava
Department of Environmental Science and Policy, Università Degli Studi Di Milano, Milan, Italy
Nathaniel D. Jensen
The Global Academy of Agriculture and Food Systems, University of Edinburgh, Edinburgh, Scotland
Njoki Kahiu
Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, USA
Chuan Liao
Department of Global Development, Cornell University, Ithaca, NY, USA
Benjamin Porter
Forest Ecosystem Monitoring Cooperative, University of Vermont, Burlington, VT, USA
School of Integrative Plant Science, Soil and Crop Sciences Section, Cornell University, Ithaca, NY, USA
Christopher B. Barrett
Charles H. Dyson School of Applied Economics and Management, Cornell University, Ithaca, NY, USA
Jeb E. Brooks School of Public Policy, Cornell University, Ithaca, NY, USA
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Cited
10 citations as recorded by crossref.
- From data to decisions: the potential of real-time precision technologies to enhance adaptive grazing management for livestock ranchers J. Derner et al. https://doi.org/10.2989/10220119.2025.2585814
- Biophysical Challenges to Pastoral Mobility in Northern Tanzania A. Treydte et al. https://doi.org/10.1016/j.rama.2025.11.004
- Spatiotemporal Patterns of Vegetation Coverage and Its Response to Land-Use Change in the Agro-Pastoral Ecotone of Inner Mongolia, China H. Liu et al. https://doi.org/10.3390/land14061202
- Climate rather than overgrazing explains most rangeland primary productivity change in Mongolia A. Purevjav et al. https://doi.org/10.1126/science.adn0005
- Assessment and Validation of FAPAR, a Satellite-Based Plant Health and Water Stress Indicator, over Uganda R. Ssembajwe et al. https://doi.org/10.3390/rs17203501
- Monitoring spatio-temporal change of rangeland vegetation in Bhutan to inform sustainable rangeland management K. Uddin et al. https://doi.org/10.1007/s44288-026-00434-4
- Detection of land degradation risk in Azerbaijan by combining fractional cover estimates based on DESIS data with multi-decadal Landsat NDVI trends S. Asam et al. https://doi.org/10.1080/01431161.2025.2536884
- Participatory assessment of rangeland conditions in selected agropastoral districts of the East Hararge Zone, Ethiopia H. Mohammed et al. https://doi.org/10.1016/j.jnc.2026.127356
- Evaluation of rangeland conditions through field survey and NDVI in semi-arid area of Dubluk district Southern Ethiopia J. Garbole et al. https://doi.org/10.1007/s44274-025-00485-3
- A comprehensive analysis of the use of modelling and remote sensing techniques for monitoring and managing rangelands R. Houinato et al. https://doi.org/10.1016/j.tfp.2025.101102
10 citations as recorded by crossref.
- From data to decisions: the potential of real-time precision technologies to enhance adaptive grazing management for livestock ranchers J. Derner et al. https://doi.org/10.2989/10220119.2025.2585814
- Biophysical Challenges to Pastoral Mobility in Northern Tanzania A. Treydte et al. https://doi.org/10.1016/j.rama.2025.11.004
- Spatiotemporal Patterns of Vegetation Coverage and Its Response to Land-Use Change in the Agro-Pastoral Ecotone of Inner Mongolia, China H. Liu et al. https://doi.org/10.3390/land14061202
- Climate rather than overgrazing explains most rangeland primary productivity change in Mongolia A. Purevjav et al. https://doi.org/10.1126/science.adn0005
- Assessment and Validation of FAPAR, a Satellite-Based Plant Health and Water Stress Indicator, over Uganda R. Ssembajwe et al. https://doi.org/10.3390/rs17203501
- Monitoring spatio-temporal change of rangeland vegetation in Bhutan to inform sustainable rangeland management K. Uddin et al. https://doi.org/10.1007/s44288-026-00434-4
- Detection of land degradation risk in Azerbaijan by combining fractional cover estimates based on DESIS data with multi-decadal Landsat NDVI trends S. Asam et al. https://doi.org/10.1080/01431161.2025.2536884
- Participatory assessment of rangeland conditions in selected agropastoral districts of the East Hararge Zone, Ethiopia H. Mohammed et al. https://doi.org/10.1016/j.jnc.2026.127356
- Evaluation of rangeland conditions through field survey and NDVI in semi-arid area of Dubluk district Southern Ethiopia J. Garbole et al. https://doi.org/10.1007/s44274-025-00485-3
- A comprehensive analysis of the use of modelling and remote sensing techniques for monitoring and managing rangelands R. Houinato et al. https://doi.org/10.1016/j.tfp.2025.101102
Saved (final revised paper)
Latest update: 21 Jul 2026
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.
This paper uses machine learning and linear unmixing to produce rangeland health indicators:...
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