Remote Sensing and Climate Data for Targeting Landscape Restoration in Africa
Tackling land degradation and restoring degraded landscapes require information on areas of priority intervention, since it is not economically and technically possible to manage all areas affected. Recent developments in data availability and improved computational power have enhanced our understan...
| Autores principales: | , , , , , , |
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| Formato: | Capítulo de libro |
| Lenguaje: | Inglés |
| Publicado: |
World Agroforestry Centre
2019
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/106885 |
| _version_ | 1855525825358594048 |
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| author | Tamene, Lulseged D. Le, Quang Bao Sileshi, Gudeta W. Aynekulu, Ermias Kizito, Fred Bossio, Deborah A. Vlek, Paul L.G. |
| author_browse | Aynekulu, Ermias Bossio, Deborah A. Kizito, Fred Le, Quang Bao Sileshi, Gudeta W. Tamene, Lulseged D. Vlek, Paul L.G. |
| author_facet | Tamene, Lulseged D. Le, Quang Bao Sileshi, Gudeta W. Aynekulu, Ermias Kizito, Fred Bossio, Deborah A. Vlek, Paul L.G. |
| author_sort | Tamene, Lulseged D. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Tackling land degradation and restoring degraded landscapes require information on areas of priority intervention, since it is not economically and technically possible to manage all areas affected. Recent developments in data availability and improved computational power have enhanced our understanding of the major regional drivers of land degradation and possible remedial measures at different scales. In this study, we have used land degradation hotspots, which were identified using satellite and climate data covering the period of 1982–2003 (Vlek et al. 2010). We then simulated the potentials of different management measures in tackling land degradation in Sub-Saharan Africa (SSA). Scenario analysis results show that about 14 million people can benefit from the application of sustainable land management (e.g., integrated soil fertility management, conservation agriculture, and soil and water conservation) techniques targeted to improve the productivity of croplands. Fallowing degraded areas and allowing them to recover (e.g., through exclosures and agroforestry) could improve land productivity. However, this intervention requires appropriate and improved methods that can accommodate the needs of about 8.7 million people who utilize those “marginal” areas for crop production or livestock grazing. This chapter presents the benefits of utilizing long-term satellite data to analyze the potentials of targeted land management and restoration measures for improving land productivity in SSA. This approach and framework can also be used to design suitable land-use planning for the restoration of degraded areas and to perform detailed cost-benefit and trade-off analysis of various interventions. |
| format | Book Chapter |
| id | CGSpace106885 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2019 |
| publishDateRange | 2019 |
| publishDateSort | 2019 |
| publisher | World Agroforestry Centre |
| publisherStr | World Agroforestry Centre |
| record_format | dspace |
| spelling | CGSpace1068852025-11-05T16:17:32Z Remote Sensing and Climate Data for Targeting Landscape Restoration in Africa Tamene, Lulseged D. Le, Quang Bao Sileshi, Gudeta W. Aynekulu, Ermias Kizito, Fred Bossio, Deborah A. Vlek, Paul L.G. land degradation ndvi rainfall restoration land management Tackling land degradation and restoring degraded landscapes require information on areas of priority intervention, since it is not economically and technically possible to manage all areas affected. Recent developments in data availability and improved computational power have enhanced our understanding of the major regional drivers of land degradation and possible remedial measures at different scales. In this study, we have used land degradation hotspots, which were identified using satellite and climate data covering the period of 1982–2003 (Vlek et al. 2010). We then simulated the potentials of different management measures in tackling land degradation in Sub-Saharan Africa (SSA). Scenario analysis results show that about 14 million people can benefit from the application of sustainable land management (e.g., integrated soil fertility management, conservation agriculture, and soil and water conservation) techniques targeted to improve the productivity of croplands. Fallowing degraded areas and allowing them to recover (e.g., through exclosures and agroforestry) could improve land productivity. However, this intervention requires appropriate and improved methods that can accommodate the needs of about 8.7 million people who utilize those “marginal” areas for crop production or livestock grazing. This chapter presents the benefits of utilizing long-term satellite data to analyze the potentials of targeted land management and restoration measures for improving land productivity in SSA. This approach and framework can also be used to design suitable land-use planning for the restoration of degraded areas and to perform detailed cost-benefit and trade-off analysis of various interventions. 2019 2020-02-04T20:55:48Z 2020-02-04T20:55:48Z Book Chapter https://hdl.handle.net/10568/106885 en Open Access application/pdf World Agroforestry Centre Tamene, Lulseged; Le, Quang Bao; Sileshi, Gudeta W.; Aynekulu, Ermias; Kizito, Fred; Bossio, Deborah & Vlek, Paul. (2019). Remote Sensing and Climate Data for Targeting Landscape Restoration in Africa. In Hadgu, K. M.; Bishaw, B.; Iiyama, M.; Birhane, E.; Negussie, A.; Davis, C. M.; Bernart, B. (Eds.). Climate-smart agriculture: enhancing resilient agricultural systems, landscapes, and livelihoods in Ethiopia and Beyond. Nairobi, Kenya: World Agroforestry (ICRAF). pp.231-241. |
| spellingShingle | land degradation ndvi rainfall restoration land management Tamene, Lulseged D. Le, Quang Bao Sileshi, Gudeta W. Aynekulu, Ermias Kizito, Fred Bossio, Deborah A. Vlek, Paul L.G. Remote Sensing and Climate Data for Targeting Landscape Restoration in Africa |
| title | Remote Sensing and Climate Data for Targeting Landscape Restoration in Africa |
| title_full | Remote Sensing and Climate Data for Targeting Landscape Restoration in Africa |
| title_fullStr | Remote Sensing and Climate Data for Targeting Landscape Restoration in Africa |
| title_full_unstemmed | Remote Sensing and Climate Data for Targeting Landscape Restoration in Africa |
| title_short | Remote Sensing and Climate Data for Targeting Landscape Restoration in Africa |
| title_sort | remote sensing and climate data for targeting landscape restoration in africa |
| topic | land degradation ndvi rainfall restoration land management |
| url | https://hdl.handle.net/10568/106885 |
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