Remote Sensing and Climate Data for Targeting Landscape Restoration in Africa

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cg.contributor.affiliationInternational Center for Tropical Agricultureen
cg.contributor.affiliationETH Zürichen
cg.contributor.affiliationUniversity of Bonnen
cg.contributor.affiliationWorld Agroforestry Centreen
cg.coverage.countryKenya
cg.coverage.iso3166-alpha2KE
cg.coverage.regionAfrica
cg.coverage.regionEastern Africa
cg.coverage.subregionNairobi
cg.creator.identifierLulseged Tamene: 0000-0002-4846-2330en
cg.creator.identifierFred Kizito: 0000-0002-7488-2582en
cg.isbn978-9966-108-24-1en
cg.placeNairobi, Kenyaen
dc.contributor.authorTamene, Lulseged D.en
dc.contributor.authorLe, Quang Baoen
dc.contributor.authorSileshi, Gudeta W.en
dc.contributor.authorAynekulu, Ermiasen
dc.contributor.authorKizito, Freden
dc.contributor.authorBossio, Deborah A.en
dc.contributor.authorVlek, Paul L.G.en
dc.date.accessioned2020-02-04T20:55:48Zen
dc.date.available2020-02-04T20:55:48Zen
dc.identifier.urihttps://hdl.handle.net/10568/106885
dc.titleRemote Sensing and Climate Data for Targeting Landscape Restoration in Africaen
dcterms.abstractTackling 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.en
dcterms.accessRightsOpen Access
dcterms.bibliographicCitationTamene, 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.en
dcterms.extent231-241 pen
dcterms.issued2019en
dcterms.languageen
dcterms.licenseCC-BY-4.0
dcterms.publisherWorld Agroforestry Centreen
dcterms.subjectland degradationen
dcterms.subjectndvien
dcterms.subjectrainfallen
dcterms.subjectrestorationen
dcterms.subjectland managementen
dcterms.typeBook Chapter

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