Can artificial intelligence and space technology transform livestock insurance and rangeland management?
cg.authorship.types | CGIAR single centre | en |
cg.contributor.affiliation | International Livestock Research Institute | en |
cg.contributor.crp | Climate Change, Agriculture and Food Security | |
cg.contributor.donor | CGIAR Trust Fund | en |
cg.contributor.initiative | Livestock and Climate | |
cg.coverage.country | Kenya | |
cg.coverage.iso3166-alpha2 | KE | |
cg.coverage.region | Africa | |
cg.creator.identifier | Ambica Paliwal: 0000-0003-3207-5042 | en |
cg.howPublished | Grey Literature | en |
cg.identifier.url | https://www.ilri.org/news/can-artificial-intelligence-and-space-technology-transform-livestock-insurance-and-rangeland#:~:text=Can%20artificial%20intelligence%20and%20space%20technology%20transform%20livestock%20insurance%20and%20rangeland%20management%3F,-New%20science&text=A%20new%20study%20shows%20that,affected%20by%20invasive%20plant%20species | en |
cg.place | Kenya | en |
cg.reviewStatus | Internal Review | en |
cg.subject.actionArea | Systems Transformation | |
cg.subject.impactArea | Climate adaptation and mitigation | |
cg.subject.impactPlatform | Environmental Health and Biodiversity | |
cg.subject.sdg | SDG 13 - Climate action | en |
dc.contributor.author | Onyango, Polycarp Otieno | en |
dc.contributor.author | Paliwal, Ambica | en |
dc.date.accessioned | 2025-01-14T14:59:07Z | en |
dc.date.available | 2025-01-14T14:59:07Z | en |
dc.identifier.uri | https://hdl.handle.net/10568/168973 | |
dc.title | Can artificial intelligence and space technology transform livestock insurance and rangeland management? | en |
dcterms.abstract | A new study shows that artificial intelligence (AI) could improve the accuracy of index-based livestock insurance (IBLI) satellite assessments in regions affected by invasive plant species. IBLI provides coverage for livestock keepers against drought, with payouts triggered when a specific region reaches a predetermined drought threshold. This threshold is calculated based on vegetation and forage scarcity, which is monitored using satellite imagery. Whereas traditional field surveys are effective for assessing forage conditions, they are often time-consuming and costly. As a result, there has been a significant shift towards using satellite remote sensing to monitor vegetation and forage conditions more efficiently. However, invasive plants species which are resistant to drought and which outcompete local plants can make monitoring less clear. | en |
dcterms.accessRights | Open Access | |
dcterms.audience | Development Practitioners | en |
dcterms.audience | Academics | en |
dcterms.audience | CGIAR | en |
dcterms.bibliographicCitation | Onyango, Polycarp., Paliwal Ambica. 2024. Can artificial intelligence and space technology transform livestock insurance and rangeland management? Blogpost. ILRI. 2024 | en |
dcterms.issued | 2024-11-24 | en |
dcterms.language | en | |
dcterms.license | CC-BY-NC-4.0 | |
dcterms.publisher | International Livestock Research Institute | en |
dcterms.subject | climate change adaptation | en |
dcterms.type | Blog Post |
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