Development and adaptation of RIICE tool for Cote d'Ivoire

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cg.contributor.affiliationInternational Rice Research Instituteen
cg.contributor.affiliationAfrica Rice Centeren
cg.contributor.affiliationSarmapen
cg.contributor.affiliationAlliance Bioversity CIATen
cg.contributor.donorWorld Banken
cg.coverage.countryCôte d'Ivoireen
cg.coverage.iso3166-alpha2CIen
cg.creator.identifierElliott Dossou-Yovo: 0000-0002-3565-8879en
dc.contributor.authorMathieu, Renauden
dc.contributor.authorDossou-Yoyo, Eliotten
dc.contributor.authorHolecz, Franciscoen
dc.contributor.authorMurusegan, Deiveeganen
dc.contributor.authorQuicho, Emmaen
dc.contributor.authorSatapathy, Sushreeen
dc.contributor.authorAkpoffo, Mariusen
dc.contributor.authorGatti, Lucaen
dc.contributor.authorOuedraogo, Mathieuen
dc.date.accessioned2025-02-17T23:59:53Zen
dc.date.available2025-02-17T23:59:53Zen
dc.identifier.urihttps://hdl.handle.net/10568/173138
dc.titleDevelopment and adaptation of RIICE tool for Cote d'Ivoireen
dcterms.abstractThis report presents the development and adaptation of the RIICE (Remote sensing-based Information and Insurance for Crops in Emerging Economies) tool for Côte d'Ivoire, carried out under the auspices of the Regional Integrated Initiative of West and Central Africa in collaboration with the Accelerating Impacts of CGIAR Climate Research for Africa (AICCRA) project. The development and validation of the RIICE tool aims to enhance rice monitoring and yield estimation through the integration of remote sensing technologies, geospatial modeling, and field validation. Key activities conducted in 2024 included the generation of a rice baseline and ecosystem map, seasonal rice area estimation for the 2023 main wet season, and the assessment of Leaf Area Index (LAI) and yield estimations using an upgraded ORYZA crop growth model. The study leveraged multi-source remote sensing data, including Sentinel-1, Sentinel-2, PlanetScope, and SAOCOM, to improve the accuracy of rice area detection and yield predictions. Field experiments were conducted to calibrate and validate crop models, focusing on dominant rice varieties and their response to different fertilizer applications in irrigated ecosystems. Findings indicate that the RIICE tool effectively identifies rice-growing areas with an 89.5% accuracy rate and provides reliable yield estimates ranging from 2.5 to 5.9 t/ha, aligning well with observed field data. The integration of climate, soil, and agronomic data enables improved decision-making for policymakers, researchers, and farmers. The study highlights the potential for expanding RIICE applications with L-band remote sensing (NISAR mission, 2025) and continued field validation to enhance monitoring accuracy. The results underscore the RIICE tool’s value in strengthening climate resilience, optimizing resource use, and improving rice production planning in Côte d'Ivoire. Further upscaling and refinement of the tool will contribute to data-driven agricultural management and climate adaptation efforts in West Africa.en
dcterms.accessRightsOpen Accessen
dcterms.bibliographicCitationMathieu R. Dossou-Yovo E. Holecz F. Murusegan D. Quicho E. Satapathy S. Akpoffo M. Gatti L Ouedraogo L. 2024. Development and adaptation of RIICE tool for Cote d'Ivoire. AICCRA Report. Accelerating Impacts of CGIAR Climate Research for Africa (AICCRA).en
dcterms.extent22 p.en
dcterms.issued2024-12en
dcterms.languageenen
dcterms.licenseCC-BY-ND-4.0en
dcterms.publisherAccelerating Impacts of CGIAR Climate Research for Africaen
dcterms.subjectmonitoringen
dcterms.subjectyieldsen
dcterms.subjectclimate change impactsen
dcterms.subjectplanningen
dcterms.typeReporten

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