ECOSat (Estimation of carbon offsets with satellites) - Final report

cg.contributor.affiliationInternational Maize and Wheat Improvement Centeren
cg.contributor.donorCGIAR Trust Funden
cg.contributor.initiativeDigital Innovationen
cg.coverage.countryMexicoen
cg.coverage.iso3166-alpha2MXen
cg.coverage.regionLatin Americaen
cg.coverage.subregionGuanajuatoen
cg.creator.identifierUrs Schulthess: 0000-0002-9642-9762en
cg.creator.identifierSimon Fonteyne: 0000-0001-9965-5266en
cg.creator.identifierAndrea Gardeazábal-Monsalve: 0000-0003-1529-4200en
cg.howPublishedGrey Literatureen
cg.reviewStatusInternal Reviewen
cg.subject.actionAreaSystems Transformationen
cg.subject.impactAreaPoverty reduction, livelihoods and jobsen
dc.contributor.authorSchulthess, Ursen
dc.contributor.authorFonteyne, Simonen
dc.contributor.authorGardeazabal Monsalve, Andreaen
dc.date.accessioned2025-02-13T14:39:12Zen
dc.date.available2025-02-13T14:39:12Zen
dc.identifier.urihttps://hdl.handle.net/10568/173025
dc.titleECOSat (Estimation of carbon offsets with satellites) - Final reporten
dcterms.abstractThis study aimed to assess whether radar (Sentinel-1) and optical (Sentinel-2) satellite data could detect residue management practices and differentiate between conventional, minimal, and no tillage fields in Guanajuato, Mexico. The study used in-situ data collected by the CIMMYT-led MasAgro Guanajuato project, which tracks land preparation and crop management. Various tillage and residue indices were tested, including NDSVI, NDTI, and NDI5, based on Sentinel-2 bands. The conclusion suggests that most successful remote sensing applications for tillage detection and residue management rely on survey data. These data can then be used to train machine learning based algorithms.en
dcterms.accessRightsOpen Accessen
dcterms.bibliographicCitationSchulthess, U., Fonteyne, S., & Gardeazabal Monsalve, A. (2024). ECOSat (Estimation of carbon offsets with satellites) - Final report. IFPRI. https://hdl.handle.net/10883/35520en
dcterms.hasVersionhttps://hdl.handle.net/10883/35520en
dcterms.issued2024-12en
dcterms.languageenen
dcterms.licenseCC-BY-4.0en
dcterms.publisherInternational Food Policy Research Instituteen
dcterms.subjectremote sensingen
dcterms.subjectcrop residue managementen
dcterms.subjectconservation agricultureen
dcterms.subjecttillageen
dcterms.typeWorking Paperen

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