TreeEyed: A QGIS plugin for tree monitoring in silvopastoral systems using state of the art AI models

cg.authorship.typesCGIAR and advanced research instituteen_US
cg.contributor.affiliationInternational Center for Tropical Agricultureen_US
cg.contributor.affiliationUniversity of Salzburgen_US
cg.contributor.initiativeAccelerated Breedingen_US
cg.contributor.initiativeLivestock and Climateen_US
cg.contributor.initiativeSustainable Animal Productivityen_US
cg.creator.identifierAndres Felipe Ruiz-Hurtado: 0000-0003-1293-8736en_US
cg.creator.identifierDarwin Alexis Arrechea-Castillo: 0000-0002-2395-2181en_US
cg.creator.identifierJuan Andrés Cardoso Arango: 0009-0001-8761-0578en_US
cg.identifier.doihttps://doi.org/10.1016/j.softx.2025.102071en_US
cg.isijournalISI Journalen_US
cg.issn2352-7110en_US
cg.journalSoftwareXen_US
cg.reviewStatusPeer Reviewen_US
cg.subject.actionAreaGenetic Innovationen_US
cg.subject.actionAreaResilient Agrifood Systemsen_US
cg.subject.alliancebiovciatINFORMATICSen_US
cg.subject.alliancebiovciatLIVESTOCKen_US
cg.subject.alliancebiovciatPLANT GENETIC RESOURCESen_US
cg.subject.alliancebiovciatTREE CROPSen_US
cg.subject.alliancebiovciatTROPICAL FORAGESen_US
cg.subject.impactAreaClimate adaptation and mitigationen_US
cg.subject.impactAreaNutrition, health and food securityen_US
cg.subject.impactAreaPoverty reduction, livelihoods and jobsen_US
cg.subject.sdgSDG 1 - No povertyen_US
cg.subject.sdgSDG 2 - Zero hungeren_US
cg.subject.sdgSDG 8 - Decent work and economic growthen_US
cg.subject.sdgSDG 10 - Reduce inequalitiesen_US
cg.subject.sdgSDG 13 - Climate actionen_US
cg.volume29en_US
dc.contributor.authorRuiz-Hurtado, Andres Felipe
dc.contributor.authorBolaños, Juliana Perez
dc.contributor.authorArrechea-Castillo, Darwin Alexis
dc.contributor.authorCardoso, Juan Andres
dc.date.accessioned2025-02-12T15:12:51Z
dc.date.available2025-02-12T15:12:51Z
dc.identifier.urihttps://hdl.handle.net/10568/172989
dc.titleTreeEyed: A QGIS plugin for tree monitoring in silvopastoral systems using state of the art AI modelsen_US
dcterms.abstractTree monitoring is a challenging task due to the labour-intensive and time-consuming data collection methods required. We present TreeEyed, a QGIS plugin designed to facilitate the monitoring of trees using remote sensing RGB imagery and artificial intelligence models. The plugin offers several tools including tree inference process for tree segmentation and detection. This tool was implemented to facilitate the manipulation and processing of Geographical Information System (GIS) data from different sources, allowing multi-resolution, variable extent, and generating results in a standard GIS format (georeferenced raster and vector). Additional options like postprocessing, dataset generation, and data validation are also incorporated.en_US
dcterms.accessRightsOpen Accessen_US
dcterms.available2025-01-29
dcterms.bibliographicCitationRuiz-Hurtado, A.F.; Bolaños, J.P.; Arrechea-Castillo, D.A.; Cardoso, J.A. (2025) TreeEyed: A QGIS plugin for tree monitoring in silvopastoral systems using state of the art AI models. SoftwareX 29: 102071. ISSN: 2352-7110en_US
dcterms.extent102071en_US
dcterms.issued2025-01-29en_US
dcterms.languageenen_US
dcterms.licenseCC-BY-NC-4.0en_US
dcterms.publisherElsevier BVen_US
dcterms.subjectremote sensingen_US
dcterms.subjecttreesen_US
dcterms.subjectsilvopastoral systemsen_US
dcterms.subjectmonitoringen_US
dcterms.subjectgeographical information systems-geographic information systemsen_US
dcterms.subjectsistema de información geográficaen_US
dcterms.subjectimagery-computer visionen_US
dcterms.subjectimagen-visión por ordenadoren_US
dcterms.subjectsensoren_US
dcterms.subjectsistema silvopascícola-sistemas silvopastoralesen_US
dcterms.subjectÁrbol forestalen_US
dcterms.typeJournal Articleen_US

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