TreeEyed: A QGIS plugin for tree monitoring in silvopastoral systems using state of the art AI models
Tree 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 tool...
| Main Authors: | , , , |
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| Format: | Journal Article |
| Language: | Inglés |
| Published: |
Elsevier
2025
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/172989 |
| _version_ | 1855527889148051456 |
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| author | Ruiz-Hurtado, Andres Felipe Bolaños, Juliana Perez Arrechea-Castillo, Darwin Alexis Cardoso, Juan Andres |
| author_browse | Arrechea-Castillo, Darwin Alexis Bolaños, Juliana Perez Cardoso, Juan Andres Ruiz-Hurtado, Andres Felipe |
| author_facet | Ruiz-Hurtado, Andres Felipe Bolaños, Juliana Perez Arrechea-Castillo, Darwin Alexis Cardoso, Juan Andres |
| author_sort | Ruiz-Hurtado, Andres Felipe |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Tree 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. |
| format | Journal Article |
| id | CGSpace172989 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | Elsevier |
| publisherStr | Elsevier |
| record_format | dspace |
| spelling | CGSpace1729892025-11-11T18:51:32Z TreeEyed: A QGIS plugin for tree monitoring in silvopastoral systems using state of the art AI models Ruiz-Hurtado, Andres Felipe Bolaños, Juliana Perez Arrechea-Castillo, Darwin Alexis Cardoso, Juan Andres remote sensing trees silvopastoral systems monitoring geographical information systems-geographic information systems sistema de información geográfica imagery-computer vision imagen-visión por ordenador sensor sistema silvopascícola-sistemas silvopastorales Árbol forestal Tree 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. 2025-02 2025-02-12T15:12:51Z 2025-02-12T15:12:51Z Journal Article https://hdl.handle.net/10568/172989 en Open Access application/pdf Elsevier Ruiz-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: 2352-7110 |
| spellingShingle | remote sensing trees silvopastoral systems monitoring geographical information systems-geographic information systems sistema de información geográfica imagery-computer vision imagen-visión por ordenador sensor sistema silvopascícola-sistemas silvopastorales Árbol forestal Ruiz-Hurtado, Andres Felipe Bolaños, Juliana Perez Arrechea-Castillo, Darwin Alexis Cardoso, Juan Andres TreeEyed: A QGIS plugin for tree monitoring in silvopastoral systems using state of the art AI models |
| title | TreeEyed: A QGIS plugin for tree monitoring in silvopastoral systems using state of the art AI models |
| title_full | TreeEyed: A QGIS plugin for tree monitoring in silvopastoral systems using state of the art AI models |
| title_fullStr | TreeEyed: A QGIS plugin for tree monitoring in silvopastoral systems using state of the art AI models |
| title_full_unstemmed | TreeEyed: A QGIS plugin for tree monitoring in silvopastoral systems using state of the art AI models |
| title_short | TreeEyed: A QGIS plugin for tree monitoring in silvopastoral systems using state of the art AI models |
| title_sort | treeeyed a qgis plugin for tree monitoring in silvopastoral systems using state of the art ai models |
| topic | remote sensing trees silvopastoral systems monitoring geographical information systems-geographic information systems sistema de información geográfica imagery-computer vision imagen-visión por ordenador sensor sistema silvopascícola-sistemas silvopastorales Árbol forestal |
| url | https://hdl.handle.net/10568/172989 |
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