DroneData: a repository for applying drone-based-data to crop characterization

This tool is available on GitHub. The users can calculate vegetation indexes, apply different trained ML models for crop-field or individual-plants detection. Likewise, when a 3D-cloud-points-file is provided, the user can estimate plant-height and leaf-angle. The tool is used by the Universidad-Ped...

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Bibliographic Details
Main Author: CGIAR Research Program on Climate Change, Agriculture and Food Security
Format: Informe técnico
Language:Inglés
Published: 2021
Subjects:
Online Access:https://hdl.handle.net/10568/123118
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author CGIAR Research Program on Climate Change, Agriculture and Food Security
author_browse CGIAR Research Program on Climate Change, Agriculture and Food Security
author_facet CGIAR Research Program on Climate Change, Agriculture and Food Security
author_sort CGIAR Research Program on Climate Change, Agriculture and Food Security
collection Repository of Agricultural Research Outputs (CGSpace)
description This tool is available on GitHub. The users can calculate vegetation indexes, apply different trained ML models for crop-field or individual-plants detection. Likewise, when a 3D-cloud-points-file is provided, the user can estimate plant-height and leaf-angle. The tool is used by the Universidad-Pedagógica-y-tecnológica and Tokyo-university, for crop area estimation and high-detailed-plant-phenotyping-characterization.
format Informe técnico
id CGSpace123118
institution CGIAR Consortium
language Inglés
publishDate 2021
publishDateRange 2021
publishDateSort 2021
record_format dspace
spelling CGSpace1231182023-03-14T11:41:35Z DroneData: a repository for applying drone-based-data to crop characterization CGIAR Research Program on Climate Change, Agriculture and Food Security models development rural development data plants vegetation estimation systems agrifood systems height detection plant This tool is available on GitHub. The users can calculate vegetation indexes, apply different trained ML models for crop-field or individual-plants detection. Likewise, when a 3D-cloud-points-file is provided, the user can estimate plant-height and leaf-angle. The tool is used by the Universidad-Pedagógica-y-tecnológica and Tokyo-university, for crop area estimation and high-detailed-plant-phenotyping-characterization. 2021-12-31 2022-10-06T14:22:02Z 2022-10-06T14:22:02Z Report https://hdl.handle.net/10568/123118 en Open Access application/pdf CGIAR Research Program on Climate Change, Agriculture and Food Security. 2021. DroneData: a repository for applying drone-based-data to crop characterization. Reported in Climate Change, Agriculture and Food Security Annual Report 2021. Innovations.
spellingShingle models
development
rural development
data
plants
vegetation
estimation
systems
agrifood systems
height
detection
plant
CGIAR Research Program on Climate Change, Agriculture and Food Security
DroneData: a repository for applying drone-based-data to crop characterization
title DroneData: a repository for applying drone-based-data to crop characterization
title_full DroneData: a repository for applying drone-based-data to crop characterization
title_fullStr DroneData: a repository for applying drone-based-data to crop characterization
title_full_unstemmed DroneData: a repository for applying drone-based-data to crop characterization
title_short DroneData: a repository for applying drone-based-data to crop characterization
title_sort dronedata a repository for applying drone based data to crop characterization
topic models
development
rural development
data
plants
vegetation
estimation
systems
agrifood systems
height
detection
plant
url https://hdl.handle.net/10568/123118
work_keys_str_mv AT cgiarresearchprogramonclimatechangeagricultureandfoodsecurity dronedataarepositoryforapplyingdronebaseddatatocropcharacterization