Spatial Quality Evaluation of Resampled Unmanned Aerial Vehicle-Imagery for Weed Mapping

Unmanned aerial vehicles (UAVs) combined with different spectral range sensors are an emerging technology for providing early weed maps for optimizing herbicide applications. Considering that weeds at very early phenological stages are similar spectrally and in appearance, three major components are...

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Detalles Bibliográficos
Autores: Borra-Serrano, Irene, Peña Barragán, José Manuel, Torres-Sánchez, Jorge, Mesas-Carrascosa, Francisco Javier, López Granados, Francisca
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2015
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/137431
Acceso en línea:http://hdl.handle.net/10261/137431
Access Level:acceso abierto
Palabra clave:Ortho-mosaicked image
UAV
Resampling
Weed mapping
Visible (RGB)
Near-infrared (NIR)
OBIA
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spelling Spatial Quality Evaluation of Resampled Unmanned Aerial Vehicle-Imagery for Weed MappingBorra-Serrano, IrenePeña Barragán, José ManuelTorres-Sánchez, JorgeMesas-Carrascosa, Francisco JavierLópez Granados, FranciscaOrtho-mosaicked imageUAVResamplingWeed mappingVisible (RGB)Near-infrared (NIR)OBIAUnmanned aerial vehicles (UAVs) combined with different spectral range sensors are an emerging technology for providing early weed maps for optimizing herbicide applications. Considering that weeds at very early phenological stages are similar spectrally and in appearance, three major components are relevant: spatial resolution, type of sensor and classification algorithm. Resampling is a technique to create a new version of an image with a different width and/or height in pixels, and it has been used in satellite imagery with different spatial and temporal resolutions. In this paper, the efficiency of resampled-images (RS-images) created from real UAV-images (UAV-images; the UAVs were equipped with two types of sensors, i.e., visible and visible plus near-infrared spectra) captured at different altitudes is examined to test the quality of the RS-image output. The performance of the object-based-image-analysis (OBIA) implemented for the early weed mapping using different weed thresholds was also evaluated. Our results showed that resampling accurately extracted the spectral values from high spatial resolution UAV-images at an altitude of 30 m and the RS-image data at altitudes of 60 and 100 m, was able to provide accurate weed cover and herbicide application maps compared with UAV-images from real flights.This research was financed by the RECUPERA-2020 Project (An agreement between CSIC and Spanish MINECO, EU-FEDER funds). Research of Torres-Sánchez and Peña was financed by the FPI and Ramón & Cajal Programs (MINECO and EU-FEDER funds), respectively. We acknowledge support by the CSIC Open Access Publication Initiative through its Unit of Information Resources for Research (URICI).Peer ReviewedMultidisciplinary Digital Publishing InstituteEuropean CommissionMinisterio de Economía y Competitividad (España)Consejo Superior de Investigaciones Científicas (España)Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]2016201620152016info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionhttp://hdl.handle.net/10261/137431reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Ingléshttp://dx.doi.org/10.3390/s150x0000xSíinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/1374312026-05-22T06:33:51Z
dc.title.none.fl_str_mv Spatial Quality Evaluation of Resampled Unmanned Aerial Vehicle-Imagery for Weed Mapping
title Spatial Quality Evaluation of Resampled Unmanned Aerial Vehicle-Imagery for Weed Mapping
spellingShingle Spatial Quality Evaluation of Resampled Unmanned Aerial Vehicle-Imagery for Weed Mapping
Borra-Serrano, Irene
Ortho-mosaicked image
UAV
Resampling
Weed mapping
Visible (RGB)
Near-infrared (NIR)
OBIA
title_short Spatial Quality Evaluation of Resampled Unmanned Aerial Vehicle-Imagery for Weed Mapping
title_full Spatial Quality Evaluation of Resampled Unmanned Aerial Vehicle-Imagery for Weed Mapping
title_fullStr Spatial Quality Evaluation of Resampled Unmanned Aerial Vehicle-Imagery for Weed Mapping
title_full_unstemmed Spatial Quality Evaluation of Resampled Unmanned Aerial Vehicle-Imagery for Weed Mapping
title_sort Spatial Quality Evaluation of Resampled Unmanned Aerial Vehicle-Imagery for Weed Mapping
dc.creator.none.fl_str_mv Borra-Serrano, Irene
Peña Barragán, José Manuel
Torres-Sánchez, Jorge
Mesas-Carrascosa, Francisco Javier
López Granados, Francisca
author Borra-Serrano, Irene
author_facet Borra-Serrano, Irene
Peña Barragán, José Manuel
Torres-Sánchez, Jorge
Mesas-Carrascosa, Francisco Javier
López Granados, Francisca
author_role author
author2 Peña Barragán, José Manuel
Torres-Sánchez, Jorge
Mesas-Carrascosa, Francisco Javier
López Granados, Francisca
author2_role author
author
author
author
dc.contributor.none.fl_str_mv European Commission
Ministerio de Economía y Competitividad (España)
Consejo Superior de Investigaciones Científicas (España)
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Ortho-mosaicked image
UAV
Resampling
Weed mapping
Visible (RGB)
Near-infrared (NIR)
OBIA
topic Ortho-mosaicked image
UAV
Resampling
Weed mapping
Visible (RGB)
Near-infrared (NIR)
OBIA
description Unmanned aerial vehicles (UAVs) combined with different spectral range sensors are an emerging technology for providing early weed maps for optimizing herbicide applications. Considering that weeds at very early phenological stages are similar spectrally and in appearance, three major components are relevant: spatial resolution, type of sensor and classification algorithm. Resampling is a technique to create a new version of an image with a different width and/or height in pixels, and it has been used in satellite imagery with different spatial and temporal resolutions. In this paper, the efficiency of resampled-images (RS-images) created from real UAV-images (UAV-images; the UAVs were equipped with two types of sensors, i.e., visible and visible plus near-infrared spectra) captured at different altitudes is examined to test the quality of the RS-image output. The performance of the object-based-image-analysis (OBIA) implemented for the early weed mapping using different weed thresholds was also evaluated. Our results showed that resampling accurately extracted the spectral values from high spatial resolution UAV-images at an altitude of 30 m and the RS-image data at altitudes of 60 and 100 m, was able to provide accurate weed cover and herbicide application maps compared with UAV-images from real flights.
publishDate 2015
dc.date.none.fl_str_mv 2015
2016
2016
2016
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Publisher's version
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/137431
url http://hdl.handle.net/10261/137431
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv http://dx.doi.org/10.3390/s150x0000x
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,81155

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