Multispectral Mapping on 3D Models and Multi-Temporal Monitoring for Individual Characterization of Olive Trees

3D plant structure observation and characterization to get a comprehensive knowledge about the plant status still poses a challenge in Precision Agriculture (PA). The complex branching and self-hidden geometry in the plant canopy are some of the existing problems for the 3D reconstruction of vegetat...

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Autores: Jurado Rodríguez, Juan Manuel, Ortega Alvarado, Lidia María, Cubillas Mercado, Juan José, Feito Higueruela, Francisco Ramón
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2020
País:España
Institución:Universidad de Jaén
Repositorio:RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
OAI Identifier:oai:dnet:ruja________::1400f3a767274e9eda534595024f03e1
Acceso en línea:https://www.mdpi.com/2072-4292/12/7/1106
https://hdl.handle.net/10953/7925
Access Level:acceso abierto
Palabra clave:unmanned aerial vehicles
heterogeneous data fusion
3D olive tree models
multispectral imaging
multi-temporal analysis
1203.04, 3101.10, 1203.09
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spelling Multispectral Mapping on 3D Models and Multi-Temporal Monitoring for Individual Characterization of Olive TreesJurado Rodríguez, Juan ManuelOrtega Alvarado, Lidia MaríaCubillas Mercado, Juan JoséFeito Higueruela, Francisco Ramónunmanned aerial vehiclesheterogeneous data fusion3D olive tree modelsmultispectral imagingmulti-temporal analysis1203.04, 3101.10, 1203.093D plant structure observation and characterization to get a comprehensive knowledge about the plant status still poses a challenge in Precision Agriculture (PA). The complex branching and self-hidden geometry in the plant canopy are some of the existing problems for the 3D reconstruction of vegetation. In this paper, we propose a novel application for the fusion of multispectral images and high-resolution point clouds of an olive orchard. Our methodology is based on a multi-temporal approach to study the evolution of olive trees. This process is fully automated and no human intervention is required to characterize the point cloud with the reflectance captured by multiple multispectral images. The main objective of this work is twofold: (1) the multispectral image mapping on a high-resolution point cloud and (2) the multi-temporal analysis of morphological and spectral traits in two flight campaigns. Initially, the study area is modeled by taking multiple overlapping RGB images with a high-resolution camera from an unmanned aerial vehicle (UAV). In addition, a UAV-based multispectral sensor is used to capture the reflectance for some narrow-bands (green, near-infrared, red, and red-edge). Then, the RGB point cloud with a high detailed geometry of olive trees is enriched by mapping the reflectance maps, which are generated for every multispectral image. Therefore, each 3D point is related to its corresponding pixel of the multispectral image, in which it is visible. As a result, the 3D models of olive trees are characterized by the observed reflectance in the plant canopy. These reflectance values are also combined to calculate several vegetation indices (NDVI, RVI, GRVI, and NDRE). According to the spectral and spatial relationships in the olive plantation, segmentation of individual olive trees is performed. On the one hand, plant morphology is studied by a voxel-based decomposition of its 3D structure to estimate the height and volume. On the other hand, the plant health is studied by the detection of meaningful spectral traits of olive trees. Moreover, the proposed methodology also allows the processing of multi-temporal data to study the variability of the studied features. Consequently, some relevant changes are detected and the development of each olive tree is analyzed by a visual-based and statistical approach. The interactive visualization and analysis of the enriched 3D plant structure with different spectral layers is an innovative method to inspect the plant health and ensure adequate plantation sustainability.This research has been partially supported by the Ministerio de Economía y Competitividad and the European Union (via ERDF funds) through the research project TIN2017-84968-R.MDPI202620262020info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://www.mdpi.com/2072-4292/12/7/1106https://hdl.handle.net/10953/7925reponame:RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaéninstname:Universidad de JaénInglésREMOTE SENSINGinfo:eu-repo/semantics/openAccessoai:dnet:ruja________::1400f3a767274e9eda534595024f03e12026-06-24T12:41:07Z
dc.title.none.fl_str_mv Multispectral Mapping on 3D Models and Multi-Temporal Monitoring for Individual Characterization of Olive Trees
title Multispectral Mapping on 3D Models and Multi-Temporal Monitoring for Individual Characterization of Olive Trees
spellingShingle Multispectral Mapping on 3D Models and Multi-Temporal Monitoring for Individual Characterization of Olive Trees
Jurado Rodríguez, Juan Manuel
unmanned aerial vehicles
heterogeneous data fusion
3D olive tree models
multispectral imaging
multi-temporal analysis
1203.04, 3101.10, 1203.09
title_short Multispectral Mapping on 3D Models and Multi-Temporal Monitoring for Individual Characterization of Olive Trees
title_full Multispectral Mapping on 3D Models and Multi-Temporal Monitoring for Individual Characterization of Olive Trees
title_fullStr Multispectral Mapping on 3D Models and Multi-Temporal Monitoring for Individual Characterization of Olive Trees
title_full_unstemmed Multispectral Mapping on 3D Models and Multi-Temporal Monitoring for Individual Characterization of Olive Trees
title_sort Multispectral Mapping on 3D Models and Multi-Temporal Monitoring for Individual Characterization of Olive Trees
dc.creator.none.fl_str_mv Jurado Rodríguez, Juan Manuel
Ortega Alvarado, Lidia María
Cubillas Mercado, Juan José
Feito Higueruela, Francisco Ramón
author Jurado Rodríguez, Juan Manuel
author_facet Jurado Rodríguez, Juan Manuel
Ortega Alvarado, Lidia María
Cubillas Mercado, Juan José
Feito Higueruela, Francisco Ramón
author_role author
author2 Ortega Alvarado, Lidia María
Cubillas Mercado, Juan José
Feito Higueruela, Francisco Ramón
author2_role author
author
author
dc.subject.none.fl_str_mv unmanned aerial vehicles
heterogeneous data fusion
3D olive tree models
multispectral imaging
multi-temporal analysis
1203.04, 3101.10, 1203.09
topic unmanned aerial vehicles
heterogeneous data fusion
3D olive tree models
multispectral imaging
multi-temporal analysis
1203.04, 3101.10, 1203.09
description 3D plant structure observation and characterization to get a comprehensive knowledge about the plant status still poses a challenge in Precision Agriculture (PA). The complex branching and self-hidden geometry in the plant canopy are some of the existing problems for the 3D reconstruction of vegetation. In this paper, we propose a novel application for the fusion of multispectral images and high-resolution point clouds of an olive orchard. Our methodology is based on a multi-temporal approach to study the evolution of olive trees. This process is fully automated and no human intervention is required to characterize the point cloud with the reflectance captured by multiple multispectral images. The main objective of this work is twofold: (1) the multispectral image mapping on a high-resolution point cloud and (2) the multi-temporal analysis of morphological and spectral traits in two flight campaigns. Initially, the study area is modeled by taking multiple overlapping RGB images with a high-resolution camera from an unmanned aerial vehicle (UAV). In addition, a UAV-based multispectral sensor is used to capture the reflectance for some narrow-bands (green, near-infrared, red, and red-edge). Then, the RGB point cloud with a high detailed geometry of olive trees is enriched by mapping the reflectance maps, which are generated for every multispectral image. Therefore, each 3D point is related to its corresponding pixel of the multispectral image, in which it is visible. As a result, the 3D models of olive trees are characterized by the observed reflectance in the plant canopy. These reflectance values are also combined to calculate several vegetation indices (NDVI, RVI, GRVI, and NDRE). According to the spectral and spatial relationships in the olive plantation, segmentation of individual olive trees is performed. On the one hand, plant morphology is studied by a voxel-based decomposition of its 3D structure to estimate the height and volume. On the other hand, the plant health is studied by the detection of meaningful spectral traits of olive trees. Moreover, the proposed methodology also allows the processing of multi-temporal data to study the variability of the studied features. Consequently, some relevant changes are detected and the development of each olive tree is analyzed by a visual-based and statistical approach. The interactive visualization and analysis of the enriched 3D plant structure with different spectral layers is an innovative method to inspect the plant health and ensure adequate plantation sustainability.
publishDate 2020
dc.date.none.fl_str_mv 2020
2026
2026
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://www.mdpi.com/2072-4292/12/7/1106
https://hdl.handle.net/10953/7925
url https://www.mdpi.com/2072-4292/12/7/1106
https://hdl.handle.net/10953/7925
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv REMOTE SENSING
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
instname:Universidad de Jaén
instname_str Universidad de Jaén
reponame_str RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
collection RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
repository.name.fl_str_mv
repository.mail.fl_str_mv
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