Geospatial assessment of pest-induced forest damage through the use of UAV-bases NIR imaging and Gi-technology

Detalhes bibliográficos
Autor(a) principal: Soloviov, Oleksii
Data de Publicação: 2014
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/11545
Resumo: Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.
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spelling Geospatial assessment of pest-induced forest damage through the use of UAV-bases NIR imaging and Gi-technologyColor-infrared Images (CIR)Near-infrared Images (NIR)Object-based ClassificationPest InfestationPixel-based ClassificationPrincipal ComponentUnmanned Aerial VehicleVegetation IndicesVery High Resolution ImagesDissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.Every year oak forests become infected by populations of the splendor beetle (Agrilus bigutattus). The detection and monitoring of infected trees is important, because of economic and ecological reasons. Traditional approach to detect the pest infestation level of each tree is performed by using ground-based observation method. It is long and ineffective method because of limitations, such as: poor visibility of the highest trees and impenetrability of some forest plots. The main goal is to identify infected oaks trees by splendor beetle at the 2 study areas. Pest-infested oak trees by splendor beetle are characterized by high level of defoliation and different reflection signatures. These features can be detected by using very high resolution color infrared (CIR) images. In August 2013 it was performed flight campaign by using unmanned aerial systems (UAS). CIR images were covering 2 test sites in rural area, near city Soest (Germany). Study areas represents small, privately owned oaks forest plots. In this research was used a small quadrocopter (Microdrone MD4-200) with vertical takeoff and landing capability (VTOL). Microdrone is carried a digital camera (Canon PowerShot SD 780 IS). Additionally, camera was modified to capture not just a visible spectrum, but also NIR spectrum (400 to 1100 nm) of infected oaks. The proposed workflow includes the CIR image acquisition, image stitching, radiometric correction, georeferencing, modified vegetation indices calculation, pixel based and object-based image classification and accuracy assessment. Images were classified using 5 classes (healthy, low infected, high infected, died trees and canopy gaps). Finally, the results can be integrated with existing WMS service. Applying of UAV make possible to obtain multitemporal data, which facilitates monitoring and detection of infected trees. The work was performed in close cooperation with the Forestry Department of Soest (Germany).Caetano, Mário Sílvio Rochinha de AndradePrinz, TorstenPla Bañón, FilibertoRUNSoloviov, Oleksii2014-03-07T18:16:53Z2014-02-282014-02-28T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/11545TID:201391791enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T03:46:04Zoai:run.unl.pt:10362/11545Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:20:21.246643Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Geospatial assessment of pest-induced forest damage through the use of UAV-bases NIR imaging and Gi-technology
title Geospatial assessment of pest-induced forest damage through the use of UAV-bases NIR imaging and Gi-technology
spellingShingle Geospatial assessment of pest-induced forest damage through the use of UAV-bases NIR imaging and Gi-technology
Soloviov, Oleksii
Color-infrared Images (CIR)
Near-infrared Images (NIR)
Object-based Classification
Pest Infestation
Pixel-based Classification
Principal Component
Unmanned Aerial Vehicle
Vegetation Indices
Very High Resolution Images
title_short Geospatial assessment of pest-induced forest damage through the use of UAV-bases NIR imaging and Gi-technology
title_full Geospatial assessment of pest-induced forest damage through the use of UAV-bases NIR imaging and Gi-technology
title_fullStr Geospatial assessment of pest-induced forest damage through the use of UAV-bases NIR imaging and Gi-technology
title_full_unstemmed Geospatial assessment of pest-induced forest damage through the use of UAV-bases NIR imaging and Gi-technology
title_sort Geospatial assessment of pest-induced forest damage through the use of UAV-bases NIR imaging and Gi-technology
author Soloviov, Oleksii
author_facet Soloviov, Oleksii
author_role author
dc.contributor.none.fl_str_mv Caetano, Mário Sílvio Rochinha de Andrade
Prinz, Torsten
Pla Bañón, Filiberto
RUN
dc.contributor.author.fl_str_mv Soloviov, Oleksii
dc.subject.por.fl_str_mv Color-infrared Images (CIR)
Near-infrared Images (NIR)
Object-based Classification
Pest Infestation
Pixel-based Classification
Principal Component
Unmanned Aerial Vehicle
Vegetation Indices
Very High Resolution Images
topic Color-infrared Images (CIR)
Near-infrared Images (NIR)
Object-based Classification
Pest Infestation
Pixel-based Classification
Principal Component
Unmanned Aerial Vehicle
Vegetation Indices
Very High Resolution Images
description Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.
publishDate 2014
dc.date.none.fl_str_mv 2014-03-07T18:16:53Z
2014-02-28
2014-02-28T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/11545
TID:201391791
url http://hdl.handle.net/10362/11545
identifier_str_mv TID:201391791
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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