Road extraction from low-cost GNSS-device dense trajectories

Detalhes bibliográficos
Autor(a) principal: de Moura Morceli, Bruno [UNESP]
Data de Publicação: 2023
Outros Autores: Porfírio Dal Poz, Aluir [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1080/17489725.2023.2216670
http://hdl.handle.net/11449/248933
Resumo: This paper proposes a method for road centerline extraction from dense Global Navigation Satellite System (GNSS) trajectories, collected by using low-cost GNSS-devices, i.e. smartphones. The proposed method basically consists in generating a frequency image by tracking the GNSS trajectories and then by applying the Steger line detector to the generated image to extract the road centerlines. The main motivation of using the Steger algorithm is its capability to detect lines with sub-pixel accuracy. To evaluate the obtained results, reference road centerlines are manually extracted from a georeferenced orthomosaic. The experiments performed demonstrate the high potential of applying the Steger line detector to frequency images, generated by using dense GPS (Global Positioning System) trajectories. The completeness and correctness values for the accomplished experiments were 98% and 99%, respectively. Additionally, the RMSE (Root Mean Square Error) ranged from 0.63 m to 2.39 m, or approximately 1/16 to 1/4 of the expected accuracy (about 10 m) of a point determined by the Single-Point Positioning (SPP) method, which is the GNSS positioning method usually employed by smartphones.
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spelling Road extraction from low-cost GNSS-device dense trajectoriesGNSS trajectoriesroad centerline extractionSmartphonesSteger line detectorThis paper proposes a method for road centerline extraction from dense Global Navigation Satellite System (GNSS) trajectories, collected by using low-cost GNSS-devices, i.e. smartphones. The proposed method basically consists in generating a frequency image by tracking the GNSS trajectories and then by applying the Steger line detector to the generated image to extract the road centerlines. The main motivation of using the Steger algorithm is its capability to detect lines with sub-pixel accuracy. To evaluate the obtained results, reference road centerlines are manually extracted from a georeferenced orthomosaic. The experiments performed demonstrate the high potential of applying the Steger line detector to frequency images, generated by using dense GPS (Global Positioning System) trajectories. The completeness and correctness values for the accomplished experiments were 98% and 99%, respectively. Additionally, the RMSE (Root Mean Square Error) ranged from 0.63 m to 2.39 m, or approximately 1/16 to 1/4 of the expected accuracy (about 10 m) of a point determined by the Single-Point Positioning (SPP) method, which is the GNSS positioning method usually employed by smartphones.Department of Cartography São Paulo State University (UNESP)Department of Cartography São Paulo State University (UNESP)Universidade Estadual Paulista (UNESP)de Moura Morceli, Bruno [UNESP]Porfírio Dal Poz, Aluir [UNESP]2023-07-29T13:57:41Z2023-07-29T13:57:41Z2023-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1080/17489725.2023.2216670Journal of Location Based Services.1748-97331748-9725http://hdl.handle.net/11449/24893310.1080/17489725.2023.22166702-s2.0-85160917020Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengJournal of Location Based Servicesinfo:eu-repo/semantics/openAccess2024-06-18T15:01:27Zoai:repositorio.unesp.br:11449/248933Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T17:18:25.128087Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Road extraction from low-cost GNSS-device dense trajectories
title Road extraction from low-cost GNSS-device dense trajectories
spellingShingle Road extraction from low-cost GNSS-device dense trajectories
de Moura Morceli, Bruno [UNESP]
GNSS trajectories
road centerline extraction
Smartphones
Steger line detector
title_short Road extraction from low-cost GNSS-device dense trajectories
title_full Road extraction from low-cost GNSS-device dense trajectories
title_fullStr Road extraction from low-cost GNSS-device dense trajectories
title_full_unstemmed Road extraction from low-cost GNSS-device dense trajectories
title_sort Road extraction from low-cost GNSS-device dense trajectories
author de Moura Morceli, Bruno [UNESP]
author_facet de Moura Morceli, Bruno [UNESP]
Porfírio Dal Poz, Aluir [UNESP]
author_role author
author2 Porfírio Dal Poz, Aluir [UNESP]
author2_role author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (UNESP)
dc.contributor.author.fl_str_mv de Moura Morceli, Bruno [UNESP]
Porfírio Dal Poz, Aluir [UNESP]
dc.subject.por.fl_str_mv GNSS trajectories
road centerline extraction
Smartphones
Steger line detector
topic GNSS trajectories
road centerline extraction
Smartphones
Steger line detector
description This paper proposes a method for road centerline extraction from dense Global Navigation Satellite System (GNSS) trajectories, collected by using low-cost GNSS-devices, i.e. smartphones. The proposed method basically consists in generating a frequency image by tracking the GNSS trajectories and then by applying the Steger line detector to the generated image to extract the road centerlines. The main motivation of using the Steger algorithm is its capability to detect lines with sub-pixel accuracy. To evaluate the obtained results, reference road centerlines are manually extracted from a georeferenced orthomosaic. The experiments performed demonstrate the high potential of applying the Steger line detector to frequency images, generated by using dense GPS (Global Positioning System) trajectories. The completeness and correctness values for the accomplished experiments were 98% and 99%, respectively. Additionally, the RMSE (Root Mean Square Error) ranged from 0.63 m to 2.39 m, or approximately 1/16 to 1/4 of the expected accuracy (about 10 m) of a point determined by the Single-Point Positioning (SPP) method, which is the GNSS positioning method usually employed by smartphones.
publishDate 2023
dc.date.none.fl_str_mv 2023-07-29T13:57:41Z
2023-07-29T13:57:41Z
2023-01-01
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1080/17489725.2023.2216670
Journal of Location Based Services.
1748-9733
1748-9725
http://hdl.handle.net/11449/248933
10.1080/17489725.2023.2216670
2-s2.0-85160917020
url http://dx.doi.org/10.1080/17489725.2023.2216670
http://hdl.handle.net/11449/248933
identifier_str_mv Journal of Location Based Services.
1748-9733
1748-9725
10.1080/17489725.2023.2216670
2-s2.0-85160917020
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Journal of Location Based Services
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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