Road extraction from low-cost GNSS-device dense trajectories
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | |
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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Repositório Institucional da UNESP |
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2946 |
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 |
|
_version_ |
1808128789311389696 |