Improving the positional accuracy of drainage networks extracted from Global Digital Elevation Models using OpenstreetMap data
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10316/101904 https://doi.org/10.1515/johh-2017-0057 |
Resumo: | Drainage networks allow the extraction of topographic parameters that are useful for basins characterization and necessary for hydrologic modelling. One way to obtain drainage networks is by their extraction from Digital Elevation Models (DEMs). However, it is common that no freely available DEMs at regional or national level exist. One way to overcome this situation is to use the available free Global Digital Elevation Models (GDEMs). However, these datasets have relatively low spatial resolutions, 30 and 90 meters for ASTER and SRTM, respectively, and it has been shown that their accuracy is relatively low in several regions (e.g., Kääb, 2005; Mukul et al., 2017). In this study a methodology is presented to improve the positional accuracy of the drainage networks extracted from the GDEMs using crowdsourced data available in the collaborative project OpenStreetMap (OSM). In this approach only free and global datasets are used, enabling its application to any location of the world. The methodology uses elevation points derived from the GDEMs and the water lines extracted from the collaborative project OSM to generate new DEMs, from which new water lines are obtained. The methodology is applied to two study areas and the positional accuracy of the used data and the obtained results are assessed using reference data. |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Improving the positional accuracy of drainage networks extracted from Global Digital Elevation Models using OpenstreetMap dataDrainage networksGDEMsOpenStreetMapPositional accuracyDrainage networks allow the extraction of topographic parameters that are useful for basins characterization and necessary for hydrologic modelling. One way to obtain drainage networks is by their extraction from Digital Elevation Models (DEMs). However, it is common that no freely available DEMs at regional or national level exist. One way to overcome this situation is to use the available free Global Digital Elevation Models (GDEMs). However, these datasets have relatively low spatial resolutions, 30 and 90 meters for ASTER and SRTM, respectively, and it has been shown that their accuracy is relatively low in several regions (e.g., Kääb, 2005; Mukul et al., 2017). In this study a methodology is presented to improve the positional accuracy of the drainage networks extracted from the GDEMs using crowdsourced data available in the collaborative project OpenStreetMap (OSM). In this approach only free and global datasets are used, enabling its application to any location of the world. The methodology uses elevation points derived from the GDEMs and the water lines extracted from the collaborative project OSM to generate new DEMs, from which new water lines are obtained. The methodology is applied to two study areas and the positional accuracy of the used data and the obtained results are assessed using reference data.2018info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10316/101904http://hdl.handle.net/10316/101904https://doi.org/10.1515/johh-2017-0057eng0042-790XMonteiro, Elisabete S. V.Fonte, Cidália C.Lima, João L. M. P. deinfo: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:RCAAP2022-09-21T20:40:02ZPortal AgregadorONG |
dc.title.none.fl_str_mv |
Improving the positional accuracy of drainage networks extracted from Global Digital Elevation Models using OpenstreetMap data |
title |
Improving the positional accuracy of drainage networks extracted from Global Digital Elevation Models using OpenstreetMap data |
spellingShingle |
Improving the positional accuracy of drainage networks extracted from Global Digital Elevation Models using OpenstreetMap data Monteiro, Elisabete S. V. Drainage networks GDEMs OpenStreetMap Positional accuracy |
title_short |
Improving the positional accuracy of drainage networks extracted from Global Digital Elevation Models using OpenstreetMap data |
title_full |
Improving the positional accuracy of drainage networks extracted from Global Digital Elevation Models using OpenstreetMap data |
title_fullStr |
Improving the positional accuracy of drainage networks extracted from Global Digital Elevation Models using OpenstreetMap data |
title_full_unstemmed |
Improving the positional accuracy of drainage networks extracted from Global Digital Elevation Models using OpenstreetMap data |
title_sort |
Improving the positional accuracy of drainage networks extracted from Global Digital Elevation Models using OpenstreetMap data |
author |
Monteiro, Elisabete S. V. |
author_facet |
Monteiro, Elisabete S. V. Fonte, Cidália C. Lima, João L. M. P. de |
author_role |
author |
author2 |
Fonte, Cidália C. Lima, João L. M. P. de |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Monteiro, Elisabete S. V. Fonte, Cidália C. Lima, João L. M. P. de |
dc.subject.por.fl_str_mv |
Drainage networks GDEMs OpenStreetMap Positional accuracy |
topic |
Drainage networks GDEMs OpenStreetMap Positional accuracy |
description |
Drainage networks allow the extraction of topographic parameters that are useful for basins characterization and necessary for hydrologic modelling. One way to obtain drainage networks is by their extraction from Digital Elevation Models (DEMs). However, it is common that no freely available DEMs at regional or national level exist. One way to overcome this situation is to use the available free Global Digital Elevation Models (GDEMs). However, these datasets have relatively low spatial resolutions, 30 and 90 meters for ASTER and SRTM, respectively, and it has been shown that their accuracy is relatively low in several regions (e.g., Kääb, 2005; Mukul et al., 2017). In this study a methodology is presented to improve the positional accuracy of the drainage networks extracted from the GDEMs using crowdsourced data available in the collaborative project OpenStreetMap (OSM). In this approach only free and global datasets are used, enabling its application to any location of the world. The methodology uses elevation points derived from the GDEMs and the water lines extracted from the collaborative project OSM to generate new DEMs, from which new water lines are obtained. The methodology is applied to two study areas and the positional accuracy of the used data and the obtained results are assessed using reference data. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018 |
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://hdl.handle.net/10316/101904 http://hdl.handle.net/10316/101904 https://doi.org/10.1515/johh-2017-0057 |
url |
http://hdl.handle.net/10316/101904 https://doi.org/10.1515/johh-2017-0057 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0042-790X |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
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 |
|
repository.mail.fl_str_mv |
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1777302801049714688 |