QPEC: QGIS Toolkit for Evaluating Geospatial Data Positional Accuracy according to the Brazilian Cartographic Accuracy Standard
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Anuário do Instituto de Geociências (Online) |
Texto Completo: | https://revistas.ufrj.br/index.php/aigeo/article/view/54245 |
Resumo: | This paper presents the development of a QGIS plugin to support evaluating the planimetric positional quality for point and linear features based on the metrics established by Brazilian legislation. For this purpose, we used the QGIS environment Graphical Modeler, which consists of an interface to concatenate a series of processes into a single algorithm. The set of tools, called QPEC, allows for performing the statistical tests from the automatic identification of the sample size and discrepancies. In order to demonstrate the implemented functionalities, a case study was carried out. In this illustrative example, the vector files from the Cartographic and Cadastral System of the Municipality of Salvador - BA (SICAD) were the reference data, and their homologous OpenStreetMap (OSM) features were the analysed database. The results obtained are presented in the attributes table. In addition, the spatial distribution of the discrepancies is visualised through the visual variable colour value in a quartile classification. The creation of this toolset corroborates the feasibility of developing more visual, automated and complete interfaces to support users of geospatial data in analysing the quality of the information available, especially when it involves free applications with open-source code. |
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Anuário do Instituto de Geociências (Online) |
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QPEC: QGIS Toolkit for Evaluating Geospatial Data Positional Accuracy according to the Brazilian Cartographic Accuracy StandardPlanimetric positional accuracyQGIS pluginPythonThis paper presents the development of a QGIS plugin to support evaluating the planimetric positional quality for point and linear features based on the metrics established by Brazilian legislation. For this purpose, we used the QGIS environment Graphical Modeler, which consists of an interface to concatenate a series of processes into a single algorithm. The set of tools, called QPEC, allows for performing the statistical tests from the automatic identification of the sample size and discrepancies. In order to demonstrate the implemented functionalities, a case study was carried out. In this illustrative example, the vector files from the Cartographic and Cadastral System of the Municipality of Salvador - BA (SICAD) were the reference data, and their homologous OpenStreetMap (OSM) features were the analysed database. The results obtained are presented in the attributes table. In addition, the spatial distribution of the discrepancies is visualised through the visual variable colour value in a quartile classification. The creation of this toolset corroborates the feasibility of developing more visual, automated and complete interfaces to support users of geospatial data in analysing the quality of the information available, especially when it involves free applications with open-source code.Universidade Federal do Rio de Janeiro2023-04-21info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/vnd.openxmlformats-officedocument.wordprocessingml.documentapplication/vnd.openxmlformats-officedocument.wordprocessingml.documentapplication/vnd.openxmlformats-officedocument.wordprocessingml.documenthttps://revistas.ufrj.br/index.php/aigeo/article/view/5424510.11137/1982-3908_2023_46_54245Anuário do Instituto de Geociências; v. 46 (2023)Anuário do Instituto de Geociências; Vol. 46 (2023)1982-39080101-9759reponame:Anuário do Instituto de Geociências (Online)instname:Universidade Federal do Rio de Janeiro (UFRJ)instacron:UFRJenghttps://revistas.ufrj.br/index.php/aigeo/article/view/54245/pdfhttps://revistas.ufrj.br/index.php/aigeo/article/view/54245/39022https://revistas.ufrj.br/index.php/aigeo/article/view/54245/39092https://revistas.ufrj.br/index.php/aigeo/article/view/54245/39161Copyright (c) 2023 Anuário do Instituto de Geociênciasinfo:eu-repo/semantics/openAccessElias, Elias Nasr NaimGiehl, SamoelAmorim, Fabricio RosaSchmidt, Marcio Augusto ReolonCamboim, Silvana PhilippiFernandes, Vivian de Oliveira2023-04-21T22:47:00Zoai:ojs.pkp.sfu.ca:article/54245Revistahttps://revistas.ufrj.br/index.php/aigeo/indexPUBhttps://revistas.ufrj.br/index.php/aigeo/oaianuario@igeo.ufrj.br||1982-39080101-9759opendoar:2023-04-21T22:47Anuário do Instituto de Geociências (Online) - Universidade Federal do Rio de Janeiro (UFRJ)false |
dc.title.none.fl_str_mv |
QPEC: QGIS Toolkit for Evaluating Geospatial Data Positional Accuracy according to the Brazilian Cartographic Accuracy Standard |
title |
QPEC: QGIS Toolkit for Evaluating Geospatial Data Positional Accuracy according to the Brazilian Cartographic Accuracy Standard |
spellingShingle |
QPEC: QGIS Toolkit for Evaluating Geospatial Data Positional Accuracy according to the Brazilian Cartographic Accuracy Standard Elias, Elias Nasr Naim Planimetric positional accuracy QGIS plugin Python |
title_short |
QPEC: QGIS Toolkit for Evaluating Geospatial Data Positional Accuracy according to the Brazilian Cartographic Accuracy Standard |
title_full |
QPEC: QGIS Toolkit for Evaluating Geospatial Data Positional Accuracy according to the Brazilian Cartographic Accuracy Standard |
title_fullStr |
QPEC: QGIS Toolkit for Evaluating Geospatial Data Positional Accuracy according to the Brazilian Cartographic Accuracy Standard |
title_full_unstemmed |
QPEC: QGIS Toolkit for Evaluating Geospatial Data Positional Accuracy according to the Brazilian Cartographic Accuracy Standard |
title_sort |
QPEC: QGIS Toolkit for Evaluating Geospatial Data Positional Accuracy according to the Brazilian Cartographic Accuracy Standard |
author |
Elias, Elias Nasr Naim |
author_facet |
Elias, Elias Nasr Naim Giehl, Samoel Amorim, Fabricio Rosa Schmidt, Marcio Augusto Reolon Camboim, Silvana Philippi Fernandes, Vivian de Oliveira |
author_role |
author |
author2 |
Giehl, Samoel Amorim, Fabricio Rosa Schmidt, Marcio Augusto Reolon Camboim, Silvana Philippi Fernandes, Vivian de Oliveira |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Elias, Elias Nasr Naim Giehl, Samoel Amorim, Fabricio Rosa Schmidt, Marcio Augusto Reolon Camboim, Silvana Philippi Fernandes, Vivian de Oliveira |
dc.subject.por.fl_str_mv |
Planimetric positional accuracy QGIS plugin Python |
topic |
Planimetric positional accuracy QGIS plugin Python |
description |
This paper presents the development of a QGIS plugin to support evaluating the planimetric positional quality for point and linear features based on the metrics established by Brazilian legislation. For this purpose, we used the QGIS environment Graphical Modeler, which consists of an interface to concatenate a series of processes into a single algorithm. The set of tools, called QPEC, allows for performing the statistical tests from the automatic identification of the sample size and discrepancies. In order to demonstrate the implemented functionalities, a case study was carried out. In this illustrative example, the vector files from the Cartographic and Cadastral System of the Municipality of Salvador - BA (SICAD) were the reference data, and their homologous OpenStreetMap (OSM) features were the analysed database. The results obtained are presented in the attributes table. In addition, the spatial distribution of the discrepancies is visualised through the visual variable colour value in a quartile classification. The creation of this toolset corroborates the feasibility of developing more visual, automated and complete interfaces to support users of geospatial data in analysing the quality of the information available, especially when it involves free applications with open-source code. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-04-21 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://revistas.ufrj.br/index.php/aigeo/article/view/54245 10.11137/1982-3908_2023_46_54245 |
url |
https://revistas.ufrj.br/index.php/aigeo/article/view/54245 |
identifier_str_mv |
10.11137/1982-3908_2023_46_54245 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://revistas.ufrj.br/index.php/aigeo/article/view/54245/pdf https://revistas.ufrj.br/index.php/aigeo/article/view/54245/39022 https://revistas.ufrj.br/index.php/aigeo/article/view/54245/39092 https://revistas.ufrj.br/index.php/aigeo/article/view/54245/39161 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2023 Anuário do Instituto de Geociências info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2023 Anuário do Instituto de Geociências |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf application/vnd.openxmlformats-officedocument.wordprocessingml.document application/vnd.openxmlformats-officedocument.wordprocessingml.document application/vnd.openxmlformats-officedocument.wordprocessingml.document |
dc.publisher.none.fl_str_mv |
Universidade Federal do Rio de Janeiro |
publisher.none.fl_str_mv |
Universidade Federal do Rio de Janeiro |
dc.source.none.fl_str_mv |
Anuário do Instituto de Geociências; v. 46 (2023) Anuário do Instituto de Geociências; Vol. 46 (2023) 1982-3908 0101-9759 reponame:Anuário do Instituto de Geociências (Online) instname:Universidade Federal do Rio de Janeiro (UFRJ) instacron:UFRJ |
instname_str |
Universidade Federal do Rio de Janeiro (UFRJ) |
instacron_str |
UFRJ |
institution |
UFRJ |
reponame_str |
Anuário do Instituto de Geociências (Online) |
collection |
Anuário do Instituto de Geociências (Online) |
repository.name.fl_str_mv |
Anuário do Instituto de Geociências (Online) - Universidade Federal do Rio de Janeiro (UFRJ) |
repository.mail.fl_str_mv |
anuario@igeo.ufrj.br|| |
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1797053535741804544 |