QPEC: QGIS Toolkit for Evaluating Geospatial Data Positional Accuracy according to the Brazilian Cartographic Accuracy Standard

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 c...

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Detalles Bibliográficos
Autores: Elias, Elias Nasr Naim, Giehl, Samoel, Amorim, Fabricio Rosa, Schmidt, Marcio Augusto Reolon, Camboim, Silvana Philippi, Fernandes, Vivian de Oliveira
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2023
País:Brasil
Institución:Universidade Federal do Rio de Janeiro (UFRJ)
Repositorio:Anuário do Instituto de Geociências (Online)
Idioma:inglés
OAI Identifier:oai:ojs.pkp.sfu.ca:article/54245
Acceso en línea:https://revistas.ufrj.br/index.php/aigeo/article/view/54245
Access Level:acceso abierto
Palabra clave:Planimetric positional accuracy
QGIS plugin
Python
Descripción
Sumario: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.