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...
| Authors: | , , , , , |
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| Format: | article |
| Status: | Published version |
| Publication Date: | 2023 |
| Country: | Brasil |
| Institution: | Universidade Federal do Rio de Janeiro (UFRJ) |
| Repository: | Anuário do Instituto de Geociências (Online) |
| Language: | English |
| OAI Identifier: | oai:ojs.pkp.sfu.ca:article/54245 |
| Online Access: | https://revistas.ufrj.br/index.php/aigeo/article/view/54245 |
| Access Level: | Open access |
| Keyword: | Planimetric positional accuracy QGIS plugin Python |
| Summary: | 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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