Topological Consistency of Geospatial Data

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Leandro Luiz Silva de França
https://orcid.org/0000-0003-0863-1926
José Luiz Portugal
https://orcid.org/0000-0002-6508-1687

Abstract

For correct analysis and decision making, based on geospatial data, it is essential to attest the data’s reliability and integrity. Regarding Logical Consistency, there are still few standards and research that address the subject in a systematic way, and there is no consensus on the proper procedures for quality control in this category. Consequently, geospatial data producers have several difficulties to ensure the integrity and consistency of their cartographic products, due to inadequate verification of logical relationships, causing rework with repeated and inefficient verifications. This article, therefore, aimed to document concepts inherent to the assessment of topological consistency and present practical examples of validation applied to real data from cartographic production. The application of this research took place in a case study for a Geospatial Vector Data Set (Conjunto de Dados Geoespaciais Vetoriais – CDGV) of the Mapping Project of the State of Bahia, detailing the entire methodological procedure for the topological validation of these data. From the results, there was a considerable number of topological inconsistencies, indicating the need for modernization of validation procedures by geospatial data producers. Regarding the contributions of this work, in addition to the compilation of a theoretical basis on the topological consistency of geospatial data, besides the development of solutions for the verification of inconsistencies with SQL queries based on PostgreSQL free software and its spatial extension PostGIS.

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How to Cite
FRANÇA, L. L. S. de; PORTUGAL, J. L. Topological Consistency of Geospatial Data. Brazilian Journal of Cartography, [S. l.], v. 74, n. 3, p. 480–498, 2022. DOI: 10.14393/rbcv74n3-61508. Disponível em: https://seer.ufu.br/index.php/revistabrasileiracartografia/article/view/61508. Acesso em: 22 nov. 2024.
Section
Review Articles

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