Positional Accuracy in Cartographic Data Using Linear Features Methods: Final Points, Intermediate Points, Generated Point, Vertex Influence, Double Buffer Normalization and Fuzziness Factor

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Juliette Zanetti
https://orcid.org/0000-0001-6816-4587
Afonso de Paula dos Santos
http://orcid.org/0000-0001-7248-4524
Nilcilene das Graças Medeiros
https://orcid.org/0000-0003-0839-3729
Júlio César de Oliveira
http://orcid.org/0000-0003-0894-5597

Abstract

In recent years, the use of linear features has been frequently investigated in cartography quality control, and several methods have been proposed to assess positional accuracy. In this sense, the present work aimed to link the tolerances defined in Decree nº 89.817, and the Technical Specification for Quality Control of Spatial Data (ET-CQDG) in the methods of linear features: End points, Intermediate Points, Generated Point and in a proposed adaptation to the Fuzziness Factor method. In the end, such methods were compared with the linear feature methods already applied in Brazil, which are: Influence of the Vertex and Normalization of the Double Buffer. For this purpose, the planimetric positional accuracy of an orthomosaic in the municipality of Viçosa-MG was evaluated, where the results obtained showed that the methods, Final Points, Vertex Influence, Factor Fuzziness and the Buffer Double normalization method obtained classification Class A planimetric scale for the 1: 1,000 scale. The Intermediate Points and Generated Point methods, on the other hand, presented Class B in the 1: 1,000 scale.

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How to Cite
ZANETTI, J.; SANTOS, A. de P. dos; MEDEIROS, N. das G.; OLIVEIRA, J. C. de. Positional Accuracy in Cartographic Data Using Linear Features Methods: Final Points, Intermediate Points, Generated Point, Vertex Influence, Double Buffer Normalization and Fuzziness Factor. Brazilian Journal of Cartography, [S. l.], v. 73, n. 1, p. 278–295, 2021. DOI: 10.14393/rbcv73n1-54226. Disponível em: https://seer.ufu.br/index.php/revistabrasileiracartografia/article/view/54226. Acesso em: 24 nov. 2024.
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Original Articles

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