Positional Accuracy Assessment of the VGI Data from OpenStreetMap  - Case Study: Federal University of Bahia Campus in Brazil

Elias, Elias Nasr Naim; Fernandes, Vivian de Oliveira; Junior, Mauro José Alixandrini

doi:10.5220/0006707702310238

Cited by 1 publication

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“…As the results published in many countries reflect values inherent to each region, the statistical or data science methodology used to measure these errors may also be important at the time of generating the metrics, so it is recommended to continue exploring methods to standardize criteria for measuring and judging the quality of VGI (Elias et al, 2018).…”

Section: Thematic Accuracymentioning

confidence: 99%

Evaluation of the quality of the Voluntary Geographic Information for the road network in Bogotá D.C

Beltran

Darghan

Aljure

et al. 2022

CIG

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The production of Voluntary Geographic Information has been growing considerably and continues to be an active area of research. However, the lack of knowledge about the quality of information generated on a voluntary and participatory basis raises challenges and questions about its use. In the review carried out for the Colombian case, no studies related to the subject were identified; consequently, this study is presented on the evaluation of the quality of this type of information on the road network of Bogotá with respect to completeness, positional accuracy and thematic accuracy. This evaluation was carried out by means of a semi-automatic process that uses a mobile buffer and the centroid of the roads to make the corresponding comparisons between two data sources. The results found reveal that the method used allowed to compare up to 85.0% of the data, and that the OpenStreetMap mesh has a completeness of 85.4%, over the entire area of Bogotá. A positional accuracy of 3.98 m and a thematic accuracy related to the percentage of error in the attributes: Road hierarchy, direction of flow and road naming of 35.8%, 15.0% and 34.6% respectively. The quality evaluated through completeness, positional and thematic accuracy in synergistic terms is deficient with respect to the minimum quality levels established in the standard data model, however, the evaluation for each of the attributes shows an acceptable quality in terms of completeness and thematic accuracy.

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Section: Thematic Accuracymentioning

confidence: 99%