AN EXPERIMENT ON DISTANCE METRICS USED FOR ROAD MATCHING IN DATA INTEGRATION
Abstract
Decision makers and researchers need datasets from different sources to analyze, combine, or create new spatial datasets. The same entity may be represented with different geometries, topologies, and attributes in different datasets due to differences in production, such as projection, scale, accuracy, purpose, and date. The geometries, topologies, and attributes of objects are often used when combining and integrating the datasets from different sources. Matching spatial datasets is one of the most important phases of data integration. Many algorithms have been developed to match datasets using several parameters inspired by geometric, topological, and attribute similarities. They generally find the similarities between objects in different datasets and create relations between each object in order to analyze, combine, update, and transfer data. The differences in geometries, topologies, and attributes make the matching process difficult. The research problem is the critical selection of similarity parameters to ensure the satisfactory matching results. The scope of this paper was limited with distance metrics. In this study, it was aimed to determine the suitable distance metrics measured from point to point and from point to line, which are widely used as parameters in road matching. Two road datasets in different databases were automatically matched using these metrics by employing a plugin of an open desktop software. Automatic matching results were compared to manual matching results to determine the success of each matching process. Consequently, it was shown that none of these metrics for road matching was adequate on its own. However, the distance between centroids of roads and Hausdorff distances were more satisfactory.
Keywords
References
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Details
Primary Language
English
Subjects
Engineering
Journal Section
Research Article
Publication Date
December 1, 2016
Submission Date
April 8, 2016
Acceptance Date
November 21, 2016
Published in Issue
Year 2016 Volume: 34 Number: 4
APA
Hacar, M., & Gökgöz, T. (2016). AN EXPERIMENT ON DISTANCE METRICS USED FOR ROAD MATCHING IN DATA INTEGRATION. Sigma Journal of Engineering and Natural Sciences, 34(4), 527-542. https://izlik.org/JA92BX67CW
AMA
1.Hacar M, Gökgöz T. AN EXPERIMENT ON DISTANCE METRICS USED FOR ROAD MATCHING IN DATA INTEGRATION. SIGMA. 2016;34(4):527-542. https://izlik.org/JA92BX67CW
Chicago
Hacar, Müslüm, and Türkay Gökgöz. 2016. “AN EXPERIMENT ON DISTANCE METRICS USED FOR ROAD MATCHING IN DATA INTEGRATION”. Sigma Journal of Engineering and Natural Sciences 34 (4): 527-42. https://izlik.org/JA92BX67CW.
EndNote
Hacar M, Gökgöz T (December 1, 2016) AN EXPERIMENT ON DISTANCE METRICS USED FOR ROAD MATCHING IN DATA INTEGRATION. Sigma Journal of Engineering and Natural Sciences 34 4 527–542.
IEEE
[1]M. Hacar and T. Gökgöz, “AN EXPERIMENT ON DISTANCE METRICS USED FOR ROAD MATCHING IN DATA INTEGRATION”, SIGMA, vol. 34, no. 4, pp. 527–542, Dec. 2016, [Online]. Available: https://izlik.org/JA92BX67CW
ISNAD
Hacar, Müslüm - Gökgöz, Türkay. “AN EXPERIMENT ON DISTANCE METRICS USED FOR ROAD MATCHING IN DATA INTEGRATION”. Sigma Journal of Engineering and Natural Sciences 34/4 (December 1, 2016): 527-542. https://izlik.org/JA92BX67CW.
JAMA
1.Hacar M, Gökgöz T. AN EXPERIMENT ON DISTANCE METRICS USED FOR ROAD MATCHING IN DATA INTEGRATION. SIGMA. 2016;34:527–542.
MLA
Hacar, Müslüm, and Türkay Gökgöz. “AN EXPERIMENT ON DISTANCE METRICS USED FOR ROAD MATCHING IN DATA INTEGRATION”. Sigma Journal of Engineering and Natural Sciences, vol. 34, no. 4, Dec. 2016, pp. 527-42, https://izlik.org/JA92BX67CW.
Vancouver
1.Müslüm Hacar, Türkay Gökgöz. AN EXPERIMENT ON DISTANCE METRICS USED FOR ROAD MATCHING IN DATA INTEGRATION. SIGMA [Internet]. 2016 Dec. 1;34(4):527-42. Available from: https://izlik.org/JA92BX67CW