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A terrain classifier to improve the inclusion of objects in the collaborative mapping tool OpenStreetMap

Published: 29 January 2021 Publication History

Abstract

In Geographic Information Systems (GIS) and, more specifically in the case of Volunteered Geographic Information (VGI), users actively participate in the processes of data inclusion, edition and deletion. Thus, the issue of data quality becomes a central topic, since it is essential to ascertain if some dimensions are being successfully achieved, such as accuracy, logical consistency, and completeness of the information within these types of system. In this context, the present paper develops the application QualiOSM, with the purpose of assisting users in the tasks of including and editing objects in the collaborative mapping tool OpenStreetMap (OSM). This paper focuses on the implementation of a terrain classifier, which was developed using the parallelepiped classifier technique and proved to be useful especially in identifying buildings of various shapes, contributing to a significant improvement in data consistency of the OSM platform.

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  1. A terrain classifier to improve the inclusion of objects in the collaborative mapping tool OpenStreetMap

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    EATIS '20: Proceedings of the 10th Euro-American Conference on Telematics and Information Systems
    November 2020
    388 pages
    ISBN:9781450377119
    DOI:10.1145/3401895
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 29 January 2021

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    Author Tags

    1. computational systems
    2. data quality
    3. geographic information systems
    4. geoprocessing
    5. quality dimensions

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    Overall Acceptance Rate 17 of 64 submissions, 27%

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