Author ORCID Identifier

https://orcid.org/ 0000-0002-9868-8338

Document Type

Other

Rights

Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence

Disciplines

Computer Sciences, Geosciences, (multidisciplinary)

Abstract

To get accurate information returned from location-based services (e.g., LBS info on nearby restaurants, retail outlets, points-of-interest, etc.), the underlying map (spatial data) must be up-to-date. However, the built environment (e.g., roads, buildings, bike paths, etc.) can change quickly over time, either through planned developments or as the result of natural/manmade disasters. The problem is that keeping online crowdsourced maps like Open Street Map (OSM) updated is still very much a manual process. As such, it can take considerable time to sync the online maps used by LBS with up-to-date spatial data in "real-time".

Our case study considers the Grangegorman area in Dublin city. It is a green/brownfield site that has seen much infrastructure change in the past decade due to its renewal as the new home for Technological University Dublin (TU Dublin). New buildings have been built, car parks have changed size/location, and new roads have been constructed due to the recent expansion. Figure 2 and Figure 3 illustrate the difference/mismatch between the current OSM crowdsourced (vector) map and Google's satellite (raster) view of the Grangegorman area.

Funder

Technological University Dublin College of Arts and Tourism

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