Synchronising geometric representations for map mashups using relative positioning and Linked Data

Weiming Huang, Ali Mansourian, Ehsan Abdolmajidi, Haiqi Xu, Lars Harrie

Research output: Contribution to journalArticlepeer-review

9 Citations (SciVal)

Abstract

Map mashups, as a common way of presenting geospatial information on the Web, are generally created by spatially overlaying thematic information on top of various base maps. This simple overlay approach often raises geometric deficiencies due to geometric uncertainties in the data. This issue is particularly apparent in a multi-scale context because the thematic data seldom have synchronised level of detail with the base map. In this study, we propose, develop, implement and evaluate a relative positioning approach based on shared geometries and relative coordinates to synchronise geometric representations for map mashups through several scales. To realise the relative positioning between datasets, we adopt a Linked Data–based technical framework in which the data are organised according to ontologies that are designed based on the GeoSPARQL vocabulary. A prototype system is developed to demonstrate the feasibility and usability of the relative positioning approach. The results show that the approach synchronises and integrates the geometries of thematic data and the base map effectively, and the thematic data are automatically tailored for multi-scale visualisation. The proposed framework can be used as a new way of modelling geospatial data on the Web, with merits in terms of both data visualisation and querying.

Original languageEnglish
Pages (from-to)1117-1137
JournalInternational Journal of Geographical Information Science
Volume32
Issue number6
Early online date2018 Mar 1
DOIs
Publication statusPublished - 2018 Jun 3

Subject classification (UKÄ)

  • Other Earth and Related Environmental Sciences

Keywords

  • geometry synchronisation
  • Linked Data
  • Map mashups
  • multiple representation
  • relative positioning

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