A Method for Matching Crowd-sourced and Authoritative Geospatial Data

Heshan Du, Natasha Alechina, Michael Jackson, Glen Hart

Research output: Journal PublicationArticlepeer-review

16 Citations (Scopus)

Abstract

A method for matching crowd-sourced and authoritative geospatial data is presented. A level of tolerance is defined as an input parameter as some difference in the geometry representation of a spatial object is to be expected. The method generates matches between spatial objects using location information and lexical information, such as names and types, and verifies consistency of matches using reasoning in qualitative spatial and description logic. We test the method by matching geospatial data from OpenStreetMap and the national mapping agencies of Great Britain and France. We also analyze how the level of tolerance affects the precision and recall of matching results for the same geographic area using 12 different levels of tolerance within a range of 1 to 80 m. The generated matches show potential in helping enrich and update geospatial data.

Original languageEnglish
Pages (from-to)406-427
Number of pages22
JournalTransactions in GIS
Volume21
Issue number2
DOIs
Publication statusPublished - 1 Apr 2017
Externally publishedYes

ASJC Scopus subject areas

  • Earth and Planetary Sciences (all)

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