Defining geospatial data fusion methods based on topological relationships

D. S. Ahn, J. H. Park, J. Y. Lee

Research output: Contribution to journalConference articlepeer-review

5 Scopus citations

Abstract

Currently, geospatial datasets are produced in various models and formats in accordance with the spatial scale of the real world such as ground/ surface/underground or indoor/outdoor. The location-based services application also uses the optimal data model and format for each purpose. Therefore, there are various geospatial dataset for representing features of the same space. Various geospatial data on same object cause problems with the financial problems and the suitability of the data. In the paper, we reviewed how to integrate existing geospatial data to utilize geospatial data constructed in different models and formats. There are four main ways to fuse existing geospatial information. The existing geospatial data fusion methods consist of a method through geometry data conversion, a method through the aspect of visualization, a method based on attribute data, and a method using topological relationships. Based on this review, we defined a geospatial data fusion method on topological relationships, which is a method considering topological relationship between geospatial objects. In this method, the topological relationship of objects uses the basic concept of IndoorGML.

Original languageEnglish
Pages (from-to)317-319
Number of pages3
JournalInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
Volume42
Issue number4/W9
DOIs
StatePublished - 26 Oct 2018
Event2018 International Conference on Geomatic and Geospatial Technology: Geospatial and Disaster Risk Management, GGT 2018 - Kuala Lumpur, Malaysia
Duration: 3 Sep 20185 Sep 2018

Keywords

  • 3D GIS
  • Anchor Node
  • Geospatial Data Fusion
  • IndoorGML
  • Topological Data Model

Fingerprint

Dive into the research topics of 'Defining geospatial data fusion methods based on topological relationships'. Together they form a unique fingerprint.

Cite this