A probabilistic theory-based matching method

Xiao Hua Tong, Su Su Deng, Wen Zhong Shi

Research output: Journal article publicationJournal articleAcademic researchpeer-review

39 Citations (Scopus)

Abstract

The conflation of geographic: datasets is one of the key technologies in the front research area of spatial data capture and integration in Geographic Information Systems ( GIS) Map conflation is a complex process of matching and merging map data. Because various reasons relate to map data discrepancies, a great amount of uncertainties exist during the process. In the first step, selecting appropriate thresholds and handling one-many or many-many matching relationships are two difficulties in feature matching, which predetermines following map merging step.This paper proposed a probabilistic method for feature matching, which fuses a variety of criteria to calculate the matching probability. The feature pair with the highest probability can be determined to be matched. This method avoids selecting thresholds and attempts to resolve one-many and many-many matching relationship.
Original languageChinese (Simplified)
Pages (from-to)210-217
Number of pages8
JournalActa Geodaetica et Cartographica Sinica
Volume36
Issue number2
Publication statusPublished - 1 Dec 2007

Keywords

  • Feature matching
  • Map conflation
  • Multi-indicators fusion
  • Probabilistic theory

ASJC Scopus subject areas

  • Earth and Planetary Sciences(all)

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