Indexing Fuzzy Spatiotemporal Data for Efficient Querying: A Meteorological Application

Aziz Sozer, Adnan Yazici, Halit Oguztuzun

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)


Spatiotemporal data, in particular fuzzy and complex spatial objects representing geographic entities and relations, is a topic of great importance in geographic information systems and environmental data management systems. For database researchers, modeling and designing a database of fuzzy spatiotemporal data and querying such a database efficiently have been challenging issues due to complex spatial features and uncertainty involved. This paper presents an integrated approach to modeling, indexing, and efficiently querying spatiotemporal data related to fuzzy spatial and complex objects and spatial relations. As our case study, we design and implement a meteorological database application that involves fuzzy spatial and complex objects, and a spatiotemporal index structure, and supports various types of spatial queries including fuzzy spatiotemporal queries. Our implementation is based on an intelligent database system architecture that combines a fuzzy object-oriented database with a fuzzy knowledge base.

Original languageEnglish
Article number6919333
Pages (from-to)1399-1413
Number of pages15
JournalIEEE Transactions on Fuzzy Systems
Issue number5
Publication statusPublished - Oct 1 2015


  • Complex spatial object
  • fuzzy object
  • knowledge base
  • meteorological database application
  • object-oriented databases
  • spatiotemporal data
  • spatiotemporal indexing and querying

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics

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