Detecting Change in Snapshot Sequences

  • Mingzheng Shi
  • Stephan Winter
Conference paper

DOI: 10.1007/978-3-642-15300-6_16

Part of the Lecture Notes in Computer Science book series (LNCS, volume 6292)
Cite this paper as:
Shi M., Winter S. (2010) Detecting Change in Snapshot Sequences. In: Fabrikant S.I., Reichenbacher T., van Kreveld M., Schlieder C. (eds) Geographic Information Science. GIScience 2010. Lecture Notes in Computer Science, vol 6292. Springer, Berlin, Heidelberg

Abstract

Wireless sensor networks are deployed to monitor dynamic geographic phenomena, or objects, over space and time. This paper presents a new spatiotemporal data model for dynamic areal objects in sensor networks. Our model supports for the first time the analysis of change in sequences of snapshots that are captured by different granularity of observations, and our model allows both incremental and non-incremental changes. This paper focuses on detecting qualitative spatial changes, such as merge and split of areal objects. A decentralized algorithm is developed, such that spatial changes can be efficiently detected by in-network aggregation of decentralized datasets.

Keywords

wireless sensor networks spatiotemporal data models decentralized algorithms qualitative spatial changes 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Mingzheng Shi
    • 1
  • Stephan Winter
    • 1
  1. 1.Department of GeomaticsUniversity of MelbourneVictoriaAustralia

Personalised recommendations