Spatial Interpolation of Streaming Geosensor Network Data in the RISER System View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2015

AUTHORS

Xu Zhong , Allison Kealy , Guy Sharon , Matt Duckham

ABSTRACT

Managing the data generated by emerging spatiotemporal data sources, such as geosensor networks, presents a growing challenge to traditional, offline GIS architectures. This paper explores the development of an end-to-end system for near real-time monitoring of environmental variables related to wildfire hazard, called RISER. The system is built upon a geosensor network and web-GIS technologies, connected by a stream-processing system. Aside from exploring the system architecture, this paper focuses specifically on the important role of stream processing as a bridge between data capture and web GIS, and as a spatial analysis engine. The paper highlights the compromise between efficiency and accuracy in spatiotemporal stream processing that must often be struck in the stream operator design. Using the specific example of spatial interpolation operators, the impact of changes to the configurations of spatial and temporal windows on the accuracy and efficiency of different spatial interpolation methods is evaluated. More... »

PAGES

161-177

References to SciGraph publications

  • 2013. Real-Time Data Analytics in Sensor Networks in MANAGING AND MINING SENSOR DATA
  • 2010-08. MG-join: detecting phenomena and their correlation in high dimensional data streams in DISTRIBUTED AND PARALLEL DATABASES
  • 1997-08. Parallel Processing for Terrain Analysis in GIS: Visibility as a Case Study in GEOINFORMATICA
  • 1977. Splines minimizing rotation-invariant semi-norms in Sobolev spaces in CONSTRUCTIVE THEORY OF FUNCTIONS OF SEVERAL VARIABLES
  • 2006-07. Fast and exact out-of-core and distributed k-means clustering in KNOWLEDGE AND INFORMATION SYSTEMS
  • Book

    TITLE

    Web and Wireless Geographical Information Systems

    ISBN

    978-3-319-18250-6
    978-3-319-18251-3

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-319-18251-3_10

    DOI

    http://dx.doi.org/10.1007/978-3-319-18251-3_10

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1001697747


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