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Comparison of Squall Line Positioning Methods Using Radar Data

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Knowledge-Based Intelligent Information and Engineering Systems (KES 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4253))

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Abstract

Squall lines are strong indicators of potential severe weather. Yet, automated positioning and tracking algorithms are not common. We propose three different ways to model and identify squall lines using radar images. The three methods are ellipse fitting, Hough transform, and the use of a genetic algorithm-based framework. They model a squall line as an ellipse, a straight line, and adjoining segments of arc respectively. We compare the advantages and limitations of each method in terms of speed, flexibility, stability and sensitivity to parameter settings. It is found that ellipse fitting is the most efficient, followed by Hough transform. Both methods lack flexibility and stability. The genetic algorithm-based framework is stable, has flexibility in modelling and analysis, but comes with a cost of efficiency. The proposed methods provide independent and objective information sources to assist weather forecast.

The authors are thankful to the Hong Kong Observatory for the provision of data and expert advices.

An erratum to this chapter is available at http://dx.doi.org/10.1007/11893011_163.

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Authors and Affiliations

  1. Dept. of Computer Science, The University of Hong Kong, Pokfulam, Hong Kong

    Ka Yan Wong & Chi Lap Yip

Authors
  1. Ka Yan Wong
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  2. Chi Lap Yip
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Editor information

Editors and Affiliations

  1. School of Design, Engineering and Computing, Bournemouth University, UK

    Bogdan Gabrys

  2. Centre for SMART Systems, School of Environment and Technology, University of Brighton, BN2 4GJ, Brighton, UK

    Robert J. Howlett

  3. School of Electrical and Information Engineering, Knowledge Based Intelligent Engineering Systems Centre, University of South Australia, Mawson Lakes, 5095, SA, Australia

    Lakhmi C. Jain

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© 2006 Springer-Verlag Berlin Heidelberg

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Wong, K.Y., Yip, C.L. (2006). Comparison of Squall Line Positioning Methods Using Radar Data. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2006. Lecture Notes in Computer Science(), vol 4253. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893011_35

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  • DOI: https://doi.org/10.1007/11893011_35

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-46542-3

  • Online ISBN: 978-3-540-46544-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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