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Classification of radar echoes using fractal geometry

Author

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  • Azzaz, Nafissa
  • Haddad, Boualem

Abstract

This paper deals with the discrimination between the precipitation echoes and the ground echoes in meteorological radar images using fractal geometry. This study aims to improve the measurement of precipitations by weather radars. For this, we considered three radar sites: Bordeaux (France), Dakar (Senegal) and Me lbourne (USA). We showed that the fractal dimension based on contourlet and the fractal lacunarity are pertinent to discriminate between ground and precipitation echoes. We also demonstrated that the ground echoes have a multifractal structure but the precipitations are more homogeneous than ground echoes whatever the prevailing climate. Thereby, we developed an automatic classification system of radar using a graphic interface. This interface, based on the fractal geometry makes possible the identification of radar echoes type in real time. This system can be inserted in weather radar for the improvement of precipitation estimations.

Suggested Citation

  • Azzaz, Nafissa & Haddad, Boualem, 2017. "Classification of radar echoes using fractal geometry," Chaos, Solitons & Fractals, Elsevier, vol. 98(C), pages 130-144.
    • Handle: RePEc:eee:chsofr:v:98:y:2017:i:c:p:130-144
    DOI: 10.1016/j.chaos.2017.03.017
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    Cited by:

    1. Kassel Hingee & Adrian Baddeley & Peter Caccetta & Gopalan Nair, 2019. "Computation of Lacunarity from Covariance of Spatial Binary Maps," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 24(2), pages 264-288, June.

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