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Classification of rainfall radar images using the scattering transform.

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Title: Classification of rainfall radar images using the scattering transform.
Authors: Lagrange, Mathieu1, Andrieu, Hervé2 herve.andrieu@ifsttar.fr, Emmanuel, Isabelle2, Busquets, Gerard1, Loubrié, Stéphane1
Source: Journal of Hydrology. Jan2018, Vol. 556, p972-979. 8p.
Subjects: Rainfall, Radar meteorology, Classification algorithms, Scattering (Mathematics), Approximation theory
Abstract: The classification of rainfall fields has mainly focused on the split between convective and stratiform rainfall fields. In the present case study, the wavelet-based scattering transform is used to classify rainfall events observed by a weather radar. This very recent method has, to the best of the authors’ knowledge, not yet been applied for such a purpose. This method considers the spatial properties of rainfall radar images. This case study regroups 34 rainfall periods recorded over the Nantes region (western France) during 23 days in both 2009 and 2012. These periods display different characteristics in terms of duration and type of rainfall field. A reference configuration of the scattering transform has been evaluated and compared to various configurations in order to approximate the application conditions most appropriate to this case study. This evaluation is performed by a leave-one-out cross validation. A global accuracy of 93.5% of well classified images is obtained in the reference conditions which is an encouraging result. The temporal sampling of the rainfall fields is an important aspect of the classification process. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Hydrology is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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Header DbId: egs
DbLabel: Engineering Source
An: 126977388
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: <searchLink fieldCode="DE" term="%22Rainfall%22">Rainfall</searchLink><br /><searchLink fieldCode="DE" term="%22Radar+meteorology%22">Radar meteorology</searchLink><br /><searchLink fieldCode="DE" term="%22Classification+algorithms%22">Classification algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Scattering+%28Mathematics%29%22">Scattering (Mathematics)</searchLink><br /><searchLink fieldCode="DE" term="%22Approximation+theory%22">Approximation theory</searchLink>
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  Data: The classification of rainfall fields has mainly focused on the split between convective and stratiform rainfall fields. In the present case study, the wavelet-based scattering transform is used to classify rainfall events observed by a weather radar. This very recent method has, to the best of the authors’ knowledge, not yet been applied for such a purpose. This method considers the spatial properties of rainfall radar images. This case study regroups 34 rainfall periods recorded over the Nantes region (western France) during 23 days in both 2009 and 2012. These periods display different characteristics in terms of duration and type of rainfall field. A reference configuration of the scattering transform has been evaluated and compared to various configurations in order to approximate the application conditions most appropriate to this case study. This evaluation is performed by a leave-one-out cross validation. A global accuracy of 93.5% of well classified images is obtained in the reference conditions which is an encouraging result. The temporal sampling of the rainfall fields is an important aspect of the classification process. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Hydrology is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1016/j.jhydrol.2016.06.063
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 8
        StartPage: 972
    Subjects:
      – SubjectFull: Rainfall
        Type: general
      – SubjectFull: Radar meteorology
        Type: general
      – SubjectFull: Classification algorithms
        Type: general
      – SubjectFull: Scattering (Mathematics)
        Type: general
      – SubjectFull: Approximation theory
        Type: general
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      – TitleFull: Classification of rainfall radar images using the scattering transform.
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            NameFull: Lagrange, Mathieu
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            NameFull: Andrieu, Hervé
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            NameFull: Emmanuel, Isabelle
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            NameFull: Busquets, Gerard
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            NameFull: Loubrié, Stéphane
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            – D: 01
              M: 01
              Text: Jan2018
              Type: published
              Y: 2018
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              Value: 556
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