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Authors: Aniss Zebiri 1 ; Dominique Béréziat 1 ; Etienne Huot 2 and Isabelle Herlin 3

Affiliations: 1 Sorbonne Université, CNRS, Laboratoire d’Informatique de Paris 6 and France ; 2 Université de Versailles Saint-Quentin-en-Yvelines, LATMOS/IPSL and France ; 3 Inria and France

Keyword(s): Rain Forecasting, Weather Radar, Multiscale Image, Image Assimilation, Motion Estimation.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Motion, Tracking and Stereo Vision ; Optical Flow and Motion Analyses ; Video Surveillance and Event Detection

Abstract: Rainfall forecasting is a major issue for anticipating severe meteorological events and for agriculture management. Weather radar imaging has been identified in the literature as the best way to measure rainfall on a large domain, with a fine spatial and temporal resolution. This paper describes two methods allowing to improve rain nowcast from radar images at two different scales. These methods are further compared to an operational chain relying on only one type of radar observation. The comparison is led with regional and local criteria. For both, significant improvements are quantified compared to the original method.

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Paper citation in several formats:
Zebiri, A.; Béréziat, D.; Huot, E. and Herlin, I. (2019). Rain Nowcasting from Multiscale Radar Images. In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP; ISBN 978-989-758-354-4; ISSN 2184-4321, SciTePress, pages 892-900. DOI: 10.5220/0007566908920900

@conference{visapp19,
author={Aniss Zebiri. and Dominique Béréziat. and Etienne Huot. and Isabelle Herlin.},
title={Rain Nowcasting from Multiscale Radar Images},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP},
year={2019},
pages={892-900},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007566908920900},
isbn={978-989-758-354-4},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP
TI - Rain Nowcasting from Multiscale Radar Images
SN - 978-989-758-354-4
IS - 2184-4321
AU - Zebiri, A.
AU - Béréziat, D.
AU - Huot, E.
AU - Herlin, I.
PY - 2019
SP - 892
EP - 900
DO - 10.5220/0007566908920900
PB - SciTePress

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