Detecting Weather Radar Clutter by Information Fusion With Satellite Images and Numerical Weather Prediction Model Output

Thomas Bøvith; Allan Aasbjerg Nielsen; Lars Kai Hansen; Rashpal S. Gill; Søren Overgaard

doi:10.1109/IGARSS.2006.136

Detecting Weather Radar Clutter by Information Fusion With Satellite Images and Numerical Weather Prediction Model Output

Thomas Bøvith, Allan Aasbjerg Nielsen, Lars Kai Hansen, Rashpal S. Gill, Søren Overgaard

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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Abstract

A method for detecting clutter in weather radar images by information fusion is presented. Radar data, satellite images, and output from a numerical weather prediction model are combined and the radar echoes are classified using supervised classification. The presented method uses indirect information on precipitation in the atmosphere from Meteosat-8 multispectral images and near-surface temperature estimates from the DMI-HIRLAM-S05 numerical weather prediction model. Alternatively, an operational nowcasting product called 'Precipitating Clouds' based on Meteosat-8 input is used. A scale-space ensemble method is used for classification and the clutter detection method is illustrated on a case of severe sea clutter contaminated radar data. Detection accuracies above 90 % are achieved and using an ensemble classification method the error rate is reduced by 40 %.

Original language	English
Title of host publication	Proceedings of the IEEE Geoscience and Remote Sensing Symposium (IGARSS) 2006
Publisher	IEEE
Publication date	2006
ISBN (Print)	0-7803-9510-7
DOIs	https://doi.org/10.1109/IGARSS.2006.136
Publication status	Published - 2006
Event	2006 IEEE International Geoscience and Remote Sensing Symposium - Denver, United States Duration: 31 Jul 2006 → 4 Aug 2006 http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=4087812

Conference

Conference	2006 IEEE International Geoscience and Remote Sensing Symposium
Country/Territory	United States
City	Denver
Period	31/07/2006 → 04/08/2006
Internet address	http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=4087812

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IEEE International Conference on Geoscience and Remote Sensing Symposium, 2006. IGARSS 2006.

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@inproceedings{3b4f5805ee244a65a62d594956f19aca,

title = "Detecting Weather Radar Clutter by Information Fusion With Satellite Images and Numerical Weather Prediction Model Output",

abstract = "A method for detecting clutter in weather radar images by information fusion is presented. Radar data, satellite images, and output from a numerical weather prediction model are combined and the radar echoes are classified using supervised classification. The presented method uses indirect information on precipitation in the atmosphere from Meteosat-8 multispectral images and near-surface temperature estimates from the DMI-HIRLAM-S05 numerical weather prediction model. Alternatively, an operational nowcasting product called 'Precipitating Clouds' based on Meteosat-8 input is used. A scale-space ensemble method is used for classification and the clutter detection method is illustrated on a case of severe sea clutter contaminated radar data. Detection accuracies above 90 % are achieved and using an ensemble classification method the error rate is reduced by 40 %.",

author = "Thomas B{\o}vith and Nielsen, {Allan Aasbjerg} and Hansen, {Lars Kai} and Gill, {Rashpal S.} and S{\o}ren Overgaard",

note = "IEEE International Conference on Geoscience and Remote Sensing Symposium, 2006. IGARSS 2006.; 2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2006 ; Conference date: 31-07-2006 Through 04-08-2006",

year = "2006",

doi = "10.1109/IGARSS.2006.136",

language = "English",

isbn = "0-7803-9510-7",

booktitle = "Proceedings of the IEEE Geoscience and Remote Sensing Symposium (IGARSS) 2006",

publisher = "IEEE",

address = "United States",

url = "http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=4087812",

}

Bøvith, T, Nielsen, AA , Hansen, LK, Gill, RS & Overgaard, S 2006, Detecting Weather Radar Clutter by Information Fusion With Satellite Images and Numerical Weather Prediction Model Output. in Proceedings of the IEEE Geoscience and Remote Sensing Symposium (IGARSS) 2006. IEEE, 2006 IEEE International Geoscience and Remote Sensing Symposium, Denver, Colorado, United States, 31/07/2006. https://doi.org/10.1109/IGARSS.2006.136

Detecting Weather Radar Clutter by Information Fusion With Satellite Images and Numerical Weather Prediction Model Output. / Bøvith, Thomas; Nielsen, Allan Aasbjerg ; Hansen, Lars Kai et al.
Proceedings of the IEEE Geoscience and Remote Sensing Symposium (IGARSS) 2006. IEEE, 2006.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

TY - GEN

T1 - Detecting Weather Radar Clutter by Information Fusion With Satellite Images and Numerical Weather Prediction Model Output

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AU - Overgaard, Søren

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N2 - A method for detecting clutter in weather radar images by information fusion is presented. Radar data, satellite images, and output from a numerical weather prediction model are combined and the radar echoes are classified using supervised classification. The presented method uses indirect information on precipitation in the atmosphere from Meteosat-8 multispectral images and near-surface temperature estimates from the DMI-HIRLAM-S05 numerical weather prediction model. Alternatively, an operational nowcasting product called 'Precipitating Clouds' based on Meteosat-8 input is used. A scale-space ensemble method is used for classification and the clutter detection method is illustrated on a case of severe sea clutter contaminated radar data. Detection accuracies above 90 % are achieved and using an ensemble classification method the error rate is reduced by 40 %.

AB - A method for detecting clutter in weather radar images by information fusion is presented. Radar data, satellite images, and output from a numerical weather prediction model are combined and the radar echoes are classified using supervised classification. The presented method uses indirect information on precipitation in the atmosphere from Meteosat-8 multispectral images and near-surface temperature estimates from the DMI-HIRLAM-S05 numerical weather prediction model. Alternatively, an operational nowcasting product called 'Precipitating Clouds' based on Meteosat-8 input is used. A scale-space ensemble method is used for classification and the clutter detection method is illustrated on a case of severe sea clutter contaminated radar data. Detection accuracies above 90 % are achieved and using an ensemble classification method the error rate is reduced by 40 %.

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ER -

Detecting Weather Radar Clutter by Information Fusion With Satellite Images and Numerical Weather Prediction Model Output

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