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Conference paper

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 — 2006, pp. 511-514
From

Department of Informatics and Mathematical Modeling, Technical University of Denmark1

Image Analysis and Computer Graphics, Department of Informatics and Mathematical Modeling, Technical University of Denmark2

Cognitive Systems, Department of Informatics and Mathematical Modeling, Technical University of Denmark3

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 %.

Language: English
Publisher: IEEE
Year: 2006
Pages: 511-514
Proceedings: 2006 IEEE International Geoscience and Remote Sensing Symposium
ISBN: 0780395107 , 1509091505 , 9780780395107 and 9781509091508
Types: Conference paper
DOI: 10.1109/IGARSS.2006.136
ORCIDs: Nielsen, Allan Aasbjerg and Hansen, Lars Kai

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