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 %.
|Title of host publication||Proceedings of the IEEE Geoscience and Remote Sensing Symposium (IGARSS) 2006|
|Publication status||Published - 2006|
|Event||2006 IEEE International Geoscience and Remote Sensing Symposium - Denver, United States|
Duration: 31 Jul 2006 → 4 Aug 2006
|Conference||2006 IEEE International Geoscience and Remote Sensing Symposium|
|Period||31/07/2006 → 04/08/2006|