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dc.contributor.author Van Den Bergh, F
dc.contributor.author Udahemuka, G
dc.contributor.author Van Wyk, BJ
dc.date.accessioned 2010-04-18T13:11:18Z
dc.date.available 2010-04-18T13:11:18Z
dc.date.issued 2009-07
dc.identifier.citation Van Den Bergh, F, Udahemuka, G and Van Wyk, BJ 2009. Potential fire detection based on Kalman-driven change detection. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Cape Town, South Africa, 12-17 July 2009, pp 1-4 en
dc.identifier.isbn 978-1-4244-3395-7
dc.identifier.uri http://hdl.handle.net/10204/4034
dc.description Copyright: 2009 IEEE, International Geoscience and Remote Sensing Symposium (IGARSS), Cape Town, South Africa, 12-17 July 2009 en
dc.description.abstract A new active fire event detection algorithm for data collected with the Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor, based on the extended Kalman filter, is introduced. Instead of using the observed temperatures of the spatial neighbours of a pixel to detect anomalous temperatures, the new algorithm only considers previous observations at the current pixel. The algorithm harnesses the Kalman filter to obtain a prediction of the expected brightness temperature at a given location, which is then compared to the actual SEVIRI observation. An adaptive threshold is used to determine whether the observed difference is indicative of a potential fire event. Initial tests show that the performance of this method is comparable to that of the EUMETSAT FIR product. en
dc.language.iso en en
dc.publisher IEEE en
dc.subject Fires en
dc.subject Fire detection algorithms en
dc.subject Spinning enhanced visible and infrared imager en
dc.subject SEVIRI en
dc.subject Kalman Filter en
dc.subject EUMETSAT FIR en
dc.subject Diurnal temperature cycle en
dc.subject DTC en
dc.subject Meteosat second generation en
dc.subject Remote sensing en
dc.subject Geoscience en
dc.title Potential fire detection based on Kalman-driven change detection en
dc.type Presentation en


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