A hybrid contextual approach to wildland fire detection using multispectral imagery

We propose a hybrid contextual fire detection algorithm for airborne and satellite thermal images. The proposed algorithm essentially treats fire pixels as anomalies in images and can be considered a special case of the more general clutter or background suppression problem. It utilizes the local ba...

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Bibliographic Details
Published in:	IEEE transactions on geoscience and remote sensing Vol. 43; no. 9; pp. 2115 - 2126
Main Authors:	Ying Li, Vodacek, A., Kremens, R.L., Ononye, A., Chunqiang Tang
Format:	Journal Article
Language:	English
Published:	New York, NY IEEE 01-09-2005 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Accuracy Algorithms Anomaly detection Applied geophysics Bands Detection algorithms Earth sciences Earth, ocean, space Exact sciences and technology Fire detection Fires High-resolution imaging Infrared detectors Internal geophysics Mahalanobis distance MODIS multispectral images Multispectral imaging Pixel Pixels Predictive models Satellites Studies Thresholds wildland fire detection algorithms detection probability multispectral remote sensing Space remote sensing accuracy covariance anomalies Anomaly detection fires propagation imagery wildland fire detection multispectral images Pixel Mahalanobis distance
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