Journal
REMOTE SENSING OF ENVIRONMENT
Volume 108, Issue 2, Pages 179-188Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2006.09.029
Keywords
fire propagation modeling; image gradient; fire detection; fire monitoring; infrared
Funding
- Division Of Computer and Network Systems
- Direct For Computer & Info Scie & Enginr [1018072] Funding Source: National Science Foundation
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Remotely sensed infrared images are often used to assess wildland I ire conditions. Separately, fire propagation models are in use to forecast future conditions. In the Dynamic Data-Driven Application System (DDDAS) concept, the fire propagation model will react to the image data, which should produce more accurate predictions of fire propagation. In this study we describe a series of image processing tools that can be used to extract fire propagation parameters from multispectral infrared images so that the parameters can be used to drive a fire propagation model built upon the DDDAS concept. The method is capable of automatically determining the fire perimeter, active fire line, and fire propagation direction. A multi-band image gradient calculation, the Normalized Difference vegetation Index, and the Normalized Difference Burn Ratio along with several standard image processing techniques are used to identify and constrain the fire propagation parameters. These fire propagation parameters can potentially be used within the DDDAS modeling framework for model update and adjustment. (C) 2006 Elsevier Inc. All rights reserved.
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