A dynamic algorithm for wildfire mapping with NOAA/AVHRR data
R. Pu A B , P. Gong A B D , Z. Li C and J. Scarborough B
+ Author Affiliations
- Author Affiliations
A State Key Lab of Remote Sensing Science, IRSA, Box 9718, Beijing 100101, China.
B Center for Assessment and Monitoring of Forest and Environmental Resources, 151 Hilgard Hall, University of California, Berkeley, CA 94720-3110, USA. Telephone: +1 510 642 1351; fax: +1 510 643 5098; email: rpu@nature.berkeley.edu; gong@nature.berkeley.edu; jscar@gisc.berkeley.edu
C Department of Meteorology and Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20742-2425, USA. Telephone: +1 301 405 6699; fax: +1 301 405 8468; email: zli@atmos.umd.edu
D Corresponding author.
International Journal of Wildland Fire 13(3) 275-285 https://doi.org/10.1071/WF03054
Submitted: 30 June 2003 Accepted: 5 April 2004 Published: 16 November 2004
Abstract
A wildfire-mapping algorithm is proposed based on fire dynamics, called the dynamic algorithm. It is applied to daily NOAA/AVHRR/HRPT data for wildland areas (scrub, chaparral, grassland, marsh, riparian forest, woodland, rangeland and forests) in California for September and October 1999. Daily AVHRR images acquired from two successive days are compared for active fire detection and burn scar mapping. The algorithm consists of four stages: data preparation; hotspot detection; burn scar mapping; and final confirmation of potential burn scar pixels. Preliminary comparisons between the result mapped by the dynamic algorithm and the fire polygons collected by the California Department of Forestry and Fire Protection through ground survey indicate that the algorithm can track burn scars at different developmental stages at a daily level. The comparisons between wildfire mapping results produced by a modified version of an existing algorithm and the dynamic algorithm also indicate this point. This is the major contribution of this algorithm to wildfire detection methods. The dynamic algorithm requires highly precise registration between consecutive images.
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