Classifying and Mapping Wildfire Severity
This study evaluates six different approaches to classifying and mapping fire severity using multi-temporal Landsat Thematic Mapper data. The six approaches tested include: two based on temporal image differencing and ratioing between pre-fire and post-fire images, two based on principal
component analysis of pre- and post-fire imagery, and two based on artificial neural networks, one using just post-fire imagery and the other both pre- and post-fire imagery. Our results demonstrated the potential value for any of these methods to provide quantitative fire severity maps, but
one of the image differencing methods (ND4/7) provided a flexible, robust, and analytically simple approach that could be applied anywhere in the Continental U.S.
Based on the results of this test, the ND4/7 was implemented operationally to classify and map fire severity over 1.2 million hectares burned in the Northern Rocky Mountains and Northern Great Plains during the 2000 fire season, as well as the 2001 fire season (Gmelin and Brewer, 2002). Approximately the same procedure was adopted in 2001 by the USDA Forest Service, Remote Sensing Applications Center to produce Burned Area Reflectance Classifications for national-level support of Burned Area Emergency Rehabilitation activities (Orlemann, 2002).
Based on the results of this test, the ND4/7 was implemented operationally to classify and map fire severity over 1.2 million hectares burned in the Northern Rocky Mountains and Northern Great Plains during the 2000 fire season, as well as the 2001 fire season (Gmelin and Brewer, 2002). Approximately the same procedure was adopted in 2001 by the USDA Forest Service, Remote Sensing Applications Center to produce Burned Area Reflectance Classifications for national-level support of Burned Area Emergency Rehabilitation activities (Orlemann, 2002).
Document Type: Research Article
Publication date: 01 November 2005
- The official journal of the American Society for Photogrammetry and Remote Sensing - the Imaging and Geospatial Information Society (ASPRS). This highly respected publication covers all facets of photogrammetry and remote sensing methods and technologies.
Founded in 1934, the American Society for Photogrammetry and Remote Sensing (ASPRS) is a scientific association serving over 7,000 professional members around the world. Our mission is to advance knowledge and improve understanding of mapping sciences to promote the responsible applications of photogrammetry, remote sensing, geographic information systems (GIS), and supporting technologies. - Editorial Board
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