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Abstract
The effort to utilize satellite-based MODIS, AVHRR, and GOES fire detections from the Hazard Monitoring System (HMS) to identify undocumented fires in Florida and improve the Monitoring Trends in Burn Severity (MTBS) mapping process has yielded promising results. This method was augmented using regression tree models to identify burned/not-burned pixels (BnB) in every Landsat scene (1984–2012) in Worldwide Referencing System 2 Path/Rows 16/40, 17/39, and 1839. The burned area delineations were combined with the HMS detections to create burned area polygons attributed with their date of fire detection. Within our study area, we processed 88,000 HMS points (2003–2012) and 1,800 Landsat scenes to identify approximately 300,000 burned area polygons. Six percent of these burned area polygons were larger than the 500-acre MTBS minimum size threshold. From this study, we conclude that the process can significantly improve understanding of fire occurrence and improve the efficiency and timeliness of assessing its impacts upon the landscape.
| Publication type | Conference Paper |
|---|---|
| Publication Subtype | Conference Paper |
| Title | Use of multi-sensor active fire detections to map fires in the United States: the future of monitoring trends in burn severity |
| Year Published | 2014 |
| Language | English |
| Publisher | USDA Forest Service |
| Publisher location | Asheville, NC |
| Contributing office(s) | Earth Resources Observation and Science (EROS) Center |
| Description | 7 p. |
| Larger Work Type | Report |
| Larger Work Subtype | Federal Government Series |
| Larger Work Title | Proceedings: Wildland fire in the Appalachians: Discussions among managers and scientists. General Technical Report SRS-199 |
| First page | 155 |
| Last page | 161 |
| Google Analytic Metrics | Metrics page |