Prescribed fire is an important land conservation tool to meet ecological, cultural, and public safety objectives across terrestrial ecosystems. While estimates of prescribed burning in the U.S.A. exceed 4.5 million hectares annually, tracking the extent of prescribed fire is problematic for several reasons and prevents an understanding of spatial and temporal trends in landscape patterns of prescribed fires. We developed a regional prescribed fire database from 12 state forestry agencies in the southeastern U.S. using records of burn location, size, and calendar days and evaluated spatial and temporal patterns in burning from 2010 to 2020. Over half of all prescribed fires in the U.S. occur in the Southeast, with five states (Florida, Georgia, Alabama, South Carolina, and Mississippi) comprising over ninety percent of the burned area over a decade. We identified hot spots of concentrated prescribed fire activity on both public and private forestlands across the region, as well as regions of less burning, which often occurred in close proximity to hot spots. Temporally, most prescribed fires occurred in March and February across the region; the least activity was recorded between May and November. Our database reveals that burning is highly concentrated within the region, presumably reflecting local land ownership categories and associated land management objectives. This database and these analyses provide the first region-wide summary of fine-scale patterns of prescribed fire in the U.S. and demonstrate the potential for various analyses beyond this work for air quality modeling and remote sensing, as well as the potential impacts of demographic and land use changes.

Prescribed fires and wildfires are common in wetland ecosystems across the Southeastern United States. However, the wetland burned area has been chronically underestimated across the region due to (1) spectral confusion between open water and burned area, (2) rapid post-fire vegetation regrowth, and (3) high annual precipitation limiting clear-sky satellite observations. We developed a machine learning algorithm specifically for burned area in wetlands, and applied the algorithm to the Sentinel-2 archive (2016–2019) across the Southeastern US (>290,000 km²). Combining Landsat-8 imagery with Sentinel-2 increased the annual clear-sky observation count from 17 to 46 in 2016 and from 16 to 78 in 2019. When validated with WorldView imagery, the Sentinel-2 burned area had a 29% and 30% omission and commission rates of error for burned area, respectively, compared to the US Geological Survey Landsat-8 Burned Area Product (L8 BA), which had a 47% and 8% omission and commission rate of error, respectively. The Sentinel-2 algorithm and the L8 BA mapped burned area within 78% and 60% of wetland fire perimeters (n = 555) compiled from state and federal agencies, respectively. This analysis demonstrated the potential of Sentinel-2 to support efforts to track the burned area, especially across challenging ecosystem types, such as wetlands.