Mapping wildfires in Canada with Landsat MSS to extend the National Burned Area Composite (NBAC) time series back to 1972
Rob Skakun A * , Guillermo Castilla A and Piyush Jain AA
Abstract
Satellite imaging has improved burned area mapping; however, few studies have taken advantage of the Multi-Spectral Scanner (MSS) in early Landsat satellites, which started acquiring data 10 years earlier than Thematic Mapper (TM).
To expand Canada’s National Burned Area Composite (NBAC) annual time series back to 1972 using MSS data and report annual statistics and national trends for 1972–2022.
Pre- and post-fire image composites were created using an improved collection of MSS data available from the Google Earth Engine. A Normalized Difference Vegetation Index (NDVI) difference image was adaptively thresholded to extract burned areas, which were then vectorised. To assess accuracy, MSS fire polygons were compared with TM in a year of overlap.
Compared with TM, MSS polygons overestimated burned area by 5.6% when the relativised differenced NDVI was used, with significant upward trends for number of fires > 200 ha, fire season length and mean duration of fires.
MSS is a valuable data source for retrospective mapping of boreal and temperate forest fires where data from finer-resolution sensors are lacking.
After the addition of MSS-mapped fires, NBAC is the longest satellite-based time series of annual burned area from individually mapped fires in the world.
Keywords: burned area, Canada, fire perimeters, Google Earth Engine, Landsat, Landsat Multi-Spectral Scanner, Landsat Thematic Mapper, MSS, NBAC, NDVI, trend analysis, wildfire mapping.
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