AUTHORS: Morgan A. Crowley*, Jeffrey A. Cardille – McGill University; Michael A. Wulder, Joanne C. White – Canadian Forest Service (Pacific Forestry Centre)
ABSTRACT: The 2017 fire season was the largest on record for British Columbia (BC) in terms of area burned, and mapping these fires is important for monitoring forest-disturbance impacts. Two data sources provide reliable estimates of post-fire perimeters: (1) the Composite-to-Change (C2C) protocol, which makes annual forest disturbance mapping possible for Canada using annual best-available-pixel composites; and (2) the Canadian National Fire Database (CFDB), which identifies fire perimeters using data from fire management agencies. These resources are vital records of fire locations and extents, but are not intended to map active fire growth and patterns through time. The purpose of this project is to determine how these data sources can inform mapping the fire’s active phase. In addition to the observations provided by Landsat, imagery from sensors such as Sentinel-2, ASTER, and MODIS can be used to increase the temporal resolution and data density. We used the Bayesian Updating of Land Cover Classifications (BULC) algorithm to merge initial classifications while tolerating occasional smoke and clouds. Working in areas identified by the CFDB, we compared each source data’s post-fire Normalized Burn Ratio (NBR) against the expected NBR of a pre-fire best-available-pixel image from C2C. This approach enabled the classification into fire/no-fire using the large-scale processing power of Google Earth Engine. BULC then fused these classified images in Earth Engine, producing a series of updated fire extent maps for the 2017 fire season in BC. The increased temporal density allows us to retrospectively synthesize and, analyze the dynamics and growth of individual fire events, which was not possible using previously established methods. This capacity can support reconstructing the progression of active fire lifespans to better understand fire growth and underlying drivers. Methods from the case study could be scaled-up for nation-wide fire mapping at intermediate time-steps for past and future fire seasons.
