NH036-07
Science-to-operations for Alaska wildfire management in times of COVID-19: Usability lessons from rapid data tool development
Science-to-operations for Alaska wildfire management in times of COVID-19: Usability lessons from rapid data tool development
Tuesday, 15 December 2020: 21:05
Virtual
Abstract:
The Boreal Fires team within the Alaska EPSCoR Fire and Ice project has the overarching goal to improve community resilience to wildfire through enhanced understanding and prediction of drivers of fire risk and behavior in Alaska. In April 2020, this established multi-disciplinary team, which unites academic scientists (remote sensing, atmospheric science, ecology, wildlife biology, economics) and Alaska Fire Service (AFS) staff (meteorology, GIS, fire behavior analysis, fire ecology), set off a conversation that aimed to identify any remote sensing or related geospatial datasets could be provided, rapidly, to AFS in order to enhance operational readiness. At the time, in-person operations and support on the ground in remote locations was anticipated to be limited by sanitary measures due to the global COVID-19 pandemic. We focussed on three datasets that were expected to provide the most useful immediate operational enhancement: Snow melt tracking with daily snow cover raster data from the NOAA National Ice Center; fire risk tracking based on daily Canadian Forest Fire Danger Rating System (CFFDRS) rasters generated by Mesowest (University of Utah); and enhanced active fire tracking using the VIIRS I-band Fire Detection Algorithm for High Latitudes (VIFDAHL). We found that the success of our effort benefitted from several essential factors: a long-standing, continuous relationship between the academic researchers and the fire management agency staff, which entailed familiarity with each other's technical capabilities, and operational characteristics; the willingness to provide data in formats that can be immediately ingested in tools that provides managers with a common operating picture; attention to details in visualization and data attribute choice; and leveraging existing products into useable data streams rather than new development. Lessons from rapid product development projects such as ours to anticipate and mitigate service interruptions in times of a global pandemic are well-suited to inform future science-to-operations elements of applied research that relates to hazard management and mitigation. They also generate avenues for future scientific research.