Arctic Urban Risks and Adaptations: a co-production framework for addressing multiple changing environmental hazards
Jen Schmidt – University of Alaska Anchorage
Arctic Urban Risks and Adaptations (AURA) is a new, four-year NSF project addressing changing environmental hazards around Anchorage, Fairbanks, and Whitehorse. Understanding how wildfire hazards are changing, and the associated risks and costs are a primary focus of the study. Overlapping risks associated with wildfire, including permafrost thaw and rain-in-winter, are being integrated as a unified approach to assessing environmental hazards. The co-production framework of the project strives to use land manager and community input to produce decadal wildfire hazard mapping and assessment tools by leveraging existing datasets other resources.
Wildfire management: statewide fuels treatment database
Currently fuels treatment datasets are spread across multiple agencies and are often lacking important information such as year of treatment. As part of a new four-year project, Jen Schmidt (PI) and the EPSCoR Boreal Fires Team hope to collaborate with others to provide comprehensive-online GIS layers that land managers and others could use to efficiently find where fuel treatments may exist. Having a centralized fuel treatment database with aerial imagery and management zones (Figure 1) would allow agencies to quickly check for prior fuel treatments, providing a valuable tool to aid in decision making and planning.
Assessing wildfire hazards over time
As part of the hazard analysis, Jen is employing recently completed NASA ABoVE (Arctic – Boreal Vulnerability Experiment) 2014 vegetation maps. These maps categorize 1984-2014 LandSat imagery of arctic and boreal forests in 15 vegetation types. The dataset has great application for visualizing vegetation change over time. In this chord diagram (Figure 2), you can follow transitions of vegetation groups in the Fairbanks North Star Borough by looking at the lines in the center of the chart connecting the groups from 1984-2014. For example, note the many transformations of “woodland” (tan) to multiple vegetation types, including “evergreen” (green) and “sparse” (gray) forests over the 30-year time period. Fire is a key driver of these vegetation changes and being able to track the transition of vegetation types can improve understanding of how vegetation composition changes in response to fire, which can aid in modeling wildfire hazards.
Wang, J.A., D. Sulla-Menashe, C.E. Woodcock, O. Sonnentag, R.F. Keeling, and M.A. Friedl. 2019. ABoVE: Landsat-derived Annual Dominant Land Cover Across ABoVE Core Domain, 1984-2014. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1691