Challenges of assessing fire and burn severity using field measures, remote sensing and modelling

Abstract

Comprehensive assessment of ecological change after fires have burned forests and rangelands is important if we are to understand, predict and measure fire effects. We highlight the challenges in effective assessment of fire and burn severity in the field and using both remote sensing and simulation models. We draw on diverse recent research for guidance on assessing fire effects on vegetation and soil using field methods, remote sensing and models. We suggest that instead of collapsing many diverse, complex and interacting fire effects into a single severity index, the effects of fire should be directly measured and then integrated into severity index keys specifically designed for objective severity assessment. Using soil burn severity measures as examples, we highlight best practices for selecting imagery, designing an index, determining timing and deciding what to measure, emphasising continuous variables measureable in the field and from remote sensing. We also urge the development of a severity field assessment database and research to further our understanding of causal mechanisms linking fire and burn severity to conditions before and during fires to support improved models linking fire behaviour and severity and for forecasting effects of future fires.

Calibrating Satellite-Based Indices of Burn Severity from UAV-Derived Metrics of a Burned Boreal Forest in NWT, Canada

“…For example, an index that measures spectral changes such as the dNBR, should be theoretically preferable for studies of burn severity, since, by definition, this term describes the degree of ecosystem change resulting from fire. The CBI, which was developed as a field measure of severity for calibrating dNBR, is similarly based on ecological changes, although pre-fire conditions must often be inferred [22,23]. A bi-temporal index also permits a more accurate mapping of the extent of burning (a pre-requisite for determining severity), by avoiding commission errors over unvegetated areas that can result from only using a post-fire index.…”

Exploring the Relationship between Burn Severity Field Data and Very High Resolution GeoEye Images: The Case of the 2011 Evros Wildfire in Greece

“…Prior to the fire, topography influences the microclimate (temperature, precipitation, and direct solar radiation), plant productivity, and biomass accumulation that directly affects the amount of biomass available to burn during the outbreak of fire [18]. After the fire event, the topographic variations in slope, aspect, and elevation influences the microclimate at a local scale which, in turn, affects the post-fire regeneration rates [47].…”

“…A possible explanation is that the fire effects are quite homogeneous and easy to measure short after the disturbance [18]. Even though in this study we focused on the short-term relationship between the GeoEye images and the fire effects, it would be beneficial to extend our analysis by looking at the long-term relationship.…”

Quantifying Changes in Total and Pyrogenic Carbon Stocks Across Fire Severity Gradients Using Active Wildfire Incidents

“…The severity of a fire describes the magnitude of impact to an ecosystem, and is represented by a wide variety of definitions and metrics (Keeley, 2009;Jain et al, 2012;Morgan et al, 2014). Keeley (2009) provided a standardized definition of fire severity as "aboveground and belowground organic matter consumption from fire" and he includes fire-caused plant mortality as a type of organic matter consumption.…”

“…Field indices classify fire severity based on the extent of organic matter loss or decomposition (i.e., using metrics such as tree crown scorch, tree mortality, woody fuel consumption, loss of soil organic horizons, etc. ), and although vegetation composition, structure, and environmental factors also influence organic matter loss, fire severity indices generally reflect fireline intensity (Keeley, 2009;Morgan et al, 2014). Because of variability in characteristics in vegetation and soil within and across ecosystems (e.g., extent of mineral soil exposure, soil color, vegetation structure and stem density), fire severity is best evaluated based on knowledge of pre-fire ecosystem characteristics (Keeley, 2009), but these data often may not exist in areas that experience unplanned fires.…”