Canadian Forest Service Publications

Calibrating satellite-based indices of burn severity from UAV-derived metrics of a burned boreal forest in NWT, Canada. 2017. Fraser, R.H.; van der Sluijs, J.; Hall, R.J. Remote Sensing 9(3):279.

Year: 2017

Issued by: Northern Forestry Centre

Catalog ID: 38033

Language: English

Availability: PDF (download)

Available from the Journal's Web site.
DOI: 10.3390/rs9030279

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Wildfires are a dominant disturbance to boreal forests, and in North America, they typically cause widespread tree mortality. Forest fire burn severity is often measured at a plot scale using the Composite Burn Index (CBI), which was originally developed as a means of assigning severity levels to the Normalized Burn Ratio (NBR) computed from Landsat satellite imagery. Our study investigated the potential to map biophysical indicators of burn severity (residual green vegetation and charred organic surface) at very high (3 cm) resolution, using color orthomosaics and vegetation height models derived from UAV-based photographic surveys and Structure from Motion methods. These indicators were scaled to 30 m resolution Landsat pixel footprints and compared to the post-burn NBR (post-NBR) and differenced NBR (dNBR) ratios computed from pre- and post-fire Landsat imagery. The post-NBR showed the strongest relationship to both the fraction of charred surface (exponential R2 = 0.79) and the fraction of green crown vegetation above 5 m (exponential R2 = 0.81), while the dNBR was more closely related to the total green vegetation fraction (exponential R2 = 0.69). Additionally, the UAV green fraction and Landsat indices could individually explain more than 50% of the variance in the overall CBI measured in 39 plots. These results provide a proof-of-concept for using low-cost UAV photogrammetric mapping to quantify key measures of boreal burn severity at landscape scales, which could be used to calibrate and assign a biophysical meaning to Landsat spectral indices for mapping severity at regional scales.

Plain Language Summary

Fires typically result in a wide range of severity and damage to forest vegetation within the boreal forest. Field observations, satellite data and models that relate the two are often used to understand the ecological consequences of forest fires. Field access may be limited and is a particular problem in northern boreal fires, such as in the Northwest Territories. A relevant question to this problem was whether images from remotely piloted Unmanned Airborne Vehicles (UAV), or drones, could be used to reduce the need for calibrating satellite data from field surveys. This study is among the first to explore relationships between UAV-derived indices and both field and satellite measures of burn severity. Understanding these relationships provides the foundation for pursuing an improved approach for mapping and evaluating the effects of forest fires and may be particularly suited for application in the northern boreal.