Mapping Wildfire Burn Severity in the Arctic Tundra from Downsampled MODIS Data

Abstract Wildfires are historically infrequent in the arctic tundra, but are projected to increase with climate warming. Fire effects on tundra ecosystems are poorly understood and difficult to quantify in a remote region where a short growing season severely limits ground data collection. Remote sensing has been widely utilized to characterize wildfire regimes, but primarily from the Landsat sensor, which has limited data acquisition in the Arctic. Here, coarse-resolution remotely sensed data are assessed as a means to quantify wildfire burn severity of the 2007 Anaktuvuk River Fire in Alaska, the largest tundra wildfire ever recorded on Alaska's North Slope. Data from Landsat Thematic Mapper (TM) and downsampled Moderate-resolution Imaging Spectroradiometer (MODIS) were processed to spectral indices and correlated to observed metrics of surface, subsurface, and comprehensive burn severity. Spectral indices were strongly correlated to surface severity (maximum R2 = 0.88) and slightly less strongly correlated to substrate severity. Downsampled MODIS data showed a decrease in severity one year post-fire, corroborating rapid vegetation regeneration observed on the burned site. These results indicate that widely-used spectral indices and downsampled coarse-resolution data provide a reasonable supplement to often-limited ground data collection for analysis and long-term monitoring of wildfire effects in arctic ecosystems.

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