Little is known about how satellite imagery can be used to describe burn severity in tundra landscapes. The Anaktuvuk River fire (ARF) of 2007 burned over 1000 km2 of tundra on the North Slope of Alaska, creating a mosaic of small (1 m2) to large (>100 m2) patches that differed in burn severity. The ARF scar provided us with an ideal landscape to determine if a single-date spectral vegetation index can be used once vegetation recovery had begun, and to independently determine how pixel size influences burn severity assessment. We determine and explore the sensitivity of several commonly used vegetation indices to variation in burn severity across the ARF scar, and the influence of pixel size on the assessment and classification of tundra burn severity. We conducted field surveys of spectral reflectance at the peak of the first growing season post-fire (extended assessment period), at eighteen field sites that ranged from high to low burn severity. In comparing single date indices, we found that the two-band Enhanced Vegetation Index (EVI2) was highly correlated with NBR and better distinguished among three burn severity classes than both the NBR and the NDVI. We also show clear evidence that SWIR reflectivity does not vary as a function of burn severity. By comparing a Quickbird scene (2.4 m pixels) to simulated 30 m and 250 m pixel scenes, we are able to confirm that while the moderate spatial resolution of the Landsat TM sensor (30 m) is sufficient for mapping tundra burn severity, the coarser resolution of the MODIS sensor (250 m) is not well matched to the fine scale of spatial heterogeneity in the ARF burn scar.
Understanding burn severity sensing in Arctic tundra: Exploring vegetation indices, sub-optimal assessment timing and the impact of increasing pixel size
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International Journal of Remote Sensing
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