Evaluating the Differenced Normalized Burn Ratio for Assessing Fire Severity Using Sentinel-2 Imagery in Northeast Siberian Larch Forests

作者：Clement J. F. Delcourt, Alisha Combee, Brian Izbicki, Michelle C. Mack, Trofim C. Maximov, Roman Petrov, Brendan M. Rogers, Rebecca C. Scholten, Tatiana A. Shestakova, Dave van Wees, Sander Veraverbeke · 发表于：Remote Sensing · 年份：2021 · DOI：10.3390/rs13122311 · 被引用次数：82 · 研究领域：Fire effects on ecosystems、Rangeland and Wildlife Management、Remote Sensing and LiDAR Applications

Fire severity is a key fire regime characteristic with high ecological and carbon cycle relevance. Prior studies on boreal forest fires primarily focused on mapping severity in North American boreal forests. However, the dominant tree species and their impacts on fire regimes are different between North American and Siberian boreal forests. Here, we used Sentinel-2 satellite imagery to test the potential for using the most common spectral index for assessing fire severity, the differenced Normalized Burn Ratio (dNBR), over two fire scars and 37 field plots in Northeast Siberian larch-dominated (Larix cajanderi) forests. These field plots were sampled into two different forest types: (1) dense young stands and (2) open mature stands. For this evaluation, the dNBR was compared to field measurements of the Geometrically structured Composite Burn Index (GeoCBI) and burn depth. We found a linear relationship between dNBR and GeoCBI using data from all forest types (R2 = 0.42, p < 0.001). The dNBR performed better to predict GeoCBI in open mature larch plots (R2 = 0.56, p < 0.001). The GeoCBI provides a holistic field assessment of fire severity yet is dominated by the effect of fire on vegetation. No significant relationships were found between GeoCBI components (overall and substrate stratum) and burn depth within our fires (p > 0.05 in all cases). However, the dNBR showed some potential as a predictor for burn depth, especially in the dense larch forests (R2 = 0.63, p &...