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Linking spectral recovery from remote sensing to ground observations at the Elephant Hill wildfire Huang, Xiyu


The 2017 Elephant Hill wildfire is considered as one of the most destructive fires in Canada. Wildfires are a major ecosystem disturbance which also causes residential displacement and financial loss. Monitoring vegetation recovery following wildfires becomes crucial to rebuilding the local community and ecological system. Since recovery rates may have discrepancies between ground data and remote sensing data, this project aimed to investigate if the post-fire spectral recovery based on Landsat time series analysis can accurately capture vegetation recovery as ground plots indicate. A total of 20 Landsat scenes with the 30-meter resolution from a year before to three years after the fire event were used to analyze the spectral recovery at the Elephant Hill region. Two spectral indicators were calculated in the analysis including normalized difference vegetation index (NDVI) and normalized burn ratio (NBR). Clear spectral recovery patterns were observed from resulting maps and time series scatterplots while there was a significant decline of NDVI and NBR in the year of 2017. NDVI and NBR values have been gradually increasing after the fire and reached pre-fire pixel values by the year 2020. However, the results did not find any significant relationships between the NDVI / NBR values and vegetation cover percentage. Since this research focused on understory recovery with almost half of the plots having greater than 30% of crown closure, it is challenging to evaluate ground vegetation types and coverage in detail with 30-meter-spatial-resolution data. Therefore, the future study can consider sampling ground data with low canopy cover every year.

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