부산대학교 도서관

Fire severity is the direct result of the combustion process and is related to the rate at which fuel is being consumed. Many studies have already been conducted to map fire severity using different burn severity indices and some of the research studies were based on field-based validation. A few studies have used the coarse and medium resolution satellite-based time series data to assess the fire severity and to assess the impacts on vegetation recovery. Therefore, this study is a remote sensing approach to map fire severity and to assess the vegetation regrowth after a big fire event (Black Christmas Bushfires) at the selected national parks in the outskirts of Sydney, Australia, using Moderate-resolution Imaging Spectroradiometer (MODIS) Data [from the year 2000 to 2016]. Two established fire severity indices, Normalised Burn Ratio (NBR) and differenced Normalised Burn Ratio (dNBR) were used to detect fire severity. Time series analysis of MODIS-derived vegetation indices [LAI (Leaf Area Index) and NDVI (Normalised Difference Vegetation Index)] was applied to understand the change in the phenological cycle after the fire events. Time-series analysis showed that MODIS-NDVI provides robust seasonality assessment than MODIS-LAI profile. The woodland area (Eucalypt Medium Woodland Forest) showed delayed vegetation recovery after the Big Christmas Bushfires.