Assessing burned areas in wildfires and prescribed fires with spectral indices and SAR images in the Margalla Hills of Pakistan

The extent of wildfires cannot be easily mapped using field-based methods in areas with complex topography and in those areas, the use of remote sensing is an alternative. This study first obtained images from the Sentinel-2 satellites for the period 2015-2020 with the objective of applying multi-temporal spectral indices to assess areas burned in wildfires and prescribed fires in the Margalla Hills of Pakistan using Google Earth Engine (GEE). Using those images, the Normalized Difference Vegetation Index (NDVI) and the Normalized Burn Ratio (NBR), which are often used to assess the severity of fires, were calculated for wildfires and prescribed fires. For each satellite image scene, spectral indices values were extracted for the 5th, 20th, 40th, 60th, 80th and 95th percentiles of pixels of each burned area. Then, box plots representing the distribution of these values were plotted for each satellite image to identify whether the regeneration time subsequent to a fire, also known as the burn scar, and the severity of the fire differed between the autumn and summer wildfires, and with prescribed fires. A statistical test revealed no differences for the re-generation time amongst the three categories of fires, but that the severity of summer wildfires was significantly different from that of prescribed fire, and this, for both indices. Second, SAR images were obtained from the Sentinel-1 mission for the same period as that of the optical imagery. A visual interpretation of the 34 variables of SAR response revealed that the 95th percentile of the Normalized Signal Ratio (NSR p_95) is adequate to detect burned areas in the study area. Moreover, it was found that 95% of the plots analyzed by the 80th percentile NSR (NSR p_80) showed a good response to fires in comparison to the spectral indices