Authors : Sanjeev Kumar Raut; David Nhemaphuki; Rebanta Aryal; Prakash Lakandri
Volume/Issue : Volume 5 - 2020, Issue 7 - July
Google Scholar : http://bitly.ws/9nMw
Scribd : https://bit.ly/3jD88Vf
DOI : 10.38124/IJISRT20JUL351
Accurate and the efficient rapid mapping of
the fire-damaged areas are the most fundamental things
for any places to retain from environmental loss. To
support the fire management, make definite strategy and
planning, and restore the vegetation, it is important to
detect the area before and after the fire damages. Under
climate change conditions, heat and drought may trigger
tough fire regimes in terms of number and dimension of
fires. To deliver the rapid information of the area
damaged by the fires, Burned Area Index (BAI),
Normalized Burned Ratio (NBR) and their versions are
applied to map burned areas from high-resolution
optical satellite data. The new MSI sensor aboard
Sentinel-2 satellites records the more spectral
information in the red edge spectral region making it
more convenient to the development of new indices for
the burned area mapping. Recently, Australia had
confronted a devastating bushfire recorded in the
history of the nation. In this project, NBR deployed to
detect burned areas at around 10m-20m spatial
resolution based on pre and post-fire Sentinel-2 images.
A dNBR (differentiated Normalized Burned Ratio) was
calculated while burn severity was mapped as purposed
by United States Geological Survey (USGS). It observed
that more than half of the East Gippsland region i.e.
about 53% of the area affected by the wildfire while
38% remained unburned and 8.4% showed the
regrowth.
Keywords : Fire Severity, Normalized Burned Ratio (NBR), Normalized Burned Ratio difference (dNBR), Sentinel, United States Geological Survey (USGS).