| dc.description.abstract | The burning of forest areas in Sri
Lanka can be considered as one of the foremost
issues that should be addressed. Human
influence could be identified as the major cause
of forest fires in Sri Lanka. Hence, identification,
mapping, and taking necessary actions for forest
fires are vital in the current context. The forest
fire that occurred in the Ella area in 2019 was the
focus of the case study. First, the burned location
identification was the crucial part of the study
due to the unavailability of a proper database of
forest fires in Sri Lanka. Hence, with the use of
newspaper articles and reports, the forest-fire
area was identified at the beginning. Then by
utilizing Sentinel-2 satellite images through the
Normalized Burn Ratio (NBR) forest fire area
was identified. Further, with occupying the
difference of NBR (dNBR) mapped the severity of
the fire by following the United States Geological
Survey (USGS) fire classification scheme. The
analysis was performed in Quantum GIS (QGIS)
open-source software platform since the Semiautomatic
Classification Plugin (SCP) provided
the best framework for analysis. Even if
immediate satellite images just after the incident
were not present, mainly due to the cloud
coverage, the analysis was able to obtain a
considerable output. Consequently, owing to the
study, 73.82 hectares of areas were identified as
burned due to the wildfire and 15.65% of the
area was highlighted as a high severity of the
burn. In conclusion, the applied methodology
could be used by any organization for forest scare
mapping, and it is vital in future planning. | en_US |
