| 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 Semi-automatic 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 |
