Forest Fire Risk Assessment Using GIS Science – A Case Study of South India
G. Godson
Institute of Remote Sensing, College of Engineering Guindy, Anna University, Chennai, Tamil Nadu, India
Search for more papers by this authorO. Mohammed Faizan
Institute of Remote Sensing, College of Engineering Guindy, Anna University, Chennai, Tamil Nadu, India
Search for more papers by this authorS. Sanjeevi
Department of Geology, College of Engineering Guindy, Anna University, Chennai, Tamil Nadu, India
Search for more papers by this authorG. Godson
Institute of Remote Sensing, College of Engineering Guindy, Anna University, Chennai, Tamil Nadu, India
Search for more papers by this authorO. Mohammed Faizan
Institute of Remote Sensing, College of Engineering Guindy, Anna University, Chennai, Tamil Nadu, India
Search for more papers by this authorS. Sanjeevi
Department of Geology, College of Engineering Guindy, Anna University, Chennai, Tamil Nadu, India
Search for more papers by this authorSuraj Kumar Singh
Search for more papers by this authorShruti Kanga
Search for more papers by this authorGowhar Meraj
Search for more papers by this authorMajid Farooq
Search for more papers by this authorSummary
Forest Fires have become increasingly common in Tamil Nadu, India. Several fire outbreaks in a year have killed hectares of wild areas. This paper makes a humble attempt to identify whether forest fires have made a considerable impact on the forest caps of Erode, Salem, and Dharmapuri Districts of Tamil Nadu. Further, it also tries to map out the forest fire frisk zones and the potential areas of forest fire spread sensitivity in the study area. To visualize the impact of forest fires, NDVI maps were generated from Satellite imageries of LANDSAT 5, 7, and 8 for the past years (2006–2019) in the corresponding fire seasons. Parameters like vegetation type, temperature, rainfall, road network, and slope (topography) of the study area were considered. Data from Tamil Nadu Forest Department, Ministry of Forest Environment and Climate Change, National Institute of Wind Energy, Indian Meteorological Department (IMD), SRTM DEM datasets, and open street map in ArcGIS 10.3 were instrumental in converting the above factors into their corresponding thematic maps. These map layers were then integrated with ArcGIS 10.3. Using a weighted overlay tool in ArcGIS 10.3, the final Risk Zone and Spread sensitivity maps were generated. This could be a valuable aid in planning Action Programmes to prevent such fires in the future. Even annual mountain trekkers can use this to plan their trips by avoiding those forest fire–prone zones.
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