Abstract
Abstract. Forest fires are frequent phenomena in Uttarakhand Himalayas especially in the months of April to May, causing major loss of valuable forest products and impact on humans through the emissions and therefore effects the climate change. The major forest fire was started on May 19, 2018 and spread in 10 districts out of 13 districts of Uttarakhand state till the fire was suppressed after May 30, 2018. The burned area mapping is essential for the forest officials to plan for mitigation measures and restoration activities after the fire season. In this study, sentinel 2A & 2B satellite datasets were used to map burned severity over Uttarakhand districts. Differenced Normalized Burn Ratio (dNBR) and Relativized Burn Ratio (RBR) were calculated and compared with the active fire points. Results shows that both the dNBR and RBR are in good agreement with the actual occurence of forest fires.
Highlights
The burned area mapping is essential for the forest officials to plan for mitigation measures and restoration activities after the fire season
The resultant Differenced Normalized Burn Ratio (dNBR) map was multiplied by a scale factor 1000 to categorize the fire severity levels
United States Geological Survey (USGS) proposed 7 interpretation levels based on the dNBR value and is shown in Table 1 and Burn severity map was generated by reclassifying the dNBR map on the basis of Table 1
Summary
The burned area mapping is essential for the forest officials to plan for mitigation measures and restoration activities after the fire season. Rapid and accurately mapping of fire burn severity is an essential initiative to support fire management activities such as strategic planning, mitigation measures and monitoring restoration of vegetation (Garcia and Caselles, 1991; Key and Benson, 1999; Michalek et al, 2000; Key and Benson, 2006; Parks et al, 2014). Studies carried out by several researchers across the world suggests that, burn severity mapping is more effective when the ratio, that combining near infrared and shortwave infrared of the electromagnetic spectrum because the burnt area show higher reflectance than the green vegetation in Short Wave Infra-red Region (SWIR) (Garcia and Caselles, 1991; Key and Benson, 1999; Parks et al, 2014). Burn severity mapping with high spatial resolution has been carried out with
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