Volume XLII-5
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-5, 469-474, 2018
https://doi.org/10.5194/isprs-archives-XLII-5-469-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-5, 469-474, 2018
https://doi.org/10.5194/isprs-archives-XLII-5-469-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  19 Nov 2018

19 Nov 2018

MAPPING OF FOREST FIRE BURNED SEVERITY USING THE SENTINEL DATASETS

K. V. Suresh Babu1, A. Roy1, and R. Aggarwal2 K. V. Suresh Babu et al.
  • 1Disaster management studies, Indian Institute of Remote Sensing, ISRO, Dehradun, India
  • 2United Nations University Institute for the Advanced Study of Sustainability, Tokyo, Japan

Keywords: Sentinel, Forest fire, NBR, dNBR, RBR

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.