ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume V-3-2022
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 533–539, 2022
https://doi.org/10.5194/isprs-annals-V-3-2022-533-2022
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 533–539, 2022
https://doi.org/10.5194/isprs-annals-V-3-2022-533-2022
 
17 May 2022
17 May 2022

ANALYZING SPATIO-TEMPORAL PATTERN OF THE FOREST FIRE BURNT AREA IN UTTARAKHAND USING SENTINEL-2 DATA

S. Mamgain, H. Karnatak, A. Roy, and P. Chauhan S. Mamgain et al.
  • Indian Institute of Remote Sensing, ISRO, Dehradun, India

Keywords: Burnt area, Normalized Burn Ratio, Sentinel 2, correlation, multiple regression analysis, fire severity

Abstract. Forest fire burnt area estimation using Normalized Burn Ratio at regional level helps in understanding the pattern of the frequency and severity of forest fires. In this study, burnt area is estimated for all the thirteen districts of Indian state Uttarakhand for last six years from 2016 to 2021 using Sentinel 2A and 2B datasets. The spatial and temporal pattern of the burnt area was analyzed by incorporating different parameters such as meteorological parameters like land surface temperature, rainfall; edaphic parameter like surface soil moisture and vegetation parameters like Normalized Difference Vegetation Index & Enhanced Vegetation Index. The estimated burnt area was statistically analyzed with respect to the parameters stated and the relationship among them was quantified. It was found that burnt area is positively correlated with the land surface temperature, while it showed negative correlation with the pre-fire precipitation, pre-fire NDVI & EVI and the surface soil moisture for 11 out of 13 districts. The district-wise forest fire burnt area assessment and analysis of its spatio-temporal pattern can be used in the preparedness and mitigation planning to prevent drastic ecological impacts of forest fires on the landscape.