Remote Sensing-Based Assessment of Fire Danger Conditions Over Boreal Forest

Forest fire is an integral part in many forested ecosystems including boreal forests, that influences forest productivity, biodiversity and socio-economy, among others. In this paper, we evaluated the potential of three selected satellite (i.e., MODIS)-based variables/indices at 8-day temporal resolution, i.e., surface temperature (
T
_S
), normalized multiband drought index (NMDI) and temperature vegetation wetness index (TVWI) in predicting/forecasting the fire danger conditions over boreal forest regions of Alberta during the period 2006-2008. The method was based on the assumption that the fire danger conditions during
i
+1 period would be high if the instantaneous values of: (i)
T
_S
values were either higher or equal; or (ii) NMDI or TVWI values were either lower or equal; with compare to their respective study-area-specific average during i period. The analyses were conducted on the basis of either individual variable or combining all of the three together. We found that 60.59% for
T
_S
, 72.41% for NMDI, and 54.19% for TVWI of fires fell under the high fire danger conditions. The combination of all of the three individual variables, it revealed that 91.63% of the fires fell in the categories of “very high” (i.e., all three variables indicated high danger), “high” (i.e., at least two of them indicated high danger), and “moderate” (i.e., at least one of the variables indicated high danger) fire danger classes. These results showed that the applicability of the proposed method in predicting fire danger conditions over the boreal forest regions.