Indicator-based measurement of resilience and analysis of spatial trend in resilience to forest fire in Uttarakhand, India

Wildfires are becoming increasingly frequent and devastating in many tropical forests. In India, nearly 6% of forest cover is highly fire-prone, and 36% is prone to frequent fires. These frequent wildfires have compound impacts on forests, which include changes in biodiversity and, forest functionality. In the short term, the burnt ecosystem cannot have the same functionality as that of a pre-fire situation. Understanding forest ecosystem health status after a fire event can help increase our ability to manage the fire seasons. 
In the current study, time series data from optical remote sensing is used to assess the forest ecosystem resilience. The study area chosen is the forest region in Uttarakhand, India, including Jim Corbett National Park, that witnessed a severe forest fire in 2016. The active fire pixels during the 2016 fire event in the area were identified, and resilience over the identified pixels was measured based on the concept of engineering resilience.  Results are presented as resilience quantified for all burnt pixels based on three different indices which represent resistance and recovery namely, time taken for recovery, maximum impact of fire event, and cumulative impact. Further, we identified how resilience differs with the type of forest cover in the study area and how well each type of forest recovers from the fire event. The findings suggest that in the Indian scenario, deciduous broadleaf forests have a longer recovery followed by evergreen broadleaf and evergreen needleleaf, while grasslands and broadleaf cropland have shorter recovery times and impacts. From this work, we aim to study forest resilience in the Indian scenario and how well this can be compared with other areas where similar climatic conditions exist. The current work has potential applications in risk governance, ecosystem management, etc. and in evaluating the post-fire processes and primary factors driving the processes. Extensive data feeds available from current satellite platforms enable the post-fire dynamics study to be more accurate, thus more informed, and faster choices by stakeholders.