Analysis of forest health and socioeconomic dimension in climate change scenario and its future impacts: remote sensing and GIS approach

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Photo by Jon Flobrant on Unsplash

Photo by Jon Flobrant on Unsplash

Why is it important?

The present study examined the relationship among various diversified datasets using remote sensing and GIS. About 72% of the total forest area of Chhattisgarh state (59,935 km2) has shown a trend of negative change between the periods (1982 and 2006). Around 50% of the total forest fires of the state were found in the two tehsils of Narayanpur and Bijapur with two major forest fire hotspots. Approximately 86% of the total forest fire event of the state occurred in the category of “tropical mixed deciduous and dry deciduous forests” whereas the intensity of forest fire events was found 2.2 times in the category “tropical lowland forests, broadleaved, evergreen, < 1000 m” when it was compared with the category of “tropical mixed deciduous and dry deciduous forests.” The highest poverty percent was found in the tehsil of Bijapur (65.9%) which retains a significantly high percentage of the tribal population (73.1%). The adaptive capacity of Raipur tehsil (state capital) is high whereas it reduces significantly towards north and south from the state capital. The climate anomaly data evaluation for the year 2030 showed variation such as reduction in rainfall and increase in temperature will significantly maneuver the forest fire regime in future is a matter of serious concern. The outcomes of the present study would certainly guide the policymakers of the state of Chhattisgarh to prepare a meaningful, transparent and robust plan for the betterment of people keeping in mind of future climate change impact.