As per the news reports in July 2020, a research study published in the journal, Science of the Total Environment, which throws light on forest fires and their impact on carbon emissions.
Forest Fires in India
As per Sandeep Bhatt from IIT, Roorkee, who has spent years tracking forest fires—such are a common sight every year in Uttarakhand. He, along with an international team, reported the direct effect on carbon emission and the ecosystem.
In fact, a total of 5,20,861 active forest fire events were detected in India during 2003–2017. As per the Forest Survey of India, over 54 per cent of the forest cover in India is exposed to occasional fire and the most fire-prone states in India are Madhya Pradesh, Himachal Pradesh, Odisha, and Uttarakhand.
Previously, in situ observations in Western Himalaya showed a sharp increase of carbon monoxide, nitrogen oxides, and ozone during high fire activity periods.
As such, there is an urgent need to identify forest fire hot sports and make accurate forecast recording of such occurrences in India.
Significance of Remote Sensing Technique
The study used remote sensing-based models to measure primary productivity over an area and looked at burn indices such are a common sight every year in Uttarakhand, which are used to demarcate the forest fire burn scars, using satellite imagery.
The normalised burn ratio which is an effective burn index commonly used to identify burnt regions in large fire zones.
Normally, healthy vegetation exhibits a very high reflectance in the near-infrared spectral region and considerably low reflectance in the shortwave infrared spectral region, which get dismantled and reversed if a fire occurs.
The spectral differences between healthy vegetation and burnt forest areas can easily be identified and highlighted by remote sensing burn indices, which may be a promising tool for land resource managers and fire officials.
Key Findings
(i) The study showed a very high to high carbon emissions taking place in the eastern Himalayan States, western desert region, and lower Himalayan region.
(ii) It was observed flat occurrence of high fire intensity at the low altitude Himalayan hilly regions may be due to the plant species (pine trees) or surrounding villages, which make them susceptible to anthropogenic activities like forest cover clearance, grazing, etc.
(iii) Sharp increase in average and maximum air temperature decline in precipitation, and change in land-use patterns have caused the increased occurrence of forest fires in most of Asia.
Further Planning
With a view to predict forest fires and identify forest fire hotspots, the team further plans to develop advanced machine learning models and artificial intelligence (AI)-based techniques.
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