Forest fire as a potential environmental threat in recent years in Sikkim, Eastern Himalayas, India

Sharma, Swati; Joshi, Varun; Chhetri, Roshan Kr.

doi:10.5958/j.2320-642x.2.1.006

Cited by 19 publications

(22 citation statements)

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“…Bon res by the cattle herders, burning of the forest oor to deter wild animals from entering the agrarian land, and logging induced decrease in forest canopy cover are the intentional causes of forest res in Sikkim. While, sparks from uphill moving vehicles, electric transformers located in forested areas, the use of a traditional torch called Rankoo, throwing away of live bidi, and cigarette butts are the accidental causes (Joshi et al, 2018;S. Sharma et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Maximum entropy-based forest fire likelihood mapping: analysing the trends, distribution, and drivers of forest fires in Sikkim Himalaya

Banerjee

2021

Scandinavian Journal of Forest Research

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The recent episodes of forest res in Brazil and Australia of 2019 are tragic reminders of the hazards of forest re. Globally incidents of forest re events are on the rise due to human encroachment into the wilderness and climate change. Sikkim with a forest cover of more than 47%, suffers seasonal instances of frequent forest re during the dry winter months. To address this issue, a GIS-aided and MaxEnt machine learning-based forest re prediction map has been prepared using a forest re inventory database and maps of environmental features. The study indicates that amongst the environmental features, climatic conditions and proximity to roads are the major determinants of forest res. Model validation criteria like ROC curve, correlation coe cient, and Cohen's Kappa show a good predictive ability (AUC = 0.95, COR = 0.81, κ = 0.78). The outcomes of this study in the form of a forest re prediction map can aid the stakeholders of the forest in taking informed mitigation measures.

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Section: Introductionmentioning

confidence: 99%

Maximum entropy-based forest fire likelihood mapping: analysing the trends, distribution, and drivers of forest fires in Sikkim Himalaya

Banerjee

2021

Scandinavian Journal of Forest Research

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“…Small and frequent fires, as data from Sikkim (3.2-8.6 ha/fire incident) also indicates 7 , seem to be common in much of the Himalaya. Majority of fires occur on drier and warmer facing (southern aspect) slopes, where chir-pine dominates 3 (FRI report: Spatial and temporal variations in forest fires in Uttarakhand).…”

Section: Effectiveness Of the State Forest Department In Controlling mentioning

confidence: 89%

“…Fire regime the world over is likely to change in many regions because of the global climate change and change in land-use patterns 1 . Fires in the Himalaya occur during the pre-monsoon summer period of moisture stress 3,7 , which is intensified because of global warming and resultant depletion of snowmelt water 8 . Despite being referred to as a major environmental factor, studies on forest fires in the Himalaya, particularly from an ecological standpoint are limited 9 .…”

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confidence: 99%

Nature of Forest Fires in Uttarakhand:Frequency, Size and Seasonal Patterns in Relation to Pre-Monsoonal Environment

et al. 2016

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“…Bon res by the cattle herders, burning of the forest oor to deter wild animals entering the agrarian land, logging induced decrease in forest canopy cover are the intentional causes of forest re in Sikkim. While, sparks from the uphill moving vehicles, electric transformers located in forested areas, use of traditional torch called Rankoo, throwing away of live bidi and cigarettes butts are the accidental causes of forest re (S. Sharma, Joshi, and Chhetri 2014).…”

Section: Introductionmentioning

confidence: 99%

Maximum entropy method-based forest fire prediction mapping of Sikkim Himalaya.

Banerjee¹

2020

Preprint

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The recent episodes of forest fire in Brazil and Australia of 2019 are tragic reminders of the hazards of the forest fire. Globally incidents of forest fire events are in the rise due to human encroachment into wilderness and climate change. Sikkim with a forest cover of more than 47%, suffers seasonal instances of frequent forest fire during the dry winter months. To address this issue, a GIS-aided and MaxEnt machine learning-based forest fire prediction map has been prepared using forest fire inventory database and maps of environmental features. The study indicates that amongst the environmental features, population density and proximity to roads are the major determinants of the forest fire. This indicates the role of human activities on the incidences of a forest fire. Model validation criteria like ROC curve, correlation coefficient and Cohen’s Kappa show a good predictive capability (AUC = 0.95, COR = 0.77, κ = 0.77). The outcomes of this study in the form of a forest fire prediction map can aid the stakeholders of the forest in taking informed mitigation measures.

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Forest fire as a potential environmental threat in recent years in Sikkim, Eastern Himalayas, India

Cited by 19 publications

References 0 publications

Maximum entropy-based forest fire likelihood mapping: analysing the trends, distribution, and drivers of forest fires in Sikkim Himalaya

Maximum entropy-based forest fire likelihood mapping: analysing the trends, distribution, and drivers of forest fires in Sikkim Himalaya

Nature of Forest Fires in Uttarakhand:Frequency, Size and Seasonal Patterns in Relation to Pre-Monsoonal Environment

Maximum entropy method-based forest fire prediction mapping of Sikkim Himalaya.

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