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Geospatial Assessment of Forest Fires in Jharkhand (India)


  • Vindhyan Ecology and Natural History Foundation, Mirzapur – 231001, Uttar Pradesh, India


Background: The forests in India and worldwide are threatened by many factors, one among them being the increasing frequency of forest fires. It damages the forest ecosystem and the environment thus altering the global climate. A proper monitoring and understanding of forest fires both spatially and temporally would assist in management of forest and help in protecting the biodiversity and wildlife habitat. Satellite remote sensing and GIS help in visualizing the extent and damage of forest fire at various scales and time periods. Objectives: To analyze the incidences of forest fires in Jharkhand state of India. Forest fire hotspot district were identified and analyzed. Methods/Statistical Analysis: The forest fire point data from the year 2005 to 2016 was analyzed in GIS domain for Jharkhand. The Landsat-8 data was utilized to obtain the forest cover of 2015 for Paschim Singhbhum district. The 2km*2km grid was generated to evaluate each grid with reference to forest fire incidence. Findings: Analysis of the datasets revealed that highest forest fire district of Jharkhand state is Paschim Singhbhum, it retain 30% of total forest fire whereas it contain approximately 17 % of the state forest cover. The study reveals very high frequency of forest fire grids in Paschim Singhbhum district falls in north-west of Pansuan dam of Porhat forest division. It provides a spatial view of forest fire occurrence, spread over duration of time which can be incorporated in management objectives to deal with the adverse effect of forest fire. Application/Improvements: Appropriate measures can focus on the particular very high to medium forest fire grid to minimize the effect of forest fire impact.


Conservation and Management, Forest Fire, GIS, GRID Analysis, Jharkhand, Paschim Singhbhum

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  • Davidenko EP, Eritsov A. The fire season 2002 in Russia.Report of the Aerial Forest Fire Service, Avialesookhrana. International Forest Fire News. 2003; 28:15–7.
  • Kudoh J. Report of the View of Northeast Asia Forest Fire from Cosmos: International Symposium, Center for Northeast Asian Studies (CNEAS), Sendai, Miyagi, Japan: Tohoku University; 2005. p. 1–5.
  • Rodriguez Y, Silva F, Molina JR, Gonzalez-Caban A, Herrera MA. Economic vulnerability of timber resources to forest fires. Journal of Environmental Management. 2012; 100:16–21. Crossref, PMid:22343614
  • Chen Z. Effects of fire on major forest ecosystem process: an overview. Chinese Journal of Applied Ecology. 2006; 17(9):1726–32. PMid:17147189
  • Tropical T. Secretariat of the Convention on Biological Diversity. Impacts of human-caused fires on biodiversity and ecosystem functioning, and their causes in tropical, temperate and boreal forest biomes, Montreal. SCBD (CBD Technical Series no. 5). 2001; 42:1–38.
  • Roy PS. Forest fire and degradation assessment using satellite remote sensing and geographic information system fire and degradation assessment using satellite remote sensing and geographic information system. Satellite Remote Sensing and GIS Applications in Agricultural Meteorology. 2003. p. 361–400. PMid:12686158
  • Srivastava RK, Singh D. Forest Fire, Haze Pollution and Climate Change. Special issue: Climate change and forestryPart 1. Indian Forester. 2003; 129:725–34.
  • Ramanathan V, Chung C, Kim D, Bettge T, Buja L, Kiehl JT, Washington WM, Fu Q, Sikka DR and Wild M. Atmospheric brown clouds: impacts on South Asian climate and hydrological cycle. Proceedings of National Academy of Sciences of the United States of America. 2005; 102:5326–33.Crossref, PMid:15749818 PMCid:PMC552786
  • Crutzen PJ, Andreae MO. Biomass burning in the tropics: impact on atmospheric chemistry and biogeochemical cycles. Science. 1990; 250(4988):1669–78. Crossref, PMid:17734705
  • Kutiel P, Inbar M. Fire impacts on soil nutrients and soil erosion in a mediterranean pine forest plantation. Catena.1993; 20:129–39. Crossref
  • Capitanio R, Carcaillet C. Post-fire mediterranean vegetation dynamics and diversity: A discussion of succession models.Forest Ecology and Management. 2008; 255:431–9. Crossref
  • Engstrom RT. First-order fire effects on animals: review and recommendations. The Journal of the Association for Fire Ecology. 2010; 6:115–30. Crossref
  • Aggarwal A, Paul V, Das S. Forest Resources: Degradation, Livelihoods, and Climate Change. In Datt D, Nischal S. Eds.Looking Back to Change Track. New Delhi: TERI; 2009. p.91–108. PMid:19183396
  • Ferreira AJD, Coelho COA, Ritsema CJ, Boulet AK, Keizer JJ. Soil and water degradation processes in burned areas: Lessons learned from a nested approach. Catena. 2008; 74:273–85. Crossref
  • Rodgers WA, Panwar HS, Mathur VB. Wildlife Protected Area Network in India- A Review: Executive Summary.Dehradun, India: Wildlife Institute of India; 2002. p. 44.
  • Wikramanayake ED, Dinerstein E, Robinson JG, Karanth KU, Rabinowitz A, Olson D, Mathew T, Hedao P, Corner M, Hemley G, Bolze D. An ecology-based method for defining priorities for large mammal conservation: the tiger as case study. Conservation Biology. 1998; 12:865–78. Crossref
  • Saha S, Howe HF. The bamboo fire cycle hypothesis: a comment. American naturalist. 2001; 158:659–63. Crossref
  • Reddy CS, Jha CS, Manaswini G, Alekhya VVLP, Pasha SV, Satish KV, Diwakar PG, Dadhwal VK. Nationwide assessment of forest burnt area in India using Resourcesat-2 AWiFS data. Current Science. 2017; 112(7):1521–32.
  • Castellnou M, Pages J, Miralles M, Pique M. Wildland fire typologies in Catalonia. Fire mapping design as a tool for forest management. Proceedings of 5° Congreso Forestal Espanol, Avila (Spain). 2009; 16:9–14.
  • Lecina-Diaz J, Alvarez A, Retana J. Extreme Fire Severity Patterns in Topographic, Convective and Wind-Driven Historical Wildfires of Mediterranean Pine Forests. PLoS ONE. 2014; 9(1):1–13. Crossref, PMid:24465492 PMCid:PMC3899010
  • Duane A, Pique M, Castellnou M, Brotons L. Predictive modelling of fire occurrences from different fire spread patterns in Mediterranean landscapes. International Journal of Wildland Fire. 2015; 24(3):407–18. Crossref
  • Rothermel RC. How to predict the spread and intensity of forest and range fires. Intermountain Forest and Range Experiment Station, USDA Forest Service, Ogden, UT, USA. General Technical Report INT-143. 1983; 161:1–168.
  • Anderson HE. Heat transfer and fire spread. Intermountain Forest and Range Experiment Station, USDA Forest Service, Ogden, UT, USA. Research Paper INT-69. 1969; 23:1–29.
  • Betts RA. Forcings and feedbacks by land ecosystem changes on climate change. J. Phys. IV France. 2006; 139:123–46. Crossref
  • Vadrevu KP, Csiszar I, Ellicott E, Giglio L, Badarinath KVS, Vermote E, Justice C. Hotspot Analysis of Vegetation Fires and Intensity in the Indian Region. IEEE Journal of selected topics in applied Earth Observations and Remote Sensing. 2013; 6(1):224–38. Crossref
  • Bahugunaand VKA, Upadhyay A. Forest fires in India: Policy initiatives for community participation. Int. Forestry Review. 2002; 4(2):122–7. Crossref
  • Champion HG, Seth SK. A Revised Survey of the Forest Types of India. New Delhi: Government of India Publication; 1968. PMCid:PMC1010472
  • Krishna PH, Reddy CS. Assessment of increasing threat of forest fires in Rajasthan, India using multi-temporal remote sensing data (2005–2010). Current Science. 2012; 102(9):1288–97.
  • Prasad VK, Badarinath KVS, Anuradha E, Biophysical and anthropogenic controls of forest fire in the Deccan plateau. India. J. Environ. Manag. 2008; 86:1–13. Crossref, PMid:17275159
  • Joseph S, Anitha K, Murthy MSR, Forest fire in India: a review of the knowledge base. J. For. Res. 2009; 14:127–34.Crossref
  • Chand TRK, Badarinath KVS, Prasad VK, Murthy MSR, Elvidge CD, Tuttle BT. Monitoring forest fires over the Indian region using DMSP-OLS nighttime satellite data. Remote Sensing Environ. 2006; 103:165–78. Crossref
  • Giriraj A, Shilpa B, Jentsch A, Sudhakar S, Murthy MSR, Tracking fires in India using advanced along track scanning radiometer (A)ATSR data. Remote Sensing. 2010; 2:591– 610. Crossref
  • Jharkhand Economic Survey 2015-16. Available from
  • Reddy CS, Pasha SV, Jha CS, Dadhwal VK. Geospatial Characterization of Deforestation, Fragmentation and Forest Fires in Telangana State, India: Conservation Perspective. Environm Monitor. 2015; 187:455.
  • Key CH, Benson NC. Landscape assessment: ground measure of severity, the Composite Burn Index; and remote sensing of severity, the Normalized Burn Ratio. In’FIREMON: Fire Effects Monitoring and Inventory System. USDA Forest Service, Rocky Mountains Research Station General Report, 2005.
  • Diaz-Delgado R, Lloret F, Pons X. Influence of fire severity on plant regeneration by means of remote sensing imagery. International Journal of Remote Sensing. 2003; 24:1751–63. Crossref
  • Rodriguez JP, Balch JK, Rodríguez-Clark KM. Assessing extinction risk in the absence of species-level data: quantitative criteria for terrestrial ecosystems. Biodiversity and Conservation. 2007; 16:183–209. Crossref
  • Ryu SR, Chen J, Zheng D, Lacroix JJ. Relating surface fire spread to landscape structure: An application of Farsite in a managed forest landscape. Landscape and Urban Planning. 2007; 83:275–83. Crossref


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