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Nationwide Assessment of Forest Burnt Area in India Using Resourcesat-2 AWiFS Data


Affiliations
1 National Remote Sensing Centre, Indian Space Research Organisation, Balanagar, Hyderabad 500 037, India
 

This study provides application of Resourcesat-2 AWiFS satellite imagery for forest burnt area assessment in India. AWiFS datasets covering peak forest fire months of 2014 have been analysed. The total burnt area under vegetation cover (forest, scrub and grasslands) of India was estimated as 57,127.75 sq. km. In 2014, 7% of forest cover of India was affected by fires. Of the major forest types, dry deciduous forests are affected by the highest burnt area, followed by moist deciduous forests. Among the biogeographic zones, the highest forest burnt area was recorded in Deccan followed by North East and Western Ghats. The highest burnt area was recorded in Odisha followed by Andhra Pradesh, Maharashtra, Chhattisgarh, Tamil Nadu, Madhya Pradesh, Telangana, Jharkhand, Manipur and Karnataka. Spatial analysis shows that 232 grid cells in India have a burnt area greater than 20 sq. km. The database generated would be useful in ecological damage assessment, fire risk modelling, carbon emissions accounting and biodiversity conservation.

Keywords

AWiFS, Forest Fire, Forest Type, India, Remote Sensing.
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  • Beringer, J., Hutley, L. B., Tapper, N. J., Coutts, A., Kerley, A. and O’Grady, A. P., Fire impacts on surface heat, moisture and carbon fluxes from a tropical savanna in northern Australia. Int. J. Wildland Fire, 2003, 12, 333–340.
  • FAO, 2003; http://www.fao.org/english/newsroom/news/2003/21962-en.html
  • Puyravaud, J. P., Pascal, J. P. and Dufour, C., Ecotone structure as an indicator of changing forest-savanna boundaries (Linganamakki Region, southern India). J. Biogeogr., 1994, 21(6), 581–593.
  • Kucera, J. and Yasuoka, Y., Retrieval of forest fire history in Far East Asia by remote sensing and its analysis with biomass burning Simulation and climate anomalies. Global Environ. Change Ocean and on Land. Terrapub. Tokyo, 2004, 411–424.
  • IPCC, Fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, 2007.
  • Meyn, A., White, P. S., Buhk, C. and Jentsch, A., Environmental drivers of large, infrequent wildfires: the emerging conceptual model. Prog. Phys. Geogr., 2007, 31(3), 287–312.
  • Kraus, D. and Goldammer, J. G., Fire regimes and ecosystems: an overview of fire ecology in tropical ecosystems. Forest fires in India – workshop proceedings (ed. Schmerbeck, J., Hiremath, A. and Ravichandran, C.). ATREE, Bangalore, India and Institute of Silviculture, Freiburg, Germany, 2007, pp. 9–13.
  • Oliver, J. G. J., Janssens-Maenhout, G., Muntean, M. and Peters, J., Trends in global CO2 emissions; 2013 Report, The Hague: PBL Netherlands Environmental Assessment Agency; ISPRA: Joint Research Centre, 2013.
  • Schmerbeck, J., Hiremath, A. and Ravichandran, C., Forest fires in India – Workshop Proceedings. ATREE, Bangalore, India & Institute of Silviculture, Freiburg, Germany, 2007.
  • Jaiswal, R. K., Mukherjee, S., Raju, K. D. and Saxena, R., Forest fire risk zone mapping from satellite imagery and GIS. Int. J. Appl. Earth Obs., 2002, 4(1), 1–10.
  • Gubbi, S., Fire, fire burning bright. Deccan Herald, Bangalore, India, 2003; http://www. Wildlife first.info/images/worldfiles/fire.doc (accessed on 15 August 2014).
  • Satendra and Kaushik, A. D., Forest fire disaster management. National Institute of Disaster Management, Delhi, 2012.
  • Joseph, S., Anitha, K. and Murthy, M. S. R., Forest fire in India: a review of the knowledge base. J. For. Res., 2009, 14, 127–134.
  • Badarinath, K. V. S. and Prasad, K. V., Carbon dioxide emissions from forest biomass burning in India. Global Environ. Res., 2011, 15, 45–52.
  • Eva, H. and Lambin, E. F., Burnt area mapping in Central Africa using ATSR data. Int. J. Remote Sens., 1998, 19, 3473–3497.
  • Chuvieco, E., Deshayes, M., Stach, N., Cocero, D. and Riano, D., Short-term fire risk: foliage moisture content estimation from satellite data. In Remote Sensing of Large Wildfires in the European Mediterranean Basin (ed. Chuvieco, E.), Berlin, SpringerVerlag, 1999, pp. 17–38.
  • Roy, P. S., Forest fire and degradation assessment using satellite remote sensing and geographic information system. Proceedings of a Training Workshop Satellite Remote Sensing and GIS Applications in Agricultural Meteorology, 2003, pp. 361–400.
  • Lentile, L. B., Holden, Z. A., Smith, A. M., Falkowski, M. J., Hudak, A. T., Morgan, P. and Benson, N. C., Remote sensing techniques to assess active fire characteristics and post-fire effects. Int. J. Wildland Fire, 2006, 15(3), 319–345.
  • Sedano, F., Kempeneers, P., Strobl, P., McInerney, D. and San Miguel, J., Increasing spatial detail of burned scar maps using IRS–AWiFS data for Mediterranean Europe. Remote Sensing, 2012, 4(3), 726–744.
  • Chirici, G. and Corona, P., An overview of passive remote sensing for post-fire monitoring. Forest, 2005, 2(3), 282–289.
  • NRSA, Perspectives of geoinformatics in forest fire management (Indian Forest Fire Response and Assessment System). Technical Report, National Remote Sensing Agency, Hyderabad, 2006.
  • MoEF, 2014; http://www.icfre.gov.in/UserFiles/File/Institute-ICFRE/2013/Stat/section (accessed on 12 January 2015).
  • FSI, State of Forest Report. Ministry of Environment and Forests, Government of India, 1995.
  • IFFN, Fire situation in India, 2002, pp. 23–27.
  • Chand, K. T. R., Badarinath, K. V. S., Prasad, K. V., Murthy, M. S. R., Elvidge, C. D. and Tuttle, B. T., Monitoring forest fires over the Indian region using DMSP-OLS nighttime satellite data. Remote Sens. Environ., 2006, 103, 165–178.
  • Harikrishna, P. and Reddy, C. S., Assessment of increasing threat of forest fires in Rajasthan, India using multi-temporal remote sensing data (2005–2010). Curr. Sci., 2012, 102(9), 1288–1297.
  • Giriraj, A., Shilpa, B., Jentsch, A., Sudhakar, S. and Murthy, M. S. R., Tracking fires in India using advanced along track scanning radiometer (A) ATSR data. Remote Sensing, 2010, 2, 591–610.
  • Badarinath, K. V. S., Sharma, A. R. and Kharol, S. K., Forest fire monitoring and burnt area mapping using satellite data: a study over the forest region of Kerala State, India. Int. J. Remote Sens., 2011, 32, 85–102.
  • Reddy, C. S., Harikrishna, P., Anitha, K. and Joseph, S., Mapping and inventory of forest fires in Andhra Pradesh, India: current status and conservation needs. ISRN Forestry, 2012; doi:10.5402/2012/380412
  • Sharma, R. K., Sharma, N., Shrestha, D. G., Luitel, K. K., Arrawatia, M. L. and Pradhan, S., Study of forest fires in Sikkim Himalayas, India using remote sensing and GIS techniques. Climate Change in Sikkim – Patterns, Impacts and Initiatives, 2012, 233–244.
  • Reddy, C. S., Khuroo, A. A., Hari Krishna, P., Saranya, K. R. L., Jha, C. S. and Dadhwal, V. K., Threat evaluation for biodiversity conservation of forest ecosystems using geospatial techniques: a case study of Odisha, India. Ecol. Eng., 2014, 69, 287–303.
  • Reddy, C. S., Navatha, K., Rachel, B., Murthy, M. S. R. and Manikya Reddy, P., Forest fire monitoring in Sirohi district, Rajasthan using remote sensing data. Curr. Sci., 2009, 97(9), 1287–1290.
  • Kodandapani, N., Cochrane, M. A. and Sukumar, R., Conservation threat of increasing fire frequencies in the Western Ghats, India. Conser. Biol., 2004, 18, 1553–1561.
  • Somashekar, R. K., Ravikumar, P., Kumar, C. M., Prakash, K. L. and Nagaraja, B. C., Burnt area mapping of Bandipur National Park, India using IRS 1C/1D LISS III data. J. Indian Soc. Remote Sens., 2009, 37(1), 37–50.
  • Kodandapani, N., Contrasting fire regimes in a seasonally dry tropical forest and a savanna ecosystem in the Western Ghats, India. Fire Ecol., 2013; doi:10.4996/fireecology.0902102
  • Sowmya, S. V. and Somashekar, R. K., Application of remote sensing and geographical information system in mapping forest fire risk zone at Bhadra wildlife sanctuary, India. J. Environ. Biol., 2010, 31(6), 969–974.
  • Sudeesh, S. and Reddy, C. S., Forest fire monitoring in NagarjunasagarSrisailam Tiger Reserve, Andhra Pradesh, India using geospatial techniques. Natl. Acad. Sci. Lett., 2013, 36(4), 437–446.
  • Saranya, K. R. L., Reddy, C. S., Prasada Rao, P. V. V. and Jha, C. S., Decadal time scale monitoring of Forest Fires in Similipal Biosphere Reserve, India using Remote sensing and GIS. Environ. Monit. Assess., 2014, 186, 3283–3296.
  • FSI, State of Forest Report, Ministry of Environment and Forests, Government of India, 2009.
  • Anon., 2011; http://censusindia.gov.in/2011-common/CensusData Summary.html
  • Rodgers, W. A. and Panwar, H. S., Planning a Wildlife Protected Area Network in India. Wildlife Institute of India, Dehradun, 1988.
  • MoEF, 2011; http://www.icfre.gov.in/UserFiles/File/Institute-ICFRE/2013/Stat/section (accessed on 12 January 2015).
  • http://glcf.umiacs.umd.edu/
  • Chavez, P. S., Image-based atmospheric corrections – revisited and improved. Photogramm. Eng. Rem. S., 1996, 62, 1025–1036.
  • NRSC. Natural Resources Census: National land use and land cover mapping using multi-temporal AWiFS data. Technical report. National Remote Sensing Centre, Hyderabad, India, 2013.
  • Reddy, C. S., Jha, C. S., Diwakar, P. G. and Dadhwal, V. K., Nationwide classification of forest types of India using remote sensing and GIS Environ. Monitor. Assess., 2015; doi: 10.1007/s10661-015-4990-8.
  • Farr, T. G. et al., The shuttle radar topography mission. Rev. Geophys., 2007, 45, RG2004.
  • https://earthdata.nasa.gov/data/near-real-time-data/firms/active-firedata
  • Dawson, T. P., Butt, N. and Miller, F., The ecology of forest fires. ASEAN Biodiversity, 2002, 1, 18–21.
  • IMD, 2014; http://www.imd.gov.in/doc/report2014.pdf (accessed on 2 April 2015).
  • IMD, 2009; http://www.imd.gov.in/doc/warm2009 (accessed on 8 February 2013).
  • FSI, State of Forest Report. Ministry of Environment and Forests, Government of India, 2013.
  • Manhas, R. K., Negi, J. D. S., Kumar, R. and Chauhan, P. S., Temporal assessment of growing stock, biomass and carbon stock of Indian forests. Climatic Change, 2006, 74, 191–221.
  • MoEF, National Biodiversity Action Plan, New Delhi, India, Ministry of Environment and Forests. Government of India, 2009.
  • Srivastava, S. K., Saran, S., Rolf A. de By and Dadhwal, V. K., A geo-information system approach for forest fire likelihood based on causative and anti-causative factors. Int. J. Geographical Inf. Sci., 2014, 28(3), 427–454.
  • Chuvieco, E. et al., Development of a framework for fire risk assessment using remote sensing and geographic information system technologies. Ecol. Modelling, 2010, 221, 46–58.
  • Martínez, J., Vega-Garcia, C. and Chuvieco, E., Human-caused wildfire risk rating for prevention planning in Spain. J. Environ. Manage., 2009, 90, 1241–1252.
  • Prasad, V. K., Badarinath, K. V. S. and Eaturu, A., Biophysical and anthropogenic controls of forest fires in the Deccan Plateau, India. J. Environ. Manage., 2007, 86(1), 1–13.
  • Vadrevu, K. P., Eaturu, A. and Badarinath, K. V. S., Fire risk evaluation using multicriteria analysis – a case study. Environ. Modeling Assess., 2009. 166(1–4), 223–239.

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  • Nationwide Assessment of Forest Burnt Area in India Using Resourcesat-2 AWiFS Data

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Authors

C. Sudhakar Reddy
National Remote Sensing Centre, Indian Space Research Organisation, Balanagar, Hyderabad 500 037, India
C. S. Jha
National Remote Sensing Centre, Indian Space Research Organisation, Balanagar, Hyderabad 500 037, India
G. Manaswini
National Remote Sensing Centre, Indian Space Research Organisation, Balanagar, Hyderabad 500 037, India
V. V. L. Padma Alekhya
National Remote Sensing Centre, Indian Space Research Organisation, Balanagar, Hyderabad 500 037, India
S. Vazeed Pasha
National Remote Sensing Centre, Indian Space Research Organisation, Balanagar, Hyderabad 500 037, India
K. V. Satish
National Remote Sensing Centre, Indian Space Research Organisation, Balanagar, Hyderabad 500 037, India
P. G. Diwakar
National Remote Sensing Centre, Indian Space Research Organisation, Balanagar, Hyderabad 500 037, India
V. K. Dadhwal
National Remote Sensing Centre, Indian Space Research Organisation, Balanagar, Hyderabad 500 037, India

Abstract


This study provides application of Resourcesat-2 AWiFS satellite imagery for forest burnt area assessment in India. AWiFS datasets covering peak forest fire months of 2014 have been analysed. The total burnt area under vegetation cover (forest, scrub and grasslands) of India was estimated as 57,127.75 sq. km. In 2014, 7% of forest cover of India was affected by fires. Of the major forest types, dry deciduous forests are affected by the highest burnt area, followed by moist deciduous forests. Among the biogeographic zones, the highest forest burnt area was recorded in Deccan followed by North East and Western Ghats. The highest burnt area was recorded in Odisha followed by Andhra Pradesh, Maharashtra, Chhattisgarh, Tamil Nadu, Madhya Pradesh, Telangana, Jharkhand, Manipur and Karnataka. Spatial analysis shows that 232 grid cells in India have a burnt area greater than 20 sq. km. The database generated would be useful in ecological damage assessment, fire risk modelling, carbon emissions accounting and biodiversity conservation.

Keywords


AWiFS, Forest Fire, Forest Type, India, Remote Sensing.

References





DOI: https://doi.org/10.18520/cs%2Fv112%2Fi07%2F1521-1532