Forest Fire Burnt Area Assessment in the Biodiversity Rich Regions Using Geospatial Technology: Uttarakhand Forest Fire Event 2016
- 186 Downloads
The hills of Uttarakhand witness forest fire every year during the summer season and the number of these fire events is reported to have increased due to increased anthropogenic disturbances as well as changes in climate. These fires cause significant damage to the natural resources which can be mapped and monitored using satellite images by virtue of its synoptic coverage of the landscape and near real time monitoring. This study presents burnt area assessment caused by the fire episode of April 2016 to the forest vegetation. Digital classification of satellite images was done to extract the burnt area which was found to be 3774.14 km2, representing 15.28% of the total forest area of the state. It also gives an account of cumulative progression of forest fire in Uttarakhand using satellite images of three dates viz. 23rd, 27th May and 2nd June, 2016. Results were analyzed at district, administrative and forest division level using overlay analysis. Separate area statistics were given for different categories of biological richness, forest types and protected areas affected by forest fire. The burnt area assessment can be used in mitigation planning to prevent drastic ecological impacts of the forest fire on the landscape.
KeywordsForest fire Uttarakhand Remote sensing Burnt area assessment
The authors acknowledge National Remote Sensing Centre (NRSC), ISRO for providing satellite data and Indian Institute of Remote Sensing for the funding and the laboratory facility to carry out the work.
Funding was provided by Department of Space, Government of India.
- Ankila, H. (2007). Forest fires in India: Extent, justification and policy. In J. Schmerbeck, A. Hiremath & C Ravichandran (Eds.), Fires in Indian forests,Workshop proceedings ATREE, Bangalore, India. Freiburg, Germany:Institute of Silviculture.Google Scholar
- Bahuguna, V. K., & Singh, S. (2002). Fire situation in India. International Forest Fire News, 26, 23–27.Google Scholar
- Bhandari, B. S., Mehta, J. P. & Semwal, R. L. (2012). Forest fire in Uttarakhand Himalaya: An overview. In G.C.S. Negi, & P.P. Dhyani (Eds.) Glimpses of Forestry Research in the Indian Himalayan Region, Special Issue on International Year of Forests–2011 (pp. 167–175). Almora: G.B. Pant Institute of Himalayan Environment and Development.Google Scholar
- Chand, T. K., Badarinath, K. V. S., Prasad, V. K., Murthy, M. S. R., Elvidge, C. D., & Tuttle, B. T. (2006). Monitoring forest fires over the Indian region using Defense Meteorological Satellite Program-Operational Linescan System nighttime satellite data. Remote Sensing of Environment, 103(2), 165–178.CrossRefGoogle Scholar
- Gubbi S. (2003). Fire, fire burning bright! Deccan Herald, Bangalore, India. http://wildlifefirst.info/images/wordfiles/fire.doc. Accessed January 2004.
- Jain, A., Roy, P. S., Ravan, S. A., Singh, R. K., & Das, K. K. (1996). Fire risk modelling using remote sensing and geographic information system. Current Science, 70(10), 928–933.Google Scholar
- Landmann, G., Held, A., Schuck, A. & Van Brusselen, J. (2015). European forests at risk. A scoping study in support of the development of a European Forest Risk Facility. European Forest Institute. https://doi.org/10.13140/RG.2.1.1927.2169
- Marschall, J. M. (2013). Timber product value loss due to prescribed fire caused injuries in red oak trees. M.S. Dissertation Thesis, Columbia, USA:University of Missouri-Columbia.Google Scholar
- Rothermel, R. C. (1983). How to predict the spread and intensity of forest and range fires. In The Bark beetles, fuels, and fire bibliography (p. 70).Google Scholar
- Rowell, A. & Moore, P. F. (2000). Global review of forest fires. Forests for Life Programme Unit, WWF International. Gland, Switzerland:IUCN.Google Scholar
- Roy, P. S. (2003). Forest fire and degradation assessment using satellite remote sensing and geographic information system. In Satellite remote sensing and GIS applications in agricultural meteorology (p. 361).Google Scholar
- Roy, P. S., Kushwaha, S. P. S., Murhty, M. S. R., Roy, A., Kushwaha, D., Reddy, C. S., Behera, M. D., Mathur, V. B., Padalia, H., Saran, S., Singh, S., Jha, C. S. & Porwal, M. C. (2012). Biodiversity characterization at landscape level: National assessment (p. 140) Indian Institute of Remote Sensing, Dehradun. ISBN 81-901418-8-0.Google Scholar
- SFR. (2015). India State of Forest Report. Dehradun: Forest Survey of India.Google Scholar
- Spanos, I., Ganatsas, P., & Tsakaldimi, M. (2010). Evaluation of postfire restoration in suburban forest of Thessaloniki, Northern Greece. Global Nest Journal, 12, 390–400.Google Scholar
- The IUCN Red List of Threatened Species. Version 2017-3. www.iucnredlist.org. Downloaded on 02 January 2018.
- UNISDR/GE/2015—ICLUX EN5000. (2015). United Nations, Office for Disaster Risk Reduction. Sendai framework for disaster risk reduction 2015–2030 (1st ed.).Google Scholar
- Vallejo, R., Hatzistathis, A., Bellot, J. & Serrasolses, I. (2000). Reclamation of Mediterranean Ecosystems affected by wildfires: Forest management recommendations. In P. Balabanis, D. Peter, A. Ghazi, & M. Tsogas (Eds.), Mediterranean desertification. Research results and policy implications (pp. 407–416). Belgium:European CommissionGoogle Scholar