THE PLAUSIBLE WILDFIRE MODEL IN GEOINFORMATION DECISION SUPPORT SYSTEM FOR WILDFIRE RESPONSE

Ager, A. A. Modeling wildfire risk to northern spotted owl. Forest Ecology and Management, vol. 246, pp 45-56, 2007.

Atkinson, D., Chladil, M., Janssen, V., Lucieer, A. Implementation of quantitative bushfire risk analysis in a GIS environment. Int. J. of Wildland Fire, vol. 19, pp -658, 2010.

Baranovskiy, N., Zharikova, M. A web-oriented geoinformation system for forest fire danger prediction in typical forests of the Ukraine. Thematic cartography for International Multidisciplinary Scientific GeoConfenferences SGEM 2015 www.sgem.org Section Forest Ecosystems the society. Lecture notes in geoinformation and cartography, Springer, pp 13-22, 2014.

Baranovsliy N.V. Integral assessment of forest fire danger. Ecology and Industry of Russia, vol 3, pp 58-59, 2010.

Chuvieco, E., Aguadoa, I., Yebraa, M., Nietoa, H., and others. Development of a framework for fire risk assessment using remote sensing and geographic information system technologies. Ecological Modelling, vol. 221, pp 46-58, 2010.

Genton, M., Butry, D. T., Gumpertz, M. L., Prestemon, J. P. Spatiotemporal analysis of wildfire ignitions in the St. Johns River Water Management District, Florida. Int. J. of Wildland Fire, vol. 15, pp 87-97, 2006.

Grab, M. V. Modeli, metodyi i algoritmyi rasprostraneniya lesnyih pozharov: diss. kand. tehn. nauk, Harkov, 230 p, 2004.

Martinez, J., Vega-Garcia, C., Chuvieco, E. Human-caused wildfire risk rating for prevention planning in Spain. J. of Environmental Management, vol. 90, pp 1241- 1252, 2009.

Miller, C., Ager, A. A. A review of recent advances in risk analysis for wildfire management, Int. J. of Wildland Fire, vol, 22, pp 1-14, 2013.

Pawlak, Z. Vagueness – a Rough Set View. Structures in Logic and Computer Science, pp 106-117, 1997.

Pawlak, Z., Jerzy, W., Slowinski, R., Ziarko, W. Rough Sets. Comm. of ACM, vol. 38(11), pp 88-95, 1995.

Preisler, H., Brillinger, D.R., Burgan, E., Benoit, J.W. Probability based models for estimating wildfire risk. Int. J. of Wildland Fire, vol. 13, pp 133-142, 2004.

Prestemon, J. P., Pye, J. M., Butry, D. T., Holmes, T. P., Mercer, D. E. Understanding broadscale wildfire risks in a human-dominated landscape. Forest Science, vol. 48, pp 685-693, 2002.

Tolhurst, K., Shields, B., Chong, D. Phoenix: development and application of a bushfire risk management tool. The Australian Journal of Emergency Management, 23(4), pp 47- 54 , 2008.

Zadeh, L. From computing with numbers to computing with words – from manipulation of measurements to manipulation of perceptions. Int. J. of Applied Math. and Computer Science, vol. 12(3), pp 307-324, 2002. International Multidisciplinary Scientific GeoConfenferences SGEM 2015 www.sgem.org 15th International Multidisciplinary Scientific GeoConferences SGEM2015 International Multidisciplinary Scientific GeoConfenferences SGEM 2015 www.sgem.org

Ager, A. A. Modeling wildfire risk to northern spotted owl. Forest Ecology and Management, vol. 246, pp 45-56, 2007.

Atkinson, D., Chladil, M., Janssen, V., Lucieer, A. Implementation of quantitative bushfire risk analysis in a GIS environment. Int. J. of Wildland Fire, vol. 19, pp -658, 2010.

Baranovskiy, N., Zharikova, M. A web-oriented geoinformation system for forest fire danger prediction in typical forests of the Ukraine. Thematic cartography for International Multidisciplinary Scientific GeoConfenferences SGEM 2015 www.sgem.org Section Forest Ecosystems the society. Lecture notes in geoinformation and cartography, Springer, pp 13-22, 2014.

Baranovsliy N.V. Integral assessment of forest fire danger. Ecology and Industry of Russia, vol 3, pp 58-59, 2010.

Chuvieco, E., Aguadoa, I., Yebraa, M., Nietoa, H., and others. Development of a framework for fire risk assessment using remote sensing and geographic information system technologies. Ecological Modelling, vol. 221, pp 46-58, 2010.

Genton, M., Butry, D. T., Gumpertz, M. L., Prestemon, J. P. Spatiotemporal analysis of wildfire ignitions in the St. Johns River Water Management District, Florida. Int. J. of Wildland Fire, vol. 15, pp 87-97, 2006.

Grab, M. V. Modeli, metodyi i algoritmyi rasprostraneniya lesnyih pozharov: diss. kand. tehn. nauk, Harkov, 230 p, 2004.

Martinez, J., Vega-Garcia, C., Chuvieco, E. Human-caused wildfire risk rating for prevention planning in Spain. J. of Environmental Management, vol. 90, pp 1241- 1252, 2009.

Miller, C., Ager, A. A. A review of recent advances in risk analysis for wildfire management, Int. J. of Wildland Fire, vol, 22, pp 1-14, 2013.

Pawlak, Z. Vagueness – a Rough Set View. Structures in Logic and Computer Science, pp 106-117, 1997.

Pawlak, Z., Jerzy, W., Slowinski, R., Ziarko, W. Rough Sets. Comm. of ACM, vol. 38(11), pp 88-95, 1995.

Preisler, H., Brillinger, D.R., Burgan, E., Benoit, J.W. Probability based models for estimating wildfire risk. Int. J. of Wildland Fire, vol. 13, pp 133-142, 2004.

Prestemon, J. P., Pye, J. M., Butry, D. T., Holmes, T. P., Mercer, D. E. Understanding broadscale wildfire risks in a human-dominated landscape. Forest Science, vol. 48, pp 685-693, 2002.

Tolhurst, K., Shields, B., Chong, D. Phoenix: development and application of a bushfire risk management tool. The Australian Journal of Emergency Management, 23(4), pp 47- 54 , 2008.

Zadeh, L. From computing with numbers to computing with words – from manipulation of measurements to manipulation of perceptions. Int. J. of Applied Math. and Computer Science, vol. 12(3), pp 307-324, 2002. International Multidisciplinary Scientific GeoConfenferences SGEM 2015 www.sgem.org 15th International Multidisciplinary Scientific GeoConferences SGEM2015 International Multidisciplinary Scientific GeoConfenferences SGEM 2015 www.sgem.org