NATURAL FACTORS OF FOREST FIRE HAZARD IN THE KOSTANAY REGION AND THEIR ASSESSMENT
DOI:
https://doi.org/10.54668/2789-6323-2026-122-2-137-154Keywords:
Forest fires, forest, natural fire hazard, remote sensing (RS), geographic information systems (GIS), Kostanay regionAbstract
Forest fires are among the most hazardous natural phenomena, with their frequency and intensity increasing under current climate change conditions. In Kazakhstan, comprehensive spatial assessment of natural fire hazard remains insufficiently studied.
This study proposes a multi-factor integrated model for assessing natural fire hazard in the Kostanay region based on remote sensing (RS) data and geographic information system (GIS) technologies. The model incorporates vegetation spectral indices (NDVI, NDMI, EVI), topographic parameters, and meteorological variables. All factors were normalized, and their weights were determined using an expert-based approach. Spatial analysis was performed in the ArcGIS environment.
The results allowed for zoning the territory of the Kostanay region according to levels of natural fire hazard. It was found that a significant portion of the area falls within moderate-high and high-risk zones. The highest concentration of fire occurrences was observed in alluvial plains and areas dominated by pine forests. Verification results showed that more than 80 % of recorded fires are located within high and very high hazard zones.
The findings can be used for wildfire risk assessment, identification of high-risk areas, and improvement of fire monitoring and management systems.
References
Goldammer J.G. (ed.). Vegetation Fires and Global Change: Challenges for Concerted International Action. – Remagen-Oberwinter: Kessel Publishing House, 2013. – 398 p.
van der Werf G.R., Randerson J.T., Giglio L., Collatz G.J., Mu M., Kasibhatla P.S., Morton D.C., DeFries R.S., Jin Y., van Leeuwen T.T. Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires // Atmospheric Chemistry and Physics. – 2010. – Vol. 10. – P. 11707–11735.DOI: https://doi.org/10.5194/acp-10-11707-2010
Bowman D.M.J.S., Balch J.K., Artaxo P., Bond W.J., Carlson J.M., Cochrane M.A., D’Antonio C.M., DeFries R.S., Doyle J.C., Harrison S.P., Johnston F.H., Keeley J.E., Krawchuk M.A., Kull C.A., Marston J.B., Moritz M.A., Prentice I.C., Roos C.I., Scott A.C., Swetnam T.W., van der Werf G.R., Pyne S.J. Fire in the Earth system // Science. – 2009. – Vol. 324. – P. 481–484. DOI: https://doi.org/10.1126/science.1163886
Jolly W.M., Cochrane M.A., Freeborn P.H., Holden Z.A., Brown T.J., Williamson G.J., Bowman D.M.J.S.
Climate-induced variations in global wildfire danger from 1979 to 2013 // Nature Communications. – 2015. – Vol. 6. – Article 7537. DOI: https://doi.org/10.1038/ncomms8537
Abatzoglou J.T., Williams A.P. Impact of anthropogenic climate change on wildfire across western US forests // Proceedings of the National Academy of Sciences. – 2016. – Vol. 113. – No. 42. – P. 11770–11775.DOI: https://doi.org/10.1073/pnas.1607171113
Morton D.C., DeFries R.S., Shimabukuro Y.E., Anderson L.O., Arai E., Espirito-Santo F.D.B., Freitas R., Morisette J. Cropland expansion changes deforestation dynamics in the southern Brazilian Amazon // Proceedings of the National Academy of Sciences. – 2006. DOI: https://doi.org/10.1073/pnas.0606377103
Jones M.W., Abatzoglou J.T., Veraverbeke S., Andela N., Lasslop G., Forkel M., Smith A.J.P., Burton C., Betts R.A., van der Werf G.R., Sitch S., Canadell J.G., Santín C., Kolden C., Doerr S.H., Le Quéré C.
Global and regional trends and drivers of fire under climate change // Reviews of Geophysics. – 2022. – Vol. 60. – Article e2020RG000726.DOI: https://doi.org/10.1029/2020RG000726
Pausas J.G., Keeley J.E. Wildfires as an ecosystem service // Frontiers in Ecology and the Environment. – 2019. – Vol. 17. – No. 5. – P. 289–295.DOI: https://doi.org/10.1002/fee.2044
Chuvieco E., Salas J., Aguado I., Yebra M., Nieto H., Martín M.P., Vilar L., Martínez J., Martín S., Ibarra P., de la Riva J., Baeza J., Rodríguez F., Molina J.R., Herrera M.A., Zamora R. Towards an integrated approach to wildfire risk assessment // Fire. – 2023. – Vol. 6. – No. 5. – Article 215.DOI: https://doi.org/10.3390/fire6050215
Chepashev A. et al. Mapping fire hazard potential in Kazakhstan using remote sensing and machine learning // International Journal of Wildland Fire. – 2024. DOI: https://doi.org/10.1071/WF24232
Babu K.V.S. et al. Burned area mapping and wildfire analysis in Kazakhstan using satellite data // Frontiers in Forests and Global Change. – 2024.DOI: https://doi.org/10.3389/ffgc.2024.1296100
Zhang Y., Xiao X., Jin C., Dong J., Zhou Y., Wagle P., Joiner J., Zhang Y., Qin Y., Wang J., Moore B.
Spatiotemporal variation of burned area in Central Asia // Remote Sensing. – 2021. – Vol. 13. – No. 2. – Article 313. DOI: https://doi.org/10.3390/rs13020313
Шогелова Н., Сартин С.А. Оценка ущерба и восстановление экосистемы резервата «Семей орманы» после катастрофического пожара 2023 года на основе дистанционного зондирования // Гидрометеорология и экология. – 2025.
DOI: https://doi.org/10.54668/2789-6323-2025-118-3-141-151
Arkhipov V., Moukanov M., Khaidarov K., Goldammer J.G.
Overview on forest fires in Kazakhstan // International Forest Fire News. – 2000. – No. 22. – P. 40–48. URL: https://www.researchgate.net/publication/44159706_Overview_on_forest_fires_in_Kazakhstan
Tussupova K., Berndtsson R., Sharapatova K., Aryngazin K., Zhanasova M. Assessment of wildfire hazard on the territory of Kazakhstan // Bulletin of Geography. Physical Geography Series. – 2015. – No. 8. – P. 55–66.
URL: https://bulletin-geography.kaznu.kz/index.php/1-geo/article/view/1140
United States Geological Survey (USGS). Earth Explorer – Landsat Data Access System. URL: https://earthexplorer.usgs.gov/
Roy D.P., Wulder M.A., Loveland T.R., et al. Landsat-8: Science and product vision for terrestrial global change research // Remote Sensing of Environment. – 2014. DOI: https://doi.org/10.1016/j.rse.2014.02.001
Malczewski J. GIS-based multicriteria decision analysis: a survey of the literature // International Journal of Geographical Information Science. – 2006. – Vol. 20. – No. 7. – P. 703–726. DOI: https://doi.org/10.1080/13658810600661508
Saaty T.L. Decision making with the analytic hierarchy process // International Journal of Services Sciences. – 2008. – Vol. 1. – No. 1. – P. 83–98. DOI: https://doi.org/10.1504/IJSSCI.2008.017590
Rouse J.W., Haas R.H., Schell J.A., Deering D.W. Monitoring vegetation systems in the Great Plains with ERTS // NASA. – 1974. URL: https://ntrs.nasa.gov/citations/19740022614
Gao B.C. NDWI – A normalized difference water index for remote sensing of vegetation liquid water from space // Remote Sensing of Environment. – 1996. DOI: https://doi.org/10.1016/S0034-4257(96)00067-3
Huete A., Didan K., Miura T., Rodriguez E.P., Gao X., Ferreira L.G. Overview of the radiometric and biophysical performance of the MODIS vegetation indices // Remote Sensing of Environment. – 2002. DOI: https://doi.org/10.1016/S0034-4257(02)00096-2)
Allison, R.S., Johnston, J.M., Craig, G., Jennings, S. Airborne optical and thermal remote sensing for wildfire detection and monitoring // Sensors. – 2016. – Vol. 16. – No. 8. – 1310. https://doi.org/10.3390/s16081310
Huete, A.R., Liu, H.Q., Batchily, K., van Leeuwen, W. A comparison of vegetation indices over a global set of TM images for EOS-MODIS // Remote Sensing of Environment. – 1997.
DOI: https://doi.org/10.1016/S0034-4257(96)00112-5
Dillon, G.K., Holden, Z.A., Morgan, P., Crimmins, M.A., Heyerdahl, E.K., Luce, C.H. Both topography and climate affected forest and woodland burn severity in two regions of the western US, 1984–2006 // Ecosphere. – 2011. – Vol. 2. – No. 12. – Article 130. DOI: https://doi.org/10.1890/ES11-00271.1
Holden Z.A., Morgan P., Evans J.S., Hudak A.T. A predictive model of burn severity based on 20-year satellite-inferred burn severity data in a large southwestern US wilderness area // Forest Ecology and Management. – 2009. – Vol. 258. – No. 11. – P. 2399–2406. DOI: https://doi.org/10.1016/j.foreco.2009.08.017
Постнов А.Д., Масленников Д.А., Катаева Л.Ю., Лощилов С.А. Влияние эффектов обтекания на динамику природного пожара в условиях неоднородности рельефа // Современные проблемы науки и образования. – 2013. – № 6. URL: https://science-education.ru/article/view?id=10817
Finney M.A. FARSITE: Fire Area Simulator – model development and evaluation // Research Paper RMRS-RP-4. – Ogden, UT: U.S. Forest Service, 1998. DOI: https://doi.org/10.2737/RMRS-RP-4
Yebra M., Dennison P.E., Chuvieco E., Riaño D., Zylstra P., Hunt E.R., Danson F.M., Qi Y., Jurdao S.
A global review of remote sensing of live fuel moisture content for fire danger assessment: Moving towards operational products // Remote Sensing of Environment. – 2013. – Vol. 136. – P. 455–468.
DOI: https://doi.org/10.1016/j.rse.2013.05.029
Parks S.A., Dillon G.K., Miller C. A new metric for quantifying burn severity: the relativized burn ratio // Remote Sensing. – 2014. – Vol. 6. – No. 3. – P. 1827–1844. DOI: https://doi.org/10.3390/rs6031827
Parks S.A., Holsinger L.M., Panunto M.H., Jolly W.M., Dobrowski S.Z., Dillon G.K.
High-severity fire: evaluating its key drivers and mapping its probability across western US forests // Environmental Research Letters. – 2018. – Vol. 13. – Article 044037. DOI: https://doi.org/10.1088/1748-9326/aab791
Kane V.R., Cansler C.A., Povak N.A., Kane J.T., McGaughey R.J., Lutz J.A., Churchill D.J., North M.P.
Mixed severity fire effects within the Rim Fire: relative importance of local climate, fire weather, topography and forest structure // Forest Ecology and Management. – 2015. – Vol. 358. – P. 62–71. DOI: https://doi.org/10.1016/j.foreco.2015.09.001
Официальный сайт РГП «Казгидромет». – URL: https://www.kazhydromet.kz (дата обращения: 20.11.2024).
Flannigan M.G., Stocks B.J., Wotton B.M. Climate change and forest fires // Science of the Total Environment. – 2000. – Vol. 262. – P. 221–229. DOI: https://doi.org/10.1016/S0048-9697(00)00524-6
Flannigan M.D., Stocks B.J., Turetsky M.R., Wotton B.M. Impacts of climate change on fire activity and fire management in the circumboreal forest // Global Change Biology. – 2009. – Vol. 15. – No. 3. – P. 549–560. DOI: https://doi.org/10.1111/j.1365-2486.2008.01660.x
Wotton M.D., Martell D.L. A lightning fire occurrence model for Ontario // Canadian Journal of Forest Research. – 2005. – Vol. 35. – P. 1389–1401. DOI: https://doi.org/10.1139/x05-071
Schoennagel T., Veblen T.T., Romme W.H. The interaction of fire, fuels, and climate across Rocky Mountain forests // BioScience. – 2004. – Vol. 54. – No. 7. – P. 661–676. DOI: https://doi.org/10.1641/0006-3568(2004)054[0661:TIOFFA]2.0.CO;2
Иванов Б.Г. «Испарение в естественных условиях». — Л.: Гидрометеоиздат, 1954.
Stehman S.V. Selecting and interpreting measures of thematic classification accuracy // Remote Sensing of Environment. – 1997. – Vol. 62. – P. 77–89. DOI: https://doi.org/10.1016/S0034-4257(97)00083-7
Turyuzhanova A.T., Nurmagambetova A.M. Comprehensive socio-economic analysis of the Kostanay region // Bulletin of L.N. Gumilyov Eurasian National University. Chemistry. Geography. Ecology Series. – 2021. – № 3(136). – P. 63–72.
Fire Information for Resource Management System (FIRMS). – URL: https://firms.modaps.eosdis.nasa.gov/ (дата обращения: 20.04.2024).
Veraverbeke S., Rogers B.M., Goulden M.L., Jandt R.R., Miller C.E., Wiggins E.B., Randerson J.T.
Lightning as a major driver of recent large fire years in North American boreal forests // Nature Climate Change. – 2017. – Vol. 7. – P. 529–534. DOI: https://doi.org/10.1038/nclimate3329
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