Openko Ivan, PhD (Economics), Associate Professor of the Department of Geodesy and Cartography, National University of Life and Environmental Sciences of Ukraine, Kyiv, Ukraine

ORCID ID: 0000-0003-2810-0778
e-mail: ivan_openko@ukr.net

Tsvyakh Oleg, PhD (Economics), Lecturer at the Department of Land Cadastre, National University of Life and Environmental Sciences of Ukraine, Kyiv, Ukraine

ORCID ID: 0000-0001-9284-2966
e-mail: 2231738@i.ua

Regression Analysis of Economic Consequences of Forest Fire in Ukraine

Abstract. Introduction. The problem of forest fires, the numerous environmental and economic losses they cause, has in recent years attracted particular attention in the context of the increasing impact of global processes such as global forest decline, numerous biodiversity loss, global climate change and land use change. All this is related to the complexity and ambiguity of the impact of forest fires on forest land, the environment and the safe living conditions of the population in the settlements (united territorial communities) located near the forests.

Purpose. Implementation of economic and mathematical modeling of negative effects of forest fires in Ukraine.

Results. According to the results of the calculations, forest fires are not the main reason for the decrease of the tree cover in Ukraine, although the area of forest land covered by the fires is very significant. For the period 2001 – 2017 the total area of burned land due to forest fires in Ukraine is 88681.0 ha, for example in Austria this figure is 1453.0 ha, Sweden – 17213.0 ha, Finland – 9336.0 ha. According to our analytical calculations, the losses caused by forest fires (for the period 2001 – 2017 – UAH 506,877 million) mainly depend on the area of forest land covered by fires (R = 0,632) and the volume of burned and damaged forest on the stump (R = 0,956). In order to promptly assess the damage caused by forest fires, we proposed a regression model, the adequacy of which is confirmed by the Fisher criterion of 107,659, and the coefficient of determination R² = 0,923.

Conclusions. Given the current dynamics, the cyclicality of the negative effects of forest fires, we predicted the area of forest land covered by forest fires, the amount of burned (damaged) forest on the stump, and damage caused by forest fires by 2030. According to the calculations, we have established that for the period 2019 – 2030 in Ukraine, the total estimated area of forest land covered by fires will be 49,991 thousand hectares, the total volume of burned and damaged forest on the stump – 4,086 million m3, damage caused by forest fires – 906,211 million UAH, or UAH 1.817 billion – considering the consumer price index for 2018.

Keywords: regression analysis, correlation coefficient, forest land, land use, forest fires.

References:

1. Gensiruk, S. A. (1979). Ratsional’noye prirodopol’zovaniye, Moskow: Lesnaia promyshlennost’ [in Russ.].
2. Vorobʹev, H. Y., Mukhamedshyn, K. D. & Devyatkyn L. M. (1984), Lesnoe khozyaystvo myra, Moskow: Lesnaia promyshlennost’ [in Russ.].
3. Zibtsev, S. V. & Borsuk, O. A. (2012). Protection of lisіv vіd pozhezh u svіtі that in ukraine – wiki of the 21st century and prospect of development. Lisove i sadovo-parkove hospodarstvo, vol. 1. Retrieved from http://journals.nubip.edu.ua/index.php/ Lis/article/download/9630/8613 (Accessed 28 August 2019).
4. Voronin, I. V., Senkevich, A. A. & Bugaev, V. A. (1975). Ekonomicheskaya effektivnost’ v lesokhozyaystvennom i lesomeliorativnom proizvodstvakh, Moskow: Lesnaia promyshlennost’ [in Russ.].
5. Against the fire. Encyclopedia of Security (2019). The negative effects of forest fires on the environment. Retrieved from https://protivpozhara.com/tipologija/prirodnye/posledstvija-lesnyx-pozharov [in Russ.].
6. Shevchenko, О. V. & Openko, I. A. (2017). Theoretical prerequisites for rational agricultural land use. Zbalansovane pryrodokorystuvannia, 3, 126-130 [in Ukrainian].
7. Shevchenko, О. V. Openko, I. A. & Tsvyakh, О. М. (2017). Economic preconditions for alternating crops as a way to prevent degradation of the agro-landscape. Zemleustrij, kadastr i monitorynh zemel’, 2, 58-65 [in Ukrainian].
8. Tsvyakh, O. & Openko, І. (2017). Main directions of urban land optimization in Kiev agglomeration”, Baltic Surveying International Scientific Journal, 6 (1), 60-65.
9. Tsvyakh, О. М. & Openko, I. A. (2017). Industrial territories as a spatial basis for optimizing the use of land in the city of Kiev. Zemleustrij, kadastr i monitorynh zemel’, 1, 83-91 [in Ukrainian].
10. Openko, I. A., Shevchenko, О. V. & Tsvyakh, О. М. (2016). Analysis of scientific and methodical approaches to the monetary valuation of land with field-protective forest plantations. Zbalansovane pryrodokorystuvannia, 4, 137-142 [in Ukrainian].
11. Openko, I. A. & Ievsiukov, T. O. (2014). Improving accounting quantity and quality of land for shelter forest plantations in the cadastral registration system. Zbalansovane pryrodokorystuvannia, 3, 106-112 [in Ukrainian].
12. Openko, I. A. & Ievsiukov, T. O. (2014). Lands under field-protective forest plantations: current state, problems, solutions. Zbalansovane pryrodokorystuvannia, 1, 125-131 [in Ukrainian].
13. Openko, I. A. (2013). A comparative analysis of the publication of land cadastral data in foreign countries and Ukraine. Zemleustrij, kadastr i monitorynh zemel’, 3, 80-87 [in Ukrainian].
14. Ievsiukov, T. & Openko, I. (2013). An Inventory Database, Evaluation and Monitoring of Especially Valuable Lands at Regional Level in Ukraine, The 3rd International Geography Symposium “GEOMED 2013”. Kemer, Antalya: Elsivier, Procedia – Social and Behavioral Sciences, Retrieved from http://www.sciencedirect.com/science/article/pii/S1877042814016619
15. State Statistics Service of Ukraine (2018). Main indicators of forestry activity (1990 – 2017). Retrieved from http://www.ukrstat.gov.ua/operativ/operativ2014/sg/lis/lis_u/lgd2016_u.htm [in Ukrainian].
16. Hansen M. C., Potapov P. V., Moore R., Hancher M. et al. (2013). High-Resolution Global Maps of 21st-Century Forest Cover Change. American Association for the Advancement of Science, 342, 6160, 850 – 853. doi: https://doi.org/10.1126/science.1244693
17. Global Forest Watch (2018). Tree Cover Loss in [selected area name]. Retrieved from globalforestwatch.org
18. Eurostat (2018). Forests, forestry and logging. Retrieved from https://ec.europa.eu/eurostat/statistics-explained/index.php/Forests,_forestry_and_logging#Forests_and_other_wooded_land
19. Eurostat (2018). Forestry. Data. Database. Retrieved from https://ec.europa.eu/eurostat/web/forestry/data/database
20. State Statistics Service of Ukraine (2018). Consumer price indices in 1991-2018. Retrieved from http://www.ukrstat.gov.ua/operativ/operativ2006/ct/cn_rik/isc/isc_u/isc_m_u.htm [in Ukrainian].
21. Ievsiukov, T. O. & Openko, I. A. (2013). Monitoring is especially valuable land from the application of remote sensing and GIS technologies. Visnyk Lʹvivsʹkoho derzhavnoho ahrarnoho universytetu: eknomika APK, 20 (2), 231-242 [in Ukrainian].
22. Openko, І. А. (2019). Ecological and economic productivity of land use in Ukraine. Ahrosvit, 13-14, 44-52 [in Ukrainian].
23. Openko, І. А. (2019). Correlation analysis of the impact of the existing public administration system on forest land use in Ukraine. Ekonomika ta derzhava, 7, 55-62 [in Ukrainian].