Mathematical Estimation of Information Reliability Regarding Forest Fires

Authors

DOI:

https://doi.org/10.37482/0536-1036-2023-3-21-34

Keywords:

forest fires, forest fire conditions, burning of wooded area, forest fire suppression efficiency, statistical analysis, lognormal distribution, information technologies, risk-oriented approach

Abstract

The rapid development of digital technologies, especially methods for processing a large amount of information, offers vast opportunities for obtaining new algorithms for supporting management decisions, including the prevention of forest fires. Therefore, the requirements for data accuracy on fire hazards in forests and forest fires considerably increase. Even though the remote sensing of the Earth from space is a potential method for acquiring information independent of the human factor, it still has several technical limitations that hinder total automation. Therefore, it is important to provide а comprehensive control over the information coming from the forest fire departments. Besides, the long-term fire risk prognoses must consider retrospective statistics and cyclical weather conditions. This requires the creation of methods for evaluating the reliability of the initial data. An analysis of the records on the number of forest fires that happened in the Russian Federation from 1969 to 2020 revealed that the distribution of the values in a large sampling set is close to lognormal, which is the author’s fundamental principle. The few deviations on the right side of the distribution indirectly support the hypothesis that, in the provided information, the large forest fires in each case were presented as smaller, fragmented events. This is also consistent with the fact that such information usually occurs when the forest fire situation is complex and has many burning locations. An analysis of the records on the forest fires extinguished within one day identified a characteristic deviation, which indirectly supports the assumption that the data was probably distorted to improve recording. In such a situation, the deviation from the pattern corresponds to low combustibility and completely loses its meaning in the conditions of a severe forest fire situation with many burning areas. The authors have formed a ranking of the regions according to the validity of the archival records on the forest fires using the correspondence of the statistical data to the lognormal distribution. The proposed method can become one of the elements of a risk-oriented approach for planning control and supervisory measures in forestry policy.
For citation: Kotelnikov R.V., Martynyuk A.A. Mathematical Estimation of Information Reliability Regarding Forest Fires. Lesnoy Zhurnal = Russian Forestry Journal, 2023, no. 3, pp. 21–34. (In Russ.). https://doi.org/10.37482/0536-1036-2023-3-21-34

Downloads

Download data is not yet available.

Author Biographies

Roman V. Kotelnikov, All-Russian Research Institute for Silviculture and Mechanization of Forestry

Candidate of Engineering; ResearcherID: B-2453-2018

Аlexsander A. Martynyuk, All-Russian Research Institute for Silviculture and Mechanization of Forestry

Doctor of Agriculture, Prof.; ResearcherID: AAB-7622-2020

References

Барталев С.А., Егоров В.А., Ефремов В.Ю., Лупян Е.А., Стыценко Ф.В., Флитман Е.В. Оценка площади пожаров на основе комплексирования спутниковых данных различного пространственного разрешения MODIS и Landsat-TM/ETM+ // Современные проблемы дистанционного зондирования Земли из космоса. 2012. Т. 9, № 2. C. 9–26. Bartalev S.A., Egorov V.A., Efremov V.Yu., Lupyan E.A., Stytsenko F.V., Flitman E.V. Integrated Burnt Area Assessment Based on Combine Use of Multi-Resolution Modis and Landsat-TM/ETM+ Satellite Data. Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa = Current Problems in Remote Sensing of the Earth from Space, 2012, no. 2, pp. 9–26. (In Russ.).

Ковалев Н.А., Лупян Е.А., Балашов И.В., Барталев С.А., Бурцев М.А., Ершов Д.В., Кривошеев Н.П., Мазуров А.А. ИСДМ-Рослесхоз: 15 лет эксплуатации и развития // Современные проблемы дистанционного зондирования Земли из космоса. 2020. Т. 17, № 7. C. 283–291. Kovalev N.A., Lupyan E.A., Balashov I.V., Bartalev S.A., Burtsev M.A., Ershov D.V., Krivosheev N.P., Mazurov A.A. ISDM-Rosleskhoz: 15 Years of Operation and Evolution. Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa = Current Problems in Remote Sensing of the Earth from Space, 2020, no. 7, pp. 283–291. (In Russ.). https://doi.org/10.21046/2070-7401-2020-17-7-283-291

Коморовский В.С. Модели организации и управления при борьбе с лесными пожарами: моногр. М.: Инфра-М, 2012. 120 с. Komorovskiy V.S. Models of Organization and Management in Fighting Forest Fires: Monograph. Moscow, Infra-M Publ., 2012. 120 p. (In Russ.).

Котельников Р.В., Коршунов Н.А., Гиряев Н.М. Задачи принятия решений в области охраны лесов от пожаров. Основные приоритеты развития информационного обеспечения // Сиб. лесн. журн. 2017. № 5. C. 18–24. Kotelnikov R.V., Korshunov N.A., Giryaev N.A. Objectives of Decision Making in Protecting Forests from Fires. Main Priorities on Development of Informational Support. Sibirskiy lesnoy zhurnal = Siberian Journal Forest Science, 2017, no. 5, pp. 18–24. (In Russ.). https://doi.org/10.15372/SJFS20170502

Котельников Р.В., Мартынюк А.А. Использование закона Бенфорда для оценки достоверности сведений о лесных пожарах // Лесотехн. журн. 2018. Т. 8, № 1(29). C. 28–34. Kotelnikov R.V., Martynyuk A.A. Application of the Benford Law in Assessment of Wildfire Data Accuracy.Lesotekhnicheskiy zhurnal= Forestry Engineering Journal, 2018, vol. 8, no. 1 (29), pp. 28–34. (In Russ.). https://doi.org/10.12737/article_5ab0dfbb946859.24647128

Лемешко Б.Ю., Лемешко С.Б., Постовалов С.Н., Чимитова Е.В. Статистический анализ данных, моделирование и исследование вероятностных закономерностей. Компьютерный подход: моногр. Новосибирск: НГТУ, 2011. 888 с. Lemeshko B.Yu., Lemeshko S.B., Postovalov S.N., Chimitova E.V. Statistical Data Analysis, Simulation and Study of Probability Regularities. Computer Approach: Monograph. Novosibirsk, NSTU Publ., 2011. 888 p. (In Russ.).

Лупян Е.А., Барталев С.А., Балашов И.В., Егоров В.А., Ершов Д.В., Кобец Д.А., Сенько К.С., Стыценко Ф.В., Сычугов И.Г. Спутниковый мониторинг лесных пожаров в 21 веке на территории Российской Федерации (цифры и факты по данным детектирования активного горения) // Современные проблемы дистанционного зондирования Земли из космоса. 2017. Т. 14, № 6. C. 158–175. Loupian E.A., Bartalev S.A., Balashov I.V., Egorov V.A., Ershov D.V., Kobets D.A., Senko K.S., Stytsenko F.V., Sychugov I.G. Satellite Monitoring of Forest Fires in the 21st Century on the Territory of the Russian Federation (Facts and Figures Based on Active Fire Detection). Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa = Current Problems in Remote Sensing of the Earth from Space, 2017, vol. 14, no. 6, pp. 158–175. (In Russ.). https://doi.org/10.21046/2070-7401-2017-14-6-158-175

Пономарев Е.И., Швецов Е.Г. Спутниковое детектирование лесных пожаров и геоинформационные методы калибровки результатов // Исследование Земли из космоса. 2015. № 1. С. 84–91. Ponomarev E.I., Shvetsov E.G. Satellite Detection of Forest Fires and Geoinformation Methods for Calibrating Results. Issledovaniye Zemli iz kosmosa = Earth Observation and Remote Sensing, 2015, no. 1, pp. 84–91. (In Russ.). https://doi.org/10.7868/S0205961415010054

Giglio L., Randerson J.T., Werf G.R. Analysis of Daily, Monthly, and Annual Burned Area Using the Fourth-Generation Global Fire Emissions Database (GFED4): Analysis of Burned Area. Journal of Geophysical Research, Biogeosciences series, 2013, vol. 118, no. 1, pp. 317–328. https://doi.org/10.1002/jgrg.20042

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, no. 7537, рр. 1–11. https://doi.org/10.1038/ncomms8537

Katz R.W., Brush G.S., Parlange M.B. Statistics of Extremes: Modeling Ecological Disturbances. Ecology, 2005, vol. 86, no. 5, pp. 1124–1134. https://doi.org/10.1890/04-0606

Kotelnikov R.V., Lupyan E.A., Bartalev S.A., Ershov D.V. Space Monitoring of Forest Fires: History of the Creation and Development of ISDM-Rosleskhoz. Contemporary Problems of Ecology, 2020, vol. 13, no. 7, pp. 795–802. https://doi.org/10.1134/S1995425520070045

Langmann B., Duncan B., Textor C., Trentmann J., Werf G. Vegetation Fire Emissions and Their Impact on Air Pollution and Climate. Atmospheric Environment, 2009, vol. 43, no. 1, pp. 107–116. https://doi.org/10.1016/j.atmosenv.2008.09.047

Limpert E., Stahel W.A., Abbt M. Log-Normal Distributions Across the Sciences: Keys and Clues. Bioscience, 2001, vol. 51, no. 5, p. 341. https://doi.org/10.1641/0006-3568(2001)051[0341:lndats]2.0.co;2

Loboda T.V., Csiszar I.A. Estimating Burned Area from AVHRR and MODIS: Validation Results and Sources of Error. Contemporary Earth Remote Sensing from Space, 2005, vol. 2, pp. 415–421.

Pereira Jr. A.C., Oliveira S.L.J., Pereira J.M.C., Turkman M.A.A. Modelling Fire Frequency in a Cerrado Savanna Protected Area. PloS One, 2014, vol. 9, no. 7, art. no. e102380. https://doi.org/10.1371/journal.pone.0102380

Royston J.P. An Extension of Shapiro and Wilk’s W. Test for Normality to Large Samples. Journal of the Royal Statistical Society, Series C: Applied Statistics, 1982, vol. 31, no. 2, pp. 115–124. https://doi.org/10.2307/2347973

Taylor S.W., Woolford D.G., Dean C.B., Martell D.L. Wildfire Prediction to Inform Fire Management: Statistical Science Challenges. Journal of the Institute of Mathematical Statistics, 2013, vol. 28, no. 4, pp. 586–615. https://doi.org/10.1214/13-sts451

Torres-Rojo J.M. Index for the Estimation of the Occurrence of Forest Fires in Large Areas. Revista Chapingo, Serie: Ciencias Forestales Y Del Ambiente, 2020, vol. 26, no. 3, pp. 433–449. https://doi.org/10.5154/r.rchscfa.2019.11.082

Werf G.R., Dempewolf J., Trigg S.N., Randerson J.T., Kasibhatla P.S., Giglio L., Murdiyarso D., Peters W., Morton D.C., Collatz G.J., Dolman A.J., DeFries R.S. Climate Regulation of Fire Emissions and Deforestation in Equatorial Asia. PNAS, 2008, vol. 105, no. 51, pp. 20350–20355. https://doi.org/10.1073/pnas.0803375105

Published

2023-06-15

How to Cite

Kotelnikov Р., and Martynyuk А. “Mathematical Estimation of Information Reliability Regarding Forest Fires”. Lesnoy Zhurnal (Forestry Journal), no. 3, June 2023, pp. 21-34, doi:10.37482/0536-1036-2023-3-21-34.