Mathematical Estimation of Information Reliability Regarding Forest Fires
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...
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| Format: | Article |
| Language: | English |
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Northern Arctic Federal University
2023-06-01
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| Series: | Лесной журнал |
| Subjects: | |
| Online Access: | https://journals.narfu.ru/index.php/fj/article/view/1476 |
| _version_ | 1797687114889953280 |
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| author | Roman V. Kotelnikov Аlexsander A. Martynyuk |
| author_facet | Roman V. Kotelnikov Аlexsander A. Martynyuk |
| author_sort | Roman V. Kotelnikov |
| collection | DOAJ |
| description | 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 |
| first_indexed | 2024-03-12T01:13:39Z |
| format | Article |
| id | doaj.art-5c07b7dac98d4e9b867a81ba42142649 |
| institution | Directory Open Access Journal |
| issn | 0536-1036 |
| language | English |
| last_indexed | 2024-03-12T01:13:39Z |
| publishDate | 2023-06-01 |
| publisher | Northern Arctic Federal University |
| record_format | Article |
| series | Лесной журнал |
| spelling | doaj.art-5c07b7dac98d4e9b867a81ba421426492023-09-13T20:24:18ZengNorthern Arctic Federal UniversityЛесной журнал0536-10362023-06-013213410.37482/0536-1036-2023-3-21-341679Mathematical Estimation of Information Reliability Regarding Forest FiresRoman V. Kotelnikov0https://orcid.org/0000-0002-9984-5913Аlexsander A. Martynyuk1https://orcid.org/0000-0001-7592-2614All-Russian Research Institute for Silviculture and Mechanization of ForestryAll-Russian Research Institute for Silviculture and Mechanization of ForestryThe 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/10.37482/0536-1036-2023-3-21-34https://journals.narfu.ru/index.php/fj/article/view/1476forest firesforest fire conditionsburning of wooded areaforest fire suppression efficiencystatistical analysislognormal distributioninformation technologiesrisk-oriented approach |
| spellingShingle | Roman V. Kotelnikov Аlexsander A. Martynyuk Mathematical Estimation of Information Reliability Regarding Forest Fires Лесной журнал forest fires forest fire conditions burning of wooded area forest fire suppression efficiency statistical analysis lognormal distribution information technologies risk-oriented approach |
| title | Mathematical Estimation of Information Reliability Regarding Forest Fires |
| title_full | Mathematical Estimation of Information Reliability Regarding Forest Fires |
| title_fullStr | Mathematical Estimation of Information Reliability Regarding Forest Fires |
| title_full_unstemmed | Mathematical Estimation of Information Reliability Regarding Forest Fires |
| title_short | Mathematical Estimation of Information Reliability Regarding Forest Fires |
| title_sort | mathematical estimation of information reliability regarding forest fires |
| topic | forest fires forest fire conditions burning of wooded area forest fire suppression efficiency statistical analysis lognormal distribution information technologies risk-oriented approach |
| url | https://journals.narfu.ru/index.php/fj/article/view/1476 |
| work_keys_str_mv | AT romanvkotelnikov mathematicalestimationofinformationreliabilityregardingforestfires AT alexsanderamartynyuk mathematicalestimationofinformationreliabilityregardingforestfires |