森林火灾信息可靠性的数学估计

IF 0.2 Q4 FORESTRY Lesnoy Zhurnal-Forestry Journal Pub Date : 2023-06-10 DOI:10.37482/0536-1036-2023-3-21-34
R. Kotelnikov
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引用次数: 0

摘要

数字技术的快速发展,特别是处理大量信息的方法,为获得支持管理决策(包括预防森林火灾)的新算法提供了巨大的机会。因此,对森林火险和森林火灾数据准确性的要求大大提高。尽管从太空对地球进行遥感是一种独立于人为因素获取信息的潜在方法,但它仍有若干技术限制,阻碍了全面自动化。因此,对来自森林消防部门的信息进行全面控制是很重要的。此外,长期的火灾风险预测必须考虑回顾性统计数据和周期性天气条件。这就需要创建评估初始数据可靠性的方法。通过对俄罗斯联邦1969 - 2020年发生的森林火灾数量记录的分析发现,在大样本集中,数值的分布接近对数正态分布,这是作者的基本原则。分布右侧的少数偏差间接支持了这样一种假设,即在所提供的信息中,每种情况下的大型森林火灾都被视为较小的、分散的事件。这也符合这样一个事实,即这种信息通常发生在森林火灾情况复杂且有许多燃烧地点的情况下。对一天内扑灭的森林火灾记录的分析发现了一个特征偏差,这间接支持了数据可能被扭曲以改进记录的假设。在这种情况下,偏离模式对应于低可燃性,在燃烧区域多的严重森林火灾情况下完全失去意义。利用统计数据与对数正态分布的对应关系,根据森林火灾档案记录的有效性,形成了区域排序。所建议的方法可以成为林业政策中规划、控制和监督措施的面向风险方法的要素之一。引用本文:Kotelnikov r.v., Martynyuk A.A.。森林火灾信息可靠性的数学估计。俄罗斯林业杂志,2023年第1期。3,第21-34页。(俄国人)。https://doi.org/10.37482/0536-1036-2023-3-21-34
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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 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
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