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估算地中海活燃料中的水分:线性回归和随机森林。

Estimation of moisture in live fuels in the mediterranean: Linear regressions and random forests.

机构信息

Forest Fire Laboratory, Department of Forest Engineering, Leonardo da Vinci Building, Campus of Rabanales, University of Córdoba, 14071, Córdoba, Spain.

Forest Fire Laboratory, Department of Forest Engineering, Leonardo da Vinci Building, Campus of Rabanales, University of Córdoba, 14071, Córdoba, Spain.

出版信息

J Environ Manage. 2022 Nov 15;322:116069. doi: 10.1016/j.jenvman.2022.116069. Epub 2022 Aug 27.

Abstract

The live fuel moisture content is an important factor in estimating the risk of forest fires and their rate of spread. However, due to a lack of research, the FMC values in the Mediterranean region of Andalusia, Spain, must be obtained by sample collection. This study is therefore the first to provide tools for estimating the moisture content of the most widespread plant species in Andalusia. First, samples were collected to estimate the moisture content of the plants; these data were collected from May 2007 to the present. Each species has its own range of moistures that depend on the time of year and the physiological state in which they are found. Secondly, an extensive database was obtained for each day of sample collection from the nearest weather station with free access. The statistics are performed at 12 solar hours on the day of sample collection and 24 h before collection, and then at 7 days, 14 days, 1 month, 3 months and 6 months before the day of collection. Finally, this database was statistically analyzed in two ways: Multiple linear regressions and random forest for each species. The predictive capacity of random forest is superior (R > 0.89) to that obtained in linear regression (R < 0.86). The highest root mean square error obtained in the case of the random forest is 0.74479 while in the linear regressions it was 1.29184. Consequently, uncertainty regarding fire behavior in the case of forest fires is reduced.

摘要

可燃物含水率是评估森林火灾风险及其蔓延速度的重要因素。然而,由于缺乏研究,西班牙安达卢西亚地区地中海区域的 FMC 值必须通过样本采集获得。因此,本研究首次提供了估算安达卢西亚最广泛分布的植物物种含水率的工具。首先,采集样本以估算植物的含水率;这些数据是从 2007 年 5 月至今收集的。每种植物都有自己的含水率范围,这取决于它们所处的季节和生理状态。其次,从最近的免费气象站获取了每个样本采集日的广泛数据库。在采集日的 12 个太阳小时以及采集前 24 小时进行统计,然后在采集日之前的 7 天、14 天、1 个月、3 个月和 6 个月进行统计。最后,以两种方式对该数据库进行了统计分析:多元线性回归和随机森林分析。随机森林的预测能力(R>0.89)优于线性回归(R<0.86)。在随机森林的情况下,获得的最大均方根误差为 0.74479,而在线性回归的情况下为 1.29184。因此,减少了森林火灾情况下对火灾行为的不确定性。

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