南京林业大学学报(自然科学版) ›› 2024, Vol. 48 ›› Issue (6): 239-244.doi: 10.12302/j.issn.1000-2006.202303033

• 研究论文 • 上一篇    下一篇

张家口崇礼区主要植物叶片理化性质及燃烧性分析

牟韵洁1(), 高德民1,*(), 龙腾腾2, 郭在军3, 牛海峰3   

  1. 1.南京林业大学信息科学技术学院,人工智能学院,江苏 南京 210037
    2.西南林业大学消防学院,云南 昆明 650224
    3.张家口市林业科学研究院,河北 张家口 075000
  • 收稿日期:2023-03-30 修回日期:2024-01-30 出版日期:2024-11-30 发布日期:2024-12-10
  • 通讯作者: *高德民(dmgao@njfu.edu.cn),副教授。
  • 作者简介:

    牟韵洁(muyunjie@njfu.edu.cn)。

  • 基金资助:
    张家口市崇礼区森林智慧防火项目(2020SLZHFH-2)

Analysis of the physicochemical properties and flammability of the plant leaves of typical plants in Chongli District of Zhangjiakou City, Hebei Province

MU Yunjie1(), GAO Demin1,*(), LONG Tengteng2, GUO Zaijun3, NIU Haifeng3   

  1. 1. College of Information Science and Technology,School of Artificial Intelligence, Nanjing Forestry University, Nanjing 210037, China
    2. College of Fire Fighting, Southwest Forestry University, Kunming 650224, China
    3. Zhangjiakou City Academy of Forestry Sciences, Zhangjiakou 075000, China
  • Received:2023-03-30 Revised:2024-01-30 Online:2024-11-30 Published:2024-12-10

摘要:

【目的】对河北省张家口市崇礼区8类典型植物叶片的理化性质和燃烧性进行分析,为当地森林火险评估和可持续经营提供参考。【方法】基于张家口市崇礼区典型地表植被类型的分布状况以及自然条件,以白桦 (Betula platyphylla)、油松(Pinus tabuliformis)、落叶松(Larix gmelinii)、榛(Corylus heterophylla)、灌杂、草本类、山杏(Prunus sibirica)、樟子松(Pinus sylvestris var. mongolica)8类植物叶片作为研究对象,选取植被覆盖率较高的纯林地段采集植物叶片并测定其理化性质,采用主成分分析法评价8类植物叶片的燃烧性,并利用聚类分析法对8类植物叶片的燃烧等级进行划分。【结果】8类植物叶片的燃烧性大小由强到弱顺序依次为樟子松、白桦、草本类、山杏、榛、油松、落叶松、灌杂。通过主成分分析与聚类分析将8类植物叶片划分为3个等级,分别为:可燃、较易燃、易燃。落叶松、油松、灌杂属于可燃等级,白桦、榛、草本类、山杏属于较易燃等级,樟子松属于易燃等级。【结论】落叶松、油松、灌杂燃烧性最弱,火灾危险性最低;樟子松燃烧性最强,火灾危险性最高,需特别关注和防范。研究结果为张家口市崇礼区森林火灾发生预报、生物防火以及营林用火等方面提供重要依据。

关键词: 植物叶片, 理化性质, 燃烧性, 森林火险, 聚类分析, 主成分分析, 张家口市崇礼区

Abstract:

【Objective】This study analyzed the physicochemical and combustion characteristics of the leaves of eight typical plants in Chongli District of Zhangjiakou City, Hebei Province, the study aimed to provide insights for assessing the risk of local forest fires and their sustainable management.【Method】Based on the distribution patterns of the typical land surface types and natural conditions in Chongli District of Zhangjiakou City, eight plant species, including Betula platyphylla, Pinus tabuliformis, Larix gmelinii, Corylus heterophylla, shrubs, herbs, Prunus sibirica, and P. sylvestris var. mongolica were selected as the research objects. Leaves were collected from pure forest segments with high vegetation coverage, and their physicochemical properties were determined. The combustion characteristics of the leaves of these eight plant species were determined by principal component analysis. The leaves were additionally categorized based on their combustion levels by cluster analysis.【Result】The combustion intensity of the leaves ranged from strongest to weakest in the following order: P. sylvestris var. mongolica, B. platyphylla, herbs, P. sibirica, C. heterophylla, P. tabuliformis, L. gmelinii, and shrubs. The leaves were classified into three categories by principal component analysis and cluster analysis, namely, the highly combustible, moderately combustible, and most easily combustible groups. The highly combustible category included L. gmelinii, P. tabuliformis, and scrub plants. The moderately combustible category comprised B. platyphylla, C. heterophylla, herbs, and P. sibirica, while the most easily combustible category included P. sylvestris var. mongolica.【Conclusion】 L. gmelinii, P. tabuliformis, and shrub plants exhibited the lowest combustion propensity, thus posing as minimal wildfire hazards. Conversely, the combustion propensity of P. sylvestris var. mongolica was highest, indicating an elevated risk of wildfires. Therefore, targeted attention and preventive measures are imperative for controlling wildfires in Chongli District. The findings provide crucial evidence for predicting forest fires in Chongli District of Zhangjiakou City, and advocates the implementation of measures such as biological fire prevention and controlled burning during forestry operation.

Key words: plant leaves, physicochemical properties, combustion characteristics, forest fire risk, cluster analysis, principal component analysis, Chongli District, Zhangjiakou City

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