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林业资源管理 ›› 2022›› Issue (5): 53-59.doi: 10.13466/j.cnki.lyzygl.2022.05.007

• 科学研究 • 上一篇    下一篇

森林可燃物大样地抽样调查方法研究

杨雪清1(), 孙志超1, 王立生2(), 柴政2, 邱议文2, 蒋春颖1   

  1. 1.国家林业和草原局林草调查规划院,北京 100714
    2.新疆生产建设兵团林业和草原工作总站,乌鲁木齐 830011
  • 收稿日期:2022-09-06 修回日期:2022-10-21 出版日期:2022-10-28 发布日期:2022-12-23
  • 通讯作者: 王立生
  • 作者简介:杨雪清(1967-),女,山西永济人,教授级高工,主要从事森林资源管理、防灾减灾、3S技术应用等方面的研究工作。Email:xqyangok@126.com

Study of Sampling Survey Method for Forest Fuels Based on Large Plots

YANG Xueqing1(), SUN Zhichao1, WANG Lisheng2(), CHAI Zheng2, QIU Yiwen2, JIANG Chunying1   

  1. 1. Academy of Forestry Inventory and Planning,National Forestry and Grassland Administration,Beijing 100714,China
    2. Forestry and Grassland Station of Xinjiang Production and Construction Corps,Urumqi 830011,China
  • Received:2022-09-06 Revised:2022-10-21 Online:2022-10-28 Published:2022-12-23
  • Contact: WANG Lisheng

摘要:

为满足森林可燃物遥感监测的需要,采用分层抽样方法设计了一套能够在典型区域主要森林类型中布设可燃物大样地的抽样方案。对每个大样地在林分型图斑区划的基础上,采用角规绕测、样方调查的方法对大样地内各层(乔木层、灌木层、草本层、枯落物层、腐殖质层)可燃物载量及其林分、地形等因素进行全面调查。探讨了采用统计学方法依据可燃物载量与林分因子、地形等因素建立可燃物载量遥感估算模型的可行性。研究表明,可燃物载量遥感估算可为区域尺度森林可燃物载量精准调查和动态监测提供有利的技术支撑。

关键词: 可燃物, 大样地, 抽样调查, 方案设计, 遥感反演

Abstract:

In order to meet the needs of remote sensing monitoring of forest fuel loads,this study designed a sampling plan by using the stratified sampling method to set up large plots of forest fuels in the major forest types in typical areas.For each large plot,on the basis of the zoning of the forest stand type,the method of measuring around the angle and the quadratic survey was used to measure the fuel load of the various layers(e.g.,tree-,shrub-,herb-,litter-,and humus-layer)in the large sample plot.A comprehensive investigation was carried out on the plant load and other factors such as stand and topography characteristics.Finally,the feasibility of using statistical methods to establish a remote sensing prediction model of fuels load based on factors such as combustibles load and vegetation index was discussed.The research results can provide favorable technical support for the accurate investigation and dynamic monitoring of the forest fuel loads at the regional scale.

Key words: forest fuel, large plot, sampling survey, program design, remote sensing retrieval

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