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    米湘成, 余建平, 王宁宁, 荚文, 任海保, 陈磊, 庞勇, 马克平. 基于激光雷达技术估算钱江源国家公园森林的地上生物量[J]. 北京林业大学学报, 2022, 44(10): 77-84. DOI: 10.12171/j.1000-1522.20220383
    引用本文: 米湘成, 余建平, 王宁宁, 荚文, 任海保, 陈磊, 庞勇, 马克平. 基于激光雷达技术估算钱江源国家公园森林的地上生物量[J]. 北京林业大学学报, 2022, 44(10): 77-84. DOI: 10.12171/j.1000-1522.20220383
    Mi Xiangcheng, Yu Jianping, Wang Ningning, Jia Wen, Ren Haibao, Chen Lei, Pang Yong, Ma Keping. Utilizing LiDAR technology to estimate forest aboveground biomass in Qianjiangyuan National Park, Jiangxi Province of eastern China[J]. Journal of Beijing Forestry University, 2022, 44(10): 77-84. DOI: 10.12171/j.1000-1522.20220383
    Citation: Mi Xiangcheng, Yu Jianping, Wang Ningning, Jia Wen, Ren Haibao, Chen Lei, Pang Yong, Ma Keping. Utilizing LiDAR technology to estimate forest aboveground biomass in Qianjiangyuan National Park, Jiangxi Province of eastern China[J]. Journal of Beijing Forestry University, 2022, 44(10): 77-84. DOI: 10.12171/j.1000-1522.20220383

    基于激光雷达技术估算钱江源国家公园森林的地上生物量

    Utilizing LiDAR technology to estimate forest aboveground biomass in Qianjiangyuan National Park, Jiangxi Province of eastern China

    • 摘要:
        目的  采用激光雷达结合地面调查的方法,拟合并预测钱江源国家公园森林的地上生物量,为国家公园森林生态系统保护和动物生境质量评估提供基础数据。
        方法  采用冠层结构指数量化亚热带常绿阔叶林的冠层高度和垂直复杂度,并结合地面调查数据和地形数据,用模型拟合和预测钱江源国家公园的地上生物量。
        结果  冠层结构指数中,与地上生物量的相关程度从大到小依次为冠层平均高度、冠层垂直复杂度、冠层最大高度。钱江源国家公园生物量分布主要在27.24 ~ 210.31 Mg/hm2(0.05 ~ 0.95分位数),平均为111.21 Mg/hm2,总的生物量约为2.57 × 106 Mg。
        结论  结合冠层指数和地形变量能较好地模拟和预测钱江源国家公园地上生物量。钱江源国家公园有大面积低海拔集中分布的常绿阔叶林,冠层平均高度和冠层垂直复杂度都比较大,地上生物量高;同时,也有大面积人工林和次生林,这些人工林和次生林主要分布在国家公园成立后才开始保护的两个片区,冠层平均高度和冠层垂直复杂度小,地上生物量较低,有待进一步恢复。

       

      Abstract:
        Objective  Utilizing technologies of airborne lidar together with ground survey, we modelled and predicted aboveground biomass of subtropical forests in Qianjiangyuan National Park, Jiangxi Province of eastern China to provide basis for assessing conservation effectiveness and quality of animal habitats in national parks.
        Method  We used canopy structural indices to quantify canopy structural variation and maximal height of subtropical forests, then modelled forest aboveground biomass with canopy structural indices and topographic variables.
        Result  Mean canopy height, vertical complexity and maximal height were closely correlated with aboveground biomass. Aboveground biomass was mainly between 27.24−210.31 Mg/ha (quantile 0.05−0.95), mean value was 111.21 Mg/ha, and total aboveground biomass was2.57 × 106 Mg.
        Conclusion  The forest aboveground biomass is well modelled and predicted using canopy structural indices and topographic variables. Large area of zonal evergreen broadleaved forests is distributed in the national park with complex canopy structure and high aboveground biomass, while large area plantation and secondary forests are also distributed in two new parts of the national park with simple canopy structure and low aboveground biomass.

       

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