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

Mi Xiangcheng; Yu Jianping; Wang Ningning; Jia Wen; Ren Haibao; Chen Lei; Pang Yong; Ma Keping

doi:10.12171/j.1000-1522.20220383

Journal of Beijing Forestry University > 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

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

1.
Zhejiang Qianjiangyuan Forest Biodiversity National Observation and Research Station, State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
2.
Qianjiangyuan National Park Administration Bureau, Kaihua 324300, Zhejiang, China
3.
Institute of Forest Resource Information Technique, Chinese Academy of Forestry, Beijing 100091, China
4.
Key Laboratory of Forestry Remote Sensing and Information System, National Forestry andGrassland Administration, Beijing 100091, China

More Information

Received Date: September 17, 2022
Revised Date: October 11, 2022
Available Online: October 13, 2022
Published Date: October 24, 2022

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Abstract

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.
- aboveground biomass,
- remote sensing,
- LiDAR,
- canopy structure index,
- evergreen broadleaved forest,
- Qianjiangyuan National Park

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References

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