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Preliminary study on dry and wet season changes in biomass on Chinese fir forest land on the basis of UAV LiDAR

  • role： First author第一作者
  • Affiliation：

    Key Laboratory for Humid Subtropical Eco-geographical Processes of the Ministry of Education, School of Geographical Sciences, Fujian Normal University, Fuzhou 350007, China

    Institute of Geography, Fujian Normal University, Fuzhou 350007, China

    Fujian Sanming Forest Ecosystem National Observation and Research Station, Sanming 365002, China

  • Email：727016023@qq.com
  • Introduction：熊景峰，研究方向为植被遥感。E-mail：727016023@qq.com
XIONG Jingfeng,  
  • role： Corresponding author通信作者
  • Affiliation：

    Key Laboratory for Humid Subtropical Eco-geographical Processes of the Ministry of Education, School of Geographical Sciences, Fujian Normal University, Fuzhou 350007, China

    Institute of Geography, Fujian Normal University, Fuzhou 350007, China

    Fujian Sanming Forest Ecosystem National Observation and Research Station, Sanming 365002, China

  • Email：zeng.hd@foxmail.com
  • Introduction：曾宏达，研究方向为植被遥感与碳计量。E-mail：zeng.hd@foxmail.com
ZENG Hongda*,  
  • Affiliation：

    Key Laboratory for Humid Subtropical Eco-geographical Processes of the Ministry of Education, School of Geographical Sciences, Fujian Normal University, Fuzhou 350007, China

    Institute of Geography, Fujian Normal University, Fuzhou 350007, China

    Fujian Sanming Forest Ecosystem National Observation and Research Station, Sanming 365002, China

XIE Jinsheng,  
  • Affiliation：

    Key Laboratory for Humid Subtropical Eco-geographical Processes of the Ministry of Education, School of Geographical Sciences, Fujian Normal University, Fuzhou 350007, China

    Institute of Geography, Fujian Normal University, Fuzhou 350007, China

    Fujian Sanming Forest Ecosystem National Observation and Research Station, Sanming 365002, China

LI Xiaojie,  
  • Affiliation：

    Key Laboratory for Humid Subtropical Eco-geographical Processes of the Ministry of Education, School of Geographical Sciences, Fujian Normal University, Fuzhou 350007, China

    Institute of Geography, Fujian Normal University, Fuzhou 350007, China

    Fujian Sanming Forest Ecosystem National Observation and Research Station, Sanming 365002, China

CHEN Jingming

résumé

With global warming, the pattern of extreme precipitation has changed considerably. How China’s plantations, which are widely distributed and at a rapid growth stage, will respond to climate change; the prediction of their carbon sink functions; and the corresponding management decisions urgently need methods to monitor growth quickly and accurately. In this study, a 17-year-old middle-aged Chinese fir plantation was monitored three times semiannually from February 2019 to February 2020 by using UAV LiDAR. Three methods to estimate the individual tree Aboveground Biomass (AGB) via UAV LiDAR parameters were compared using ground survey data. The three methods were height and crown diameter regression, diameter at breast height-tree height regression, and diameter at breast height-tree height-crown diameter regression (D-HCD). Then, the seasonal growth changes in tree height, diameter at breast height, and AGB were estimated in a six-month interval. Results showed that D-HCD was the optimal method for estimating the individual AGB of Chinese fir (R2=0.77, root mean square error [RMSE]=15.99 kg). In the D-HCD method, the tree height and crown diameter extracted by UAV LiDAR were used to estimate the diameter at breast height (DBH), and AGB was calculated by substituting DBH and tree height into an allometric equation. The annual and even seasonal growth changes in the Chinese fir plantation in the fast-growing period could be accurately monitored by UAV LiDAR. The average total accuracy of individual tree identification in 16 plots reached 0.927, the estimated RMSE of tree height was only 0.13 m, the R2 between the estimated and measured annual individual AGB changes (ΔAGB) was 0.64, RMSE was equal to 1.87 kg, and the relative error (rRMSE) was 29.74%. When the individual trees were upscaled to plots, the relative error of ΔAGB estimation was reduced, and rRMSE decreased to 17.10%. During the study period, the average daily temperature in spring and summer was 7 ℃ higher than that in autumn and winter, and the amount of rainfall was more than three times that in autumn and winter. The seasonal distribution of rainfall in this year was seriously uneven, and the growth of Chinese fir showed obvious differences in dry and wet seasons. The average increments in individual tree height in wet and dry seasons were 0.50 and 0.13 m, respectively, and the biomass increments were 5.12 and 1.37 kg, respectively. Individual ΔAGB increased with DBH class during annual and seasonal growth; the larger the individual was, the more advantageous the growth was. In particular, the growth of dominant trees in the dry season was much better than that of other diameter classes, indicating a strong drought tolerance. However, the growth of individuals whose DBH was much smaller than the average level almost stopped.

mots-clés

remote sensing;Chinese fir;aboveground biomass;UAV-LiDAR;Multitemporal;Dry and wet season

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