崔译今, 贾炜玮, 王帆, 等. 基于TLS数据的落叶松–水曲柳混交林单木因子提取及树高模型构建研究[J]. 西南林业大学学报(自然科学), 2024, 44(6): 1–9 . DOI: 10.11929/j.swfu.202401064
引用本文: 崔译今, 贾炜玮, 王帆, 等. 基于TLS数据的落叶松–水曲柳混交林单木因子提取及树高模型构建研究[J]. 西南林业大学学报(自然科学), 2024, 44(6): 1–9 . DOI: 10.11929/j.swfu.202401064
Cui Yijin, Jia Weiwei, Wang Fan, Guo Haotian, Li Dandan. Extraction of Individual Tree Factor and Tree Height Model Construction of Larix olgensisFraxinus mandshurica Mixed Forest Based on TLS Data[J]. Journal of Southwest Forestry University. DOI: 10.11929/j.swfu.202401064
Citation: Cui Yijin, Jia Weiwei, Wang Fan, Guo Haotian, Li Dandan. Extraction of Individual Tree Factor and Tree Height Model Construction of Larix olgensisFraxinus mandshurica Mixed Forest Based on TLS Data[J]. Journal of Southwest Forestry University. DOI: 10.11929/j.swfu.202401064

本文排版定稿已在中国知网网络首发,如需阅读全文请打开知网首页,并搜索该论文题目即可查看。

基于TLS数据的落叶松–水曲柳混交林单木因子提取及树高模型构建研究

Extraction of Individual Tree Factor and Tree Height Model Construction of Larix olgensisFraxinus mandshurica Mixed Forest Based on TLS Data

  • 摘要: 以孟家岗林场1 hm2落叶松水与曲柳混交林样地为研究对象,利用等断面积径级标准木法把林木分为优势木、平均木、被压木3个等级,然后以人工实测值作为参考值,分别分析利用TLS提取2种树种的3种等级木单木因子的精度,最后采用TLS数据提取的单木因子构建树高模型。筛选出两种树种最优基础树高模型,并进一步评价和比较以林木分级为哑变量构建的树高模型。结果表明:针对本研究选取的水落混交林样地,点云数据与实测数据单木匹配结果中,落叶松匹配精度为92.79%,水曲柳为92.25%;2个树种的胸径提取精度达到97%以上,且胸径提取精度优势木 > 平均木 > 被压木,2个树种的树高提取精度达到95%以上,落叶松树高提取精度平均木 > 优势木 > 被压木;水曲柳树高提取精度优势木 > 平均木 > 被压木。使用TLS数据构建的基础树高模型中,拟合落叶松效果最好的是Logistic模型(R2=0.7830、RMSE=1.9516),拟合水曲柳效果最好的是Gompertz模型(R2=0.7248、RMSE=1.9536),因此以Logistic模型、Gompertz模型分别为2个树种基于TLS数据构建的最优基础模型,最后2个树种采用以林木分级为哑变量构建的模型R2分别为0.7907、0.7312。TLS技术对水落混交林样地单木匹配率很高,单木因子提取精度较好,基于TLS数据所构建的以林木分级为哑变量的模型,在预测树木高度和胸径的生长差异方面表现优于基础模型,具有更好的预测精度和适应性,可以为该地区水落混交林的林业经营提供参考。

     

    Abstract: Taking the 1 hm2 mixed stand of Larix olgensis-Fraxinus mandshurica in Mengjiagang Forest Farm as the research object, the forest trees were divided into three grades: dominant trees, average trees, and pressed trees, using the equal cross-sectional area class standard wood method. Then, with the measured values as the reference value, the accuracy of extracting the individual tree factors of the three grades of the two species by TLS was analyzed respectively, and finally the tree height model was constructed using the individual tree factors extracted from TLS data. The optimal basic tree height models of the two species were screened out, and the tree height models built with the dummy variable of tree classification were further evaluated and compared. The results showed that: for the mixed stand of standing water and falling leaves selected in this paper, the matching accuracy of the individual tree between the point cloud data and the measured data was 92.79% for Larix olgensis and 92.25% for Fraxinus mandshurica. The extraction accuracy of the diameter at breast height of the two species reached more than 97%, and the extraction accuracy of the diameter at breast height of the dominant trees was higher than that of the average trees and the pressed trees. The extraction accuracy of the tree height of the two species reached more than 95%, and the extraction accuracy of the average trees of Larix olgensis was higher than that of the dominant trees and the pressed trees. The extraction accuracy of the dominant trees of Fraxinus mandshurica was higher than that of the average trees and the pressed trees. In the basic tree height models built using TLS data, the Logistic model (R2=0.7830, RMSE=1.9516) fitted Larix olgensis best, and the Gompertz model (R2=0.7248, RMSE=1.9536) fitted Fraxinus mandshurica best. Therefore, the Logistic model and Gompertz model were the optimal basic models built based on TLS data for the two tree species respectively. Finally, the models built with tree classification as dummy variable for the two tree species had R2 values of 0.7907 and 0.7312, respectively. TLS technology has a high individual tree matching rate for mixed stand and a good accuracy in extracting individual tree factors. The model built based on TLS data with tree classification as dummy variable performs better than the basic model in predicting the growth differences of tree height and diameter at breast height, with better prediction accuracy and adaptability, which can provide a theoretical basis for the forestry management of mixed stand in this region.

     

/

返回文章
返回