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生态学杂志 ›› 2026, Vol. 45 ›› Issue (4): 1353-1363.doi: 10.13292/j.1000-4890.202604.037

• 研究报告 • 上一篇    下一篇

混交林单木冠层叶绿素含量反演及三维特征

杨文财,王红*,章萌


  

  1. (河海大学地理与遥感学院, 南京 210098)
  • 出版日期:2026-04-10 发布日期:2026-04-14

The inversion and three-dimensional feature of leaf chlorophyll content of individual tree canopies in mixed forests.

YANG Wencai, WANG Hong*, ZHANG Meng   

  1. (College of Geography and Remote Sensing, Hohai University, Nanjing 210098, China).

  • Online:2026-04-10 Published:2026-04-14

摘要: 混交林单木冠层叶绿素含量(leaf chlorophyll content, LCC)的三维空间异质性是评估林木生理状况、光能利用效率与解析种间互作的关键。现有研究往往关注林分尺度,忽略了冠层垂直维度的变异,限制了对混交林生态过程的精细认知。本文以黄河三角洲人工混交林为研究对象,结合样方调查和叶片生化数据,基于无人机激光雷达(UAV-LiDAR)数据对混交林进行单木分割和三维空间划分,利用无人机高光谱(UAV-HSI)数据,耦合PROSPECT-D叶片光学模型与LESS冠层辐射传输模型,实现单木的树种分类和冠层LCC反演。结果表明:(1)联合UAV-LiDAR和UAV-HSI数据可有效划分混交林中的不同树种(OA=91.7%, Kappa=0.887),基于PROSPECT-D-LESS耦合模型,可高精度反演单木冠层LCC(R2=0.809, RMSE=4.973 μg·cm-2);(2)较之刺槐纯林,刺槐白蜡混交林的刺槐LCC提升13.6%(P<0.05),而刺槐榆树混交林的刺槐LCC则下降39.4%(P<0.05);(3)在水平方向上,单木冠层LCC呈现出东、南侧高于西、北侧的分布特征;在垂直方向上,刺槐和白蜡纯林的冠层LCC随高度递增,在混交状态下则呈相反趋势,与榆树混交后,刺槐原有的LCC垂直递增格局同样发生逆转,榆树LCC在纯林和混交中均表现为随高度增加而降低的分布特点。本研究结果可为混交林单木冠层LCC反演及空间分布特征分析提供有效方法,为科学评估混交林的树木生理表现及指导区域生态修复策略提供科学依据。


关键词: 黄河三角洲, 光合生理, 三维空间分布, 辐射传输模型, 无人机激光雷达, 无人机高光谱

Abstract: The threedimensional spatial heterogeneity of leaf chlorophyll content (LCC) at the individual tree canopy is critical for evaluating the physiological status and light use efficiency of trees, and for analyzing interspecific interactions in mixed forests. However, previous studies often focus on the stand scale and overlook the vertical variation of LCC within the canopy, which limits in-depth understanding of ecological processes in mixed forests. To address this gap, we conducted plot surveys and leaf biochemical analyses in artificial mixed forests in the Yellow River Delta. Unmanned aerial vehicle (UAV)-borne LiDAR (UAV-LiDAR) was employed for individual tree segmentation and 3D spatial partitioning, while hyperspectral imagery (UAV-HSI) data were processed using a coupled framework of PROSPECT-D leaf optical model and LESS canopy radiative transfer model to classify tree species and retrieve individual canopy LCC. The results showed that: (1) The fusion of UAV-LiDAR and UAV-HSI data enabled effective discrimination of different tree species in the mixed forests (Overall Accuracy=91.7%, Kappa=0.887), and the coupled PROSPECT-D-LESS model achieved accurate retrieval of individual canopy LCC (R2=0.809, RMSE=4.973 μg·cm-2). (2) Species mixtures were associated with significant shifts in LCC. Compared to monocultures, the LCC of Robinia pseudoacacia increased by 13.6% (P<0.05) in R. pseudoacacia-Fraxinus velutina mixtures but decreased by 39.4% (P<0.05) in R. pseudoacacia-Ulmus pumila mixtures. (3) In the horizontal direction, canopy LCC was generally higher on the eastern and southern sides than on the western and northern sides. Vertically, LCC increased with the height of R. pseudoacacia and F. velutina monocultures. The trend was opposite in mixed stands. Notably, the vertical LCC gradient of R. pseudoacacia inverted when mixed with U. pumila, while U. pumila exhibited a consistent decreasing trend with height in both monoculture and mixed settings. Our results can provide an effective method for the inversion of individual tree canopy LCC and the analysis of its spatial variations in mixed forests, and offer a scientific basis for evaluating tree physiological performance in mixed forests and the guidance of regional ecological restoration strategies.


Key words: Yellow River Delta, photosynthetic physiology, 3D spatial distribution, radiative transfer model, UAV-HSI, UAV-LiDAR