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Retrieval of forest canopy heights by using large-footprint waveform data assisted by the LiDAR model over hillsides

  • role： First author第一作者
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

    University of Chinese Academy of Sciences, Beijing 100049, China

  • Email：wangyao@radi.ac.cn
  • Introduction：汪垚(1993—　)，男，硕士研究生，研究方向为森林遥感。E-mail：wangyao@radi.ac.cn
Yao WANG12,  
  • role： Corresponding author通信作者
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

  • Email：niwj@radi.ac.cn
  • Introduction：倪文俭(1982—　)，男，研究员，研究方向为森林遥感机理模型发展及基于多源遥感数据的森林植被碳储量及其动态变化监测。E-mail：niwj@radi.ac.cn
Wenjian NI1*,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

Zhiyu ZHANG1,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

    University of Chinese Academy of Sciences, Beijing 100049, China

Jianli LIU12,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

    School of Information Science and Technology, Beijing Normal University, Beijing 100875, China

Haoyang YU13,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

    University of Chinese Academy of Sciences, Beijing 100049, China

Dafeng ZHANG12

résumé

Full waveform data of large-footprint LiDAR are widely used to retrieve global or regional forest canopy heights. However, most studies have focused on forests on relatively flat terrains where the slope is smaller than 20°. Estimating the canopy height of hillside forest stands over mountainous areas with large relief remains a challenge. A model-assisted method is proposed to estimate canopy heights of hillside forest stands by using LiDAR waveforms and overcome the effect of terrains. The adaptability of the method in 0° to 40° is evaluated. We propose a new method and redefine the height index. First, the LiDAR waveform of bare ground is simulated according to given terrain slopes. Second, the LiDAR waveforms of a forest stand and bare ground are aligned according to their signal ending points. Finally, the heights of quarter energy points (i.e., H50 and H75) of the LiDAR waveform of forests are defined relative to the signal ending points, and the heights of quarter energy points (i.e., Hg50 and Hg75) of the LiDAR waveform of bare ground are defined relative to the signal ending points. The relative height indices (i.e., RH50 and RH75) of the forest LiDAR waveform are defined as the difference in the corresponding index of the simulated waveform of forest and bare ground, namely, RH50=H50 − Hg50 and RH75=H75 − Hg75. The newly defined RH50 and RH75 are used to estimate forest canopy heights. The model-assisted method is validated within 0° to 40° terrain slopes and compared with Gaussian decomposition and edge-extent methods. (1) Within the 0° to 20° terrain slopes, the accuracies of estimating forest canopy heights using Gaussian decomposition, edge-extent, and proposed model-assisted methods areR2=0.70, 0.78, and 0.98 and root-mean-square error (RMSE)=2.90 m, 2.48 m, and 0.60 m, respectively. The performance of the proposed method is slightly better than that of the two other methods. (2) Within the 22° to 40° terrain slopes, the accuracies of estimating forest canopy heights using Gaussian decomposition, edge-extent, and proposed model-assisted methods are R2=0.14, 0.28, and 0.97 and RMSE=4.93 m, 4.53 m, and 0.81 m, respectively. The proposed model-assisted method is superior to the two other methods. (3) The estimation accuracy of the model-assisted method within the 0° to 40° terrain slopes is R2=0.97 and RMSE=0.80 m. This model can overcome the effect of the terrain and maintain high accuracy. The method will be further validated using spaceborne LiDAR data in future research. The proposed method can correct the effect of slope over hillsides, and the relative height indices extracted by this method are insensitive to terrain slopes. The proposed method shows a potential for use in the accurate estimation of forest canopy heights over hillsides.

mots-clés

lidar;terrain;waveform broadened;GLAS;forest canopy height

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