Assessing the impact of broadleaf tree structure on airborne full-waveform small-footprint LiDAR signals through simulation

被引:10
|
作者
Romanczyk, Paul [1 ]
van Aardt, Jan [1 ]
Cawse-Nicholson, Kerry [1 ]
Kelbe, David [1 ]
McGlinchy, Joe [2 ]
Krause, Keith [3 ]
机构
[1] Rochester Inst Technol, Chester F Carlson Ctr Imaging Sci, Rochester, NY 14623 USA
[2] ESRI, Redlands, CA 92373 USA
[3] Natl Ecol Observ Network, Boulder, CO 80301 USA
基金
美国国家科学基金会;
关键词
FOREST STAND CHARACTERISTICS; IMAGING SPECTROMETER; CANOPY STRUCTURE; LASER ALTIMETER; VEGETATION; PARAMETERS; BIOMASS; HEIGHT; VALIDATION; RETRIEVAL;
D O I
10.5589/m13-015
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Full-waveform small-footprint Light Detection and Ranging (LiDAR) is still in the early stages of development for forest structure assessment, in part due to the complex interaction between a laser pulse and the forest structure, which is not yet fully understood. In recent years, simulation studies (which claim absolute ground truth) have sought to tackle this problem. The challenge remains to determine the limit of structural fidelity, in terms of tree structural components, that is required for waveform-based simulation studies. Understanding of such interactions could lead to improved biophysical modeling from LiDAR waveform signals. We present a simulation study that evaluates the impact of tree structural components on received waveform signals across different outgoing pulse widths and scanning angles. The simulation was performed on a small red maple (Acer rubrum) and red oak (Quercus rubra) stand. It was concluded the back-scattered waveform is dominated by the leaves, while the trunks, twigs, and leaf stems had a minimal impact on the signal. Scan angle (08, 108, and 208) and outgoing pulse width (4 ns, 8 ns, and 16 ns) do not have as statistically significant (95% confidence) impact on mean waveform comparison statistics. This result has implications on the level of complexity required for future simulations and for waveform LiDAR based structural algorithm development.
引用
收藏
页码:S60 / S72
页数:13
相关论文
共 45 条
  • [31] Characterizing Canopy Structure Variability in Amazonian Secondary Successions with Full-Waveform Airborne LiDAR
    Jacon, Aline D.
    Galvao, Lenio Soares
    Martins-Neto, Rorai Pereira
    Crespo-Peremarch, Pablo
    Aragao, Luiz E. O. C.
    Ometto, Jean P.
    Anderson, Liana O.
    Vedovato, Laura Barbosa
    Silva, Celso H. L.
    Lopes, Aline Pontes
    Peripato, Vinicius
    Assis, Mauro
    Pereira, Francisca R. S.
    Haddad, Isadora
    de Almeida, Catherine Torres
    Cassol, Henrique L. G.
    Dalagnol, Ricardo
    REMOTE SENSING, 2024, 16 (12)
  • [32] Estimation of mean tree height using small-footprint airborne LiDAR without a digital terrain model
    Yamamoto, Kazukiyo
    Takahashi, Tomoaki
    Miyachi, Yousuke
    Kondo, Naoto
    Morita, Shinichi
    Nakao, Motohiko
    Shibayama, Takashi
    Takaichi, Yoshiyuki
    Tsuzuku, Masashi
    Murate, Naoaki
    JOURNAL OF FOREST RESEARCH, 2011, 16 (06) : 425 - 431
  • [33] Estimation of coniferous forest aboveground biomass with aggregated airborne small-footprint LiDAR full-waveforms
    Qin, Haiming
    Wang, Cheng
    Xi, Xiaohuan
    Tian, Jianlin
    Zhou, Guoqing
    OPTICS EXPRESS, 2017, 25 (16): : A851 - A869
  • [34] Effects of voxel size, scan angle and crown structure on the accuracy of tree species classification using airborne full-waveform LiDAR
    Cao, Lin
    Shen, Xin
    Dai, Jinsong
    Ruan, Honghua
    She, Guanghui
    2016 4RTH INTERNATIONAL WORKSHOP ON EARTH OBSERVATION AND REMOTE SENSING APPLICATIONS (EORSA), 2016,
  • [35] Decomposition of small-footprint full waveform LiDAR data based on generalized Gaussian model and grouping LM optimization
    Ma, Hongchao
    Zhou, Weiwei
    Zhang, Liang
    Wang, Suyuan
    MEASUREMENT SCIENCE AND TECHNOLOGY, 2017, 28 (04)
  • [37] Assessing the 3-D Structure of Bamboo Forests Using an Advanced Pseudo-Vertical Waveform Approach Based on Airborne Full-Waveform LiDAR Data
    Zhang, Zhengnan
    Cao, Lin
    Liu, Hao
    Fu, Xiaoyao
    Shen, Xin
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2021, 59 (12): : 10647 - 10670
  • [38] Tree species classification and estimation of stem volume and DBH based on single tree extraction by exploiting airborne full-waveform LiDAR data
    Yao, Wei
    Krzystek, Peter
    Heurich, Marco
    REMOTE SENSING OF ENVIRONMENT, 2012, 123 : 368 - 380
  • [39] A Method for Quantifying Understory Leaf Area Index in a Temperate Forest through Combining Small Footprint Full-Waveform and Point Cloud LiDAR Data
    Song, Jinling
    Zhu, Xiao
    Qi, Jianbo
    Pang, Yong
    Yang, Lei
    Yu, Lihong
    REMOTE SENSING, 2021, 13 (15)
  • [40] A Multi-Threshold Segmentation for Tree-Level Parameter Extraction in a Deciduous Forest Using Small-Footprint Airborne LiDAR Data
    Wang, Xiao-Hu
    Zhang, Yi-Zhuo
    Xu, Miao-Miao
    REMOTE SENSING, 2019, 11 (18)