Estimating Leaf Area Density of Individual Trees Using the Point Cloud Segmentation of Terrestrial LiDAR Data and a Voxel-Based Model

The leaf area density (LAD) within a tree canopy is very important for the understanding and modeling of photosynthetic studies of the tree. Terrestrial light detection and ranging (LiDAR) has been applied to obtain the three-dimensional structural properties of vegetation and estimate the LAD. However, there is concern about the efficiency of available approaches. Thus, the objective of this study was to develop an effective means for the LAD estimation of the canopy of individual magnolia trees using high-resolution terrestrial LiDAR data. The normal difference method based on the differences in the structures of the leaf and non-leaf components of trees was proposed and used to segment leaf point clouds. The vertical LAD profiles were estimated using the voxel-based canopy profiling (VCP) model. The influence of voxel size on the LAD estimation was analyzed. The leaf point cloud’s extraction accuracy for two magnolia trees was 86.53% and 84.63%, respectively. Compared with the ground measured leaf area index (LAI), the retrieved accuracy was 99.9% and 90.7%, respectively. The LAD (as well as LAI) was highly sensitive to the voxel size. The spatial resolution of point clouds should be the appropriate estimator for the voxel size in the VCP model.

[1]  Chang Yao,et al.  Automated retinal blood vessels segmentation based on simplified PCNN and fast 2D-Otsu algorithm , 2009 .

[2]  Guang Zheng,et al.  Computational-Geometry-Based Retrieval of Effective Leaf Area Index Using Terrestrial Laser Scanning , 2012, IEEE Transactions on Geoscience and Remote Sensing.

[3]  F. Baret,et al.  Review of methods for in situ leaf area index (LAI) determination: Part II. Estimation of LAI, errors and sampling , 2004 .

[4]  Martin Beland,et al.  A model for deriving voxel-level tree leaf area density estimates from ground-based LiDAR , 2014, Environ. Model. Softw..

[5]  Philip J. Radtke,et al.  Laser point-quadrat sampling for estimating foliage-height profiles in broad-leaved forests , 2001 .

[6]  Muhammad H. Alsuwaiyel,et al.  Algorithms - Design Techniques and Analysis , 1999, Lecture Notes Series on Computing.

[7]  Zhao Jing.  Review of forest vertical structure parameter inversion based on remote sensing technology , 2013 .

[8]  Hans Pretzsch,et al.  Using terrestrial laser scanner for estimating leaf areas of individual trees in a conifer forest , 2010, Trees.

[9]  K. Omasa,et al.  Factors contributing to accuracy in the estimation of the woody canopy leaf area density profile using 3D portable lidar imaging. , 2007, Journal of experimental botany.

[10]  David J. Harding,et al.  A portable LIDAR system for rapid determination of forest canopy structure , 2004 .

[11]  Mingquan Wu,et al.  Generating pseudo large footprint waveforms from small footprint full-waveform airborne LiDAR data for the layered retrieval of LAI in orchards. , 2016, Optics express.

[12]  Bo Du,et al.  A Three-Step Approach for TLS Point Cloud Classification , 2016, IEEE Transactions on Geoscience and Remote Sensing.

[13]  Q. Guo,et al.  A geometric method for wood-leaf separation using terrestrial and simulated Lidar data , 2015 .

[14]  Richard A. Fournier,et al.  Estimation of 3D vegetation density with Terrestrial Laser Scanning data using voxels. A sensitivity analysis of influencing parameters , 2017 .

[15]  Guang Zheng,et al.  Improved Salient Feature-Based Approach for Automatically Separating Photosynthetic and Nonphotosynthetic Components Within Terrestrial Lidar Point Cloud Data of Forest Canopies , 2016, IEEE Transactions on Geoscience and Remote Sensing.

[16]  Semyung Wang,et al.  A new segmentation method for point cloud data , 2002 .

[17]  M. Monsi,et al.  On the factor light in plant communities and its importance for matter production. 1953. , 2004, Annals of botany.

[18]  Kenji Omasa,et al.  Voxel-Based 3-D Modeling of Individual Trees for Estimating Leaf Area Density Using High-Resolution Portable Scanning Lidar , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[19]  Ronald L. Graham,et al.  An Efficient Algorithm for Determining the Convex Hull of a Finite Planar Set , 1972, Inf. Process. Lett..

[20]  Pol Coppin,et al.  3D modeling of light interception in heterogeneous forest canopies using ground-based LiDAR data , 2011, International Journal of Applied Earth Observation and Geoinformation.

[21]  Maggi Kelly,et al.  A New Method for Segmenting Individual Trees from the Lidar Point Cloud , 2012 .

[22]  Yifang Ban,et al.  Toward an Optimal Algorithm for LiDAR Waveform Decomposition , 2012, IEEE Geoscience and Remote Sensing Letters.

[23]  Jw Wilson.  Estimation of foliage denseness and foliage angle by inclined point quadrats , 1963 .

[24]  Zheng Niu,et al.  Synergistic application of geometric and radiometric features of LiDAR data for urban land cover mapping. , 2015, Optics express.

[25]  D. Baldocchi,et al.  On seeing the wood from the leaves and the role of voxel size in determining leaf area distribution of forests with terrestrial LiDAR , 2014 .

[26]  Shihua Li,et al.  Tree point clouds registration using an improved ICP algorithm based on kd-tree , 2016, 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).

[27]  Kenji Omasa,et al.  Estimation and Error Analysis of Woody Canopy Leaf Area Density Profiles Using 3-D Airborne and Ground-Based Scanning Lidar Remote-Sensing Techniques , 2010, IEEE Transactions on Geoscience and Remote Sensing.

[28]  Clive S. Fraser,et al.  Automatic Segmentation of Raw LIDAR Data for Extraction of Building Roofs , 2014, Remote. Sens..

[29]  Kenji Omasa,et al.  3-D voxel-based solid modeling of a broad-leaved tree for accurate volume estimation using portable scanning lidar , 2013 .

[30]  Babak Taati,et al.  Difference of Normals as a Multi-scale Operator in Unorganized Point Clouds , 2012, 2012 Second International Conference on 3D Imaging, Modeling, Processing, Visualization & Transmission.

[31]  M. Verstraete,et al.  Estimating leaf area distribution in savanna trees from terrestrial LiDAR measurements , 2011 .

[32]  H. Mizunaga,et al.  A three-dimensional light transfer model based on the vertical point-quadrant method and Monte-Carlo simulation in a Fagus crenata forest canopy on Mount Naeba in Japan , 2011 .

[33]  Toshihiko Hara,et al.  Ground-Based Estimation of Leaf Area Index and Vertical Distribution of Leaf Area Density in a Betula ermanii Forest , 2009 .