Individual tree crown delineation using localized contour tree method and airborne LiDAR data in coniferous forests

2016 ◽  
Vol 52 ◽  
pp. 82-94 ◽  
Author(s):  
Bin Wu ◽  
Bailang Yu ◽  
Qiusheng Wu ◽  
Yan Huang ◽  
Zuoqi Chen ◽  
...  
Keyword(s):  
Airborne Lidar ◽  
Coniferous Forests ◽  
Lidar Data ◽  
Tree Crown ◽  
Individual Tree ◽  
Crown Delineation ◽  
Tree Crown Delineation ◽  
Airborne Lidar Data ◽  
Contour Tree ◽  
Tree Method

scholarly journals Individual Tree Crown Delineation Using Multispectral LiDAR Data

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5421 ◽  
Author(s):  
Faizaan Naveed ◽  
Baoxin Hu ◽  
Jianguo Wang ◽  
G. Brent Hall
Keyword(s):  
Lidar Data ◽  
Segmentation Method ◽  
Tree Crown ◽  
Individual Tree ◽  
Tree Crowns ◽  
Multi Scale ◽  
Crown Delineation ◽  
Tree Crown Delineation ◽  
The City ◽  
532 Nm

In this study, multispectral Light Detection and Ranging (LiDAR) data were utilized to improve delineation of individual tree crowns (ITC) as an important step in individual tree analysis. A framework to integrate spectral and height information for ITC delineation was proposed, and the multi-scale algorithm for treetop detection developed in one of our previous studies was improved. In addition, an advanced region-based segmentation method that used detected treetops as seeds was proposed for segmentation of individual crowns based on their spectral, contextual, and height information. The proposed methods were validated with data acquired using Teledyne Optech’s Titan LiDAR sensor. The sensor was operated at three wavelengths (1550 nm, 1064 nm, and 532 nm) within a study area located in the city of Toronto, ON, Canada. The proposed method achieved 80% accuracy, compared with manual delineation of crowns, considering both matched and partially matched crowns, which was 12% higher than that obtained by the earlier marker-controlled watershed (MCW) segmentation technique. Furthermore, the results showed that the integration of spectral and height information improved ITC delineation using either the proposed framework or MCW segmentation, compared with using either spectral or height information individually.

Parameterization of Aerodynamic Roughness Length and Zero Plane Displacement Over Tropical Region Using Airborne LiDAR Data

2015 ◽  
Vol 73 (5) ◽  
Author(s):  
Muhammad Zulkarnain Abdul Rahman ◽  
Faiznor Farok ◽  
Abd Wahid Rasib ◽  
Wan Hazli Wan Kadir
Keyword(s):  
Airborne Lidar ◽  
Frontal Area ◽  
Tropical Region ◽  
Surface Model ◽  
Lidar Data ◽  
Individual Tree ◽  
Crown Delineation ◽  
Aerodynamic Roughness ◽  
Plane Displacement ◽  
Airborne Lidar Data

Airborne LiDAR data has been one of the reliable data for individual tree properties estimation. High density airborne LiDAR data has been used previously for detailed reconstruction of tree geometry. The aim of this study is to estimate aerodynamic roughness over specific height (Zo/H) and zero plane displacement (do) over forest area using airborne LiDAR data. The results of this study will be very useful as a main guideline for related applications to understand the role of carbon and hydrological cycles, land cover and land use change, habitat fragmentation, and biogeographical modeling. The airborne LiDAR data is first classified into ground and non-ground classes. The ground points are interpolated for digital terrain model (DTM) generation and the non-ground points are used to generate digital surface model (DSM). Canopy height model (CHM) is then generated by subtracting DTM from DSM. Individual tree delineation is carried out on the CHM and individual tree height is used together with allometric equation in estimating height to crown base (HCB) and diameter at breast height (DBH). Tree crown delineation is carried out using the Inverse Watershed segmentation approach. Crown diameter, HBC and DBH are used to estimate individual tree frontal area and the total frontal area over a specific ground surface is further calculated by subtracting the intersected crowns and trunks from the total area of tree crowns and trunks. The considered ground area i.e. plants area determined the final spatial resolution of the Zo/H and do. Both parameters are calculated for different wind directions that were assumed to be originated from North/South and East/West. The results show that the estimated Zo/H and do have similar pattern and values with previous studies over vegetated area. 

scholarly journals Individual Tree Position Extraction and Structural Parameter Retrieval Based on Airborne LiDAR Data: Performance Evaluation and Comparison of Four Algorithms

2020 ◽  
Vol 12 (3) ◽  
pp. 571 ◽  
Author(s):  
Chen ◽  
Xiang ◽  
Moriya
Keyword(s):  
Template Matching ◽  
Local Maximum ◽  
Airborne Lidar ◽  
Forest Monitoring ◽  
Lidar Data ◽  
Individual Tree ◽  
Matching Algorithm ◽  
Crown Width ◽  
Individual Trees ◽  
Airborne Lidar Data

Information for individual trees (e.g., position, treetop, height, crown width, and crown edge) is beneficial for forest monitoring and management. Light Detection and Ranging (LiDAR) data have been widely used to retrieve these individual tree parameters from different algorithms, with varying successes. In this study, we used an iterative Triangulated Irregular Network (TIN) algorithm to separate ground and canopy points in airborne LiDAR data, and generated Digital Elevation Models (DEM) by Inverse Distance Weighted (IDW) interpolation, thin spline interpolation, and trend surface interpolation, as well as by using the Kriging algorithm. The height of the point cloud was assigned to a Digital Surface Model (DSM), and a Canopy Height Model (CHM) was acquired. Then, four algorithms (point-cloud-based local maximum algorithm, CHM-based local maximum algorithm, watershed algorithm, and template-matching algorithm) were comparatively used to extract the structural parameters of individual trees. The results indicated that the two local maximum algorithms can effectively detect the treetop; the watershed algorithm can accurately extract individual tree height and determine the tree crown edge; and the template-matching algorithm works well to extract accurate crown width. This study provides a reference for the selection of algorithms in individual tree parameter inversion based on airborne LiDAR data and is of great significance for LiDAR-based forest monitoring and management.

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