Abstract
Forest canopy density and height are used as variables in a number of environmental applications, including the estimation of biomass, forest extent and condition, and biodiversity. The airborne Light Detection and Ranging (LiDAR) is very useful to estimate forest canopy parameters according to the generated canopy height models (CHMs). The purpose of this work is to introduce an algorithm to delineate crown parameters, e.g. tree height and crown radii based on the generated rasterized CHMs. And accuracy assessment for the extraction of volumetric parameters of a single tree is also performed via manual measurement using corresponding aerial photo pairs. A LiDAR dataset of a golf course acquired by Leica ALS70-HP is used in this study. Two algorithms, i.e. a traditional one with the subtraction of a digital elevation model (DEM) from a digital surface model (DSM), and a pit-free approach are conducted to generate the CHMs firstly. Then two algorithms, a multilevel morphological active-contour (MMAC) and a variable window filter (VWF), are implemented and used in this study for individual tree delineation. Finally, experimental results of two automatic estimation methods for individual trees can be evaluated with manually measured stand-level parameters, i.e. tree height and crown diameter. The resulting CHM generated by a simple subtraction is full of empty pixels (called "pits") that will give vital impact on subsequent analysis for individual tree delineation. The experimental results indicated that if more individual trees can be extracted, tree crown shape will became more completely in the CHM data after the pit-free process.
Highlights
A Light Detection and Ranging (LiDAR) system comprises multiple subsystems, namely a global positioning system (GPS), inertial measurement unit, and laser scanner
There are some improvement for the Canopy Height Models (CHMs) generation, e.g. searching the highest LiDAR return in each grid cell, replacing each LiDAR return with a small disk, using triangulated irregular network (TIN) interpolation, and a pit-free method developed by Khosravipour et al (2014)
3.2.1 Results for the early study: A TreeTop application developed in a Web-LiDAR forest inventory project was conducted to perform individual tree delineation for the CHMs comparison (Chang et al, 2015)
Summary
A LiDAR system comprises multiple subsystems, namely a global positioning system (GPS), inertial measurement unit, and laser scanner. The large volumes of spatial data collected in a short period using LiDAR systems are typically employed for quantitative analyses and modeling in studies on geology, coastal erosion, and geomorphology. Airborne LiDAR technology can be used to collect multiple laser returns at pulse repetition rates up to 500 KHz. The positional accuracy of the resultant laser pulse return is typical at the decimeter level. Two types of airborne LiDAR systems are currently available; full-waveform (FW) and discrete-echo LiDAR. For each transmitted laser pulse, only three to seven echoes are typically used to record the intensity and three-dimensional coordinates. FW LiDAR systems can record the entire waveform for each transmitted laser pulse. For the single standing-based approach, canopy parameters of individual trees can be extracted from the Canopy Height Models (CHMs). Except for the tree height, there are some parameters such as crown width (CW), crown base height, and crown projected area (CPA) can be estimated in the process (Bortolot & Wynne, 2005; Popescu, 2007; Kwak et al, 2010; Dalponte et al, 2011)
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