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Resolving leaf area index of individual trees based on multi-return terrestrial laser point cloud data

  • role： First author第一作者
  • Affiliation：

    College of Forestry, Nanjing Forestry University, Nanjing 210037, China

    Advanced Analysis and Testing Center, Nanjing Forestry University, Nanjing 210037, China

  • Email：757758952@qq.com
  • Introduction：黄星旻，1995年生，研究方向为森林资源动态监测。E-mail：757758952@qq.com
Xingming HUANG12,  
  • role： Corresponding author通信作者
  • Affiliation：

    College of Forestry, Nanjing Forestry University, Nanjing 210037, China

    Advanced Analysis and Testing Center, Nanjing Forestry University, Nanjing 210037, China

  • Email：sunyuan1123@126.com
  • Introduction：孙圆，1976年生，副教授，研究方向为森林资源动态监测。E-mail：sunyuan1123@126.com
Yuan SUN12*,  
  • Affiliation：

    College of Forestry, Nanjing Forestry University, Nanjing 210037, China

    Advanced Analysis and Testing Center, Nanjing Forestry University, Nanjing 210037, China

Huiqian LIU12,  
  • Affiliation：

    College of Information Science and Technology, Nanjing Forestry University, Nanjing 210037, China

Fangzhou LIU3

Resümee

This study aimed to extract the Leaf Area Index (LAI) of individual trees through multi-return terrestrial laser point cloud data, including single target, first-return waveform, intermediate, and last target data. The species was soapberry planted as street trees. An algorithm based on Beer–Lambert law was developed to divide return waveform, and the LAIs of individual trees with different projection resolutions of 0.01, 0.02, and 0.03 m were obtained. Two-dimensional digital hemispherical image data and LAI-2200 were used to extract the LAIs of corresponding single trees for accuracy comparison. Result shows that the resolutions and multiple return waveforms have significant influence on LAI. The results with 0.02 m and 0.03 m resolutions are similar to those obtained with LAI2200, and the difference is insignificant. However, the single target waveform point cloud data are used for the LAI solution and can be mutually verified with the results of the 2D image data of LAI2200. The LAI value of single target waveform point cloud was calculated with Beer– Lambert at 0.02 m resolution, and the intercept measured by LAI2200 data was subjected to a linear regression with an intercept of 0 and slope of 0.827, which is close to 1. Therefore, for the multi-return waveform ground laser scanning data, the single target waveform point cloud data with a projection resolution of 0.02 m can be used to obtain accurate LAI when using an extinction coefficient method. The algorithm for calculating the LAI based on multi-return waveform ground-based laser data in this study expands the application field of TLS and provides an important technical reference for the accurate extraction of the growth of standing trees and accurate tree modeling.

Schlüsselwort

multi-return waveform;terrestrial laser scan;leaf area index;difference analysis

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