红外与毫米波学报2025，Vol.44Issue(2)：211-216,6.DOI:10.11972/j.issn.1001-9014.2025.02.009
基于多光谱机载激光雷达的城市树种分类研究
Urban tree species classification based on multispectral airborne LiDAR
胡佩纶 1陈育伟 2Mohammad Imangholiloo 3Markus Holopainen 3王一程 4Juha Hyyppä2
作者信息
- 1. 芬兰地理空间研究所遥感和摄影测量部,埃斯波02150,芬兰||赫尔辛基大学森林科学系,赫尔辛基00014,芬兰
- 2. 芬兰地理空间研究所遥感和摄影测量部,埃斯波02150,芬兰
- 3. 赫尔辛基大学森林科学系,赫尔辛基00014,芬兰
- 4. 先进激光技术安徽省实验室,安徽 合肥 230037
- 折叠
摘要
Abstract
Urban tree species provide various essential ecosystem services in cities,such as regulating urban tem-peratures,reducing noise,capturing carbon,and mitigating the urban heat island effect.The quality of these ser-vices is influenced by species diversity,tree health,and the distribution and the composition of trees.Traditional-ly,data on urban trees has been collected through field surveys and manual interpretation of remote sensing imag-es.In this study,we evaluated the effectiveness of multispectral airborne laser scanning(ALS)data in classifying 24 common urban roadside tree species in Espoo,Finland.Tree crown structure information,intensity features,and spectral data were used for classification.Eight different machine learning algorithms were tested,with the extra trees(ET)algorithm performing the best,achieving an overall accuracy of 71.7％using multispectral Li-DAR data.This result highlights that integrating structural and spectral information within a single framework can improve the classification accuracy.Future research will focus on identifying the most important features for spe-cies classification and developing algorithms with greater efficiency and accuracy.关键词
多光谱机载激光雷达/机器学习/树种分类Key words
multispectral airborne LiDAR/machine learning/tree species classification分类
林学引用本文复制引用
胡佩纶,陈育伟,Mohammad Imangholiloo,Markus Holopainen,王一程,Juha Hyyppä..基于多光谱机载激光雷达的城市树种分类研究[J].红外与毫米波学报,2025,44(2):211-216,6.
