森林是地球生态系统的重要组成部分,森林冠层生物物理参数表征冠层结构特征,森林结构多样性支持着森林生态系统的稳定和生物多样性,因此准确估算冠层结构参数对监测森林生态系统的变化至关重要.激光雷达(Light Detection and Ranging,LiDAR)作为一种快速发展的主动遥感技术,已成功应用于冠层参数的反演.本文总结了激光雷达在植被遥感中的应用,重点介绍了在冠层生物物理参数提取中的应用,对比分析了不同平台(地基、机载和星载)激光雷达提取参数的方法.结果表明:①地基激光雷达(Terrestrial laser scanner,TLS)、机载激光雷达(Aerial laser scanner,ALS)和星载激光雷达(Spaceborne laser scanner,SLS)3 种激光雷达在生物物理参数的反演中各有其适用范围,其中,TLS适用于局部区域的精细结构研究,ALS适用于中等面积森林监测,SLS适用于全球尺度变化监测.②在叶面积指数(leaf area index,LAI)反演中,TLS提供了样地内LAI的精确分布,ALS提供多尺度LAI估计,SLS可以反演全球尺度的LAI.而在消光系数和聚集度指数(clumping index,CI)的反演中,TLS反演精度高、效率高,适用于精细结构研究;而ALS数据可反演大范围CI及消光系数.③激光雷达为森林结构多样性研究提供了强有力的工具,通过精确估算表征冠层结构特征的各类参数,有助于更好开展森林生物多样性的动态监测.鉴于此,对激光雷达未来发展方向提出展望,建议进一步融合TLS、ALS、SLS数据,优化反演算法,提高大范围和复杂地形条件下的参数反演精度,为生态学研究和森林管理提供更准确的数据支持.
Advances in Forest Canopy Parameter Retrieval Using LiDAR Technology
Forests are an important component of Earth's ecosystem,the biophysical parameters of the forest canopy reflect the characteristics of its structure.The diversity of forest structures plays a crucial role in supporting ecosystem stability and biodiversity.Therefore,accurately estimating canopy structure parameters is vital for monitoring changes in forest ecosystems.As a rapidly advancing active remote sensing technology,Light Detection and Ranging(LiDAR)has been successfully applied in the retrieval of canopy parameters.This paper summarizes the application of LiDAR in vegetation remote sensing,with emphasis on its application in canopy parameter extraction,and compares and analyzes the methodologies for parameters retrieval from different LiDAR platforms(ground-based,airborne and spaceborne).The following conclusions are drawn:(1)Three types of LiDAR have distinct applications for the inversion of biophysical parameters.Terrestrial LiDAR(TLS)is suitable for fine-scale structure research in localized regions;Airborne LiDAR(ALS)is ideal for monitoring medium-size forest;and Spaceborne LiDAR(SLS)is appropriate for monitoring global scale changes.(2)In the inversion of the Leaf Area Index(LAI),TLS provides accurate distribution of LAI within a sample site;ALS offers multi-scale LAI estimations;and SLS can invert global scale LAI.For the inversion of extinction coefficient and Clumping Index(CI),TLS inversion is highly precise and efficient,making it suitable for fine-scale structure studies.A large range of CI and extinction coefficient can be retrieved using ALS data.(3)LiDAR is a powerful tool for studying forest structural diversity.By accurately estimating various parameters that characterize canopy structural characteristics,LIDAR facilitates dynamic monitoring of forest biodiversity.Looking ahead,future studies should aim to integrate airborne,spaceborne and terrestrial LiDAR data,optimize inversion algorithms,and improve accuracy of parameter inversion under large-scale and complex terrain conditions.These efforts will provide more reliable data support for ecological research and forest management.
retrieval of biophysical parameters of forest canopiesspaceborne LiDARairborne LiDARterrestrial LiDAR
万方数据
维普
