摘要
森林垂直结构参数指的是森林冠层孔隙率、郁闭度、叶面积指数(leaf area index, LAI)和聚集指数(clumping index, CI)等关键结构参数在垂直方向的分布特征.获取森林垂直结构参数是深入研究森林碳氮水循环和遥感辐射传输过程的关键环节.本文聚焦LAI和CI,探讨森林垂直结构参数地面实测与遥感反演研究进展.地面测量的常用仪器有LAI-2200、数字半球相机和光合有效辐射(photosynthetically active radiation, PAR)测量仪等,不同高度的测量可以通过破坏采样、塔基测量和移动升降机等手段来进行.地面测量方法虽然较为准确,但通常比较费时费力,不利于获取大范围信息.遥感方法主要通过经验的植被指数估算或物理模型反演来进行.激光雷达(LiDAR)作为一种主动式遥感方法,具有反演垂直结构参数的独特优势.虽然遥感方法能够进行大范围连续观测,但目前还没有成熟的全球遥感产品能满足实际需求,少数区域产品也缺乏充分的质量检验.森林垂直结构参数已经在陆面过程模型、冠层辐射传输模型和森林经营管理中展现了巨大的应用价值.未来的研究应进一步探索新的地面测量和遥感反演方法,分析参数的垂直分布特征,同时开展垂直结构参数的验证研究,为森林垂直结构参数在模型机理研究和森林管理中提供科学依据.
Forest vertical stratification directly affects the transfer of solar radiation and water evapotranspiration in the canopy.Consequently, leaf photosynthesis varies in different parts of the canopy, affecting the growth of trees and the succession process of the plant community. The vertical distribution of forest structural parameters, such as the leaf area index(LAI) and clumping index(CI), is critical not only for understanding of the forest carbon, nitrogen, and water cycles and remote sensing radiative transfer processes, but also for forest monitoring and management practices.Forest vertical LAI and CI can be obtained through field measurement and remote sensing inversion methods. For field measurements, LAI-2200, digital hemispherical photography, and photosynthetically active radiation sensors are frequently used instruments. Vertical structural measurements are usually carried out through destructive sampling, tower-base measurement, and mobile elevators. In general, field measurements are more accurate;however, they are time-consuming and laborious, making them unsuitable for large-scale applications.Remote sensing technology uses the passive optical method, the light detection and ranging(LiDAR) technology, and synthetic aperture radar(SAR) methods to estimate forest vertical LAI and CI. The classical passive optical method is based on either the empirical vegetation index estimation method or physical model inversion method. The vegetation index method establishes an empirical relationship between vegetation structural parameters and vegetation indices. Subsequently, the relationship is used to estimate the structural parameters for different layers. The physical model inversion method is based on a physical radiative transfer model. In general, the application of both passive optical and SAR methods in forest vertical parameter retrieval is limited.As an active remote sensing technology, the LiDAR technology has shown its unique advantages in the inversion of vertical structural parameters. Based on the platform used, LiDAR can be classified into three categories: Terrestrial laser scanning(TLS),airborne laser scanning(ALS), and spaceborne laser scanning. The basic rationale of the LiDAR technology is based on the BeerLambert Law, which estimates canopy LAI and CI from the canopy gap fraction;both empirical statistical and physical inversion methods are used during the process. The use of LiDAR to estimate LAI and CI is gaining popularity worldwide, but most of the research is based on TLS and ALS. The development of new space-based LiDAR technologies, such as the Global Ecosystem Dynamics Investigation on the International Space Station, will greatly advance the acquisition of forest vertical structural information on a global scale. However, the relatively complex operation and data processing requirements have limited its widespread application.The vertical distribution of forest LAI can be represented by the normal, Weibull, beta, chi-square, and Johnson’s S-B distributions. The CI values usually decrease with the increase in canopy height because the upper part of the canopy usually has larger gaps. However, mature global vertical LAI and CI products that can meet the application requirements are currently unavailable. Due to the limits of ground measurements, forest vertical LAI and CI retrieved from remote sensing lack sufficient ground validation. In field measurements, the LAI values of trees, shrubs, and herbs should be acquired simultaneously in order to validate the remote sensing LAI. The development of wireless sensor networks and unmanned aerial vehicles provides convenient and effective methods to obtain a large amount of vertical structural information useful for validation purposes.Forest vertical LAI and CI have been applied in land surface and radiative transfer models and forest management studies. In future research, new field measurement and remote sensing inversion methods should be explored. Various LiDAR data sources can be used to generate high-quality vertical structural products, and these vertical products should be fully validated to better meet the requirements proposed by the research and management communities.
作者
方红亮
Hongliang Fang(State Key L aboratory of Resources and Environmental Information System,Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101,China;College of Resources and Environment,University of Chinese Academy of Sciences,Beijing 100049,China)
出处
《科学通报》
EI
CAS
CSCD
北大核心
2021年第24期3141-3153,共13页
Chinese Science Bulletin
基金
国家重点研发计划(2016YFA0600201)资助。
关键词
垂直结构参数
叶面积指数
聚集指数
地面测量
遥感反演
激光雷达
vertical structural parameters
leaf area index(LAI)
clumping index
field measurement
remote sensing inversion
LiDAR
作者简介
方红亮,E-mail:fanghl@lreis.ac.cn。
