高光谱遥感在植物多样性研究中的应用进展与趋势

Progress and trends of application of hyperspectral remote sensing in plant diversity research

人类活动、极端气候、物种入侵等事件导致植物的生物多样性丧失加剧,生物多样性保护迫切需要快速准确地收集陆地植物多样性信息。高光谱遥感的出现,为大空间尺度上的植物多样性研究提供了技术基础,为群落和景观水平的生物多样性相关理论的验证提供了契机。本文简要回顾了近年来高光谱遥感技术的发展及其在植物多样性研究中的应用。重点介绍了两类高光谱遥感反演多样性的手段,即直接反演和间接反演。直接反演手段以光谱变异假说为理论基础,从光谱曲线特征入手直接建立光谱信息与植物多样性的关系;间接反演手段则通过植被指数将光谱信息关联植物多样性,或通过定量反演功能性状计算功能多样性指标,进而实现植物多样性的间接估测。论文进一步结合实例,论述了高光谱遥感技术在大尺度生物多样性相关研究中的应用,如物种入侵监测、物种分布及多样性格局制图、生物多样性与生态系统功能关系研究。最后分析了高光谱遥感技术在生态研究应用中的局限性。随着多源遥感技术的发展日渐成熟,高光谱遥感技术与地面通量监测、激光雷达、计算机可视化等其他技术的协同应用可能是在生物多样性研究领域中一个新的发展方向。

Plant diversity is closely related to ecosystem productivity,stability,and resource use efficiency.The rate of plant biodiversity loss due to human activities,extreme climate,and species invasions is accelerating annually,and an urgent need is recognized for rapid and accurate collection of information of terrestrial plant diversity for biodiversity conservation.Remote sensing techniques are important methods of earth observation from space.In recent years,image data from remote sensing have been developing toward refinement and comprehensiveness,and high-quality data covering more ground information have been gradually applied.The emergence of hyperspectral remote sensing technology enables sensors to collect continuous spectral curves of ground targets in fine spectral resolution,which consequently provides massive information of ground objects and realizes the quantitative inversion of ground object parameters.Hyperspectral remote sensing technology offers a technical basis for the large-scale observation of plant diversity and functional traits.It further brings opportunities for the verification of theories of community assembly with the continuous variation in spatial scales.In this study,we review the development of hyperspectral remote sensing technology and its application in detecting plant diversity and functional traits.Two types of inversion approaches for quantifying biodiversity through hyperspectral remote sensing,namely,direct inversion and indirect inversion,are introduced.The direct inversion approach takes the spectral variation hypothesis(SVH)as its theoretical basis,which posits that biodiversity is linked to the heterogeneity of spectral image.The SVH-based approaches,also known as“spectral diversity metrics,”are to directly establish the relationship between spectral information and plant diversity.Common spectral diversity metrics include the coefficient of variation of spectral bands,the convex hull volume in spectral space,the spectral angle mapper,the divergence of spectral information,and the convex hull area.Numerous studies have proven that these spectral diversity metrics can be used to effectively track the variation in biodiversity indicators,such as species richness,Shannon index,and Rao’s Q index.The indirect inversion approach correlates spectral information with plant diversity via quantitative remote sensing.Plant functional traits can be retrieved from hyperspectral image data through empirical and physically-based models with convincing accuracy.With the quantitative retrieved traits from image data,functional diversity indices,which can be closely linked to ecosystem functioning,such as FRic(functional richness),FDiv(functional divergence),and FEve(functional evenness),can be characterized and spatially mapped.Studies also confirmed that the indirect approach can be employed to assess taxonomic and even phylogenetic diversity through the quantification of vegetation indices.Combined with existing application examples,we then discuss the technical advantages of hyperspectral remote sensing technology in the studies on species invasion,species mapping,biodiversity spatial patterns,and the large-scale biodiversity and ecosystem functioning relationship.At the end of this review,limitations of the application of hyperspectral remote sensing technology in ecological studies are analyzed.With the development of multisource remote sensing technology,hyperspectral remote sensing coordinated with other technological means(e.g.,ground flux monitoring,laser radar technique,and computer visualization)will be applied more extensively in biodiversity-relevant studies.