Remote sensing of terrestrial plant biodiversity

Abstract Biodiversity is essential to healthy ecosystem function, influencing productivity and resilience to disturbance. Biodiversity loss endangers essential ecosystem services and risks unacceptable environmental consequences. Global biodiversity observations are needed to provide a better understanding of the distribution of biodiversity, to better identify high priority areas for conservation and to help maintain essential ecosystem goods and services. Traditional in situ biodiversity monitoring is limited in time and space and is usually a costly and time-consuming enterprise. Remote sensing can provide data over a large area in a consistent, objective manner and has been used to detect plant biodiversity in a range of ecosystems, typically based on relating spectral properties to the distribution of habitat, species or functional groups. Recent years have witnessed the emergence of methods using imaging spectroscopy to assess biodiversity via plant traits or spectral information content. However, questions regarding the complex drivers of plant optical properties and the scale dependence of spectral diversity – biodiversity relationship confound diversity monitoring using remote sensing and must first be better understood before these methods can be operationally applied. To address some of these topics, we (1) review the history of remote sensing approaches in biodiversity estimation, summarizing the pros and cons of different methods, (2) illustrate successes and major gaps of remote sensing of biodiversity, and (3) identify promising future directions. We focus on emerging methods using spectral diversity (optical diversity) as a proxy for terrestrial plant diversity that offer to revolutionize the study of diversity in its different dimensions (phylogenetic, taxonomic, and functional diversity) from remote sensing. We also discuss remaining knowledge gaps and ways spectral diversity might be effectively integrated into a global biodiversity monitoring system, bridging a gap between ecology and remote sensing.