Abstract:

As the increasing pressure caused by climatic changes and human activities, the structure and function of terrestrial ecosystems are undergoing dramatic changes. Understanding how ecosystem processes change at large spatial-temporal scales is crucial for dealing with the threats and challenges posed by global climate change. Traditional field survey method can obtain accurate plot-level ecosystem observations, but it is difficult to be used to address large-scale ecosystem patterns and processes because of spatial and temporal discontinuities. Compared to traditional field survey methods, remote sensing has the advantages of real-time acquisition, repeated monitoring and multi spatial-temporal scales, which can compensate for the shortcomings of traditional field observation methods. Remote sensing can be used to identify the type and characteristic of ground objects, and extract key ecosystem parameters, energy flow and material circulation through retrieving the information contained by electromagnetic signals. Remote sensing data have become an indispensable data source in ecological studies, especially at the ecosystem, landscape, regional or global scales. With the emergence of new remote sensing sensors (e.g., light detection and ranging, and solar-induced chlorophyll fluorescence) and near-surface remote sensing platforms (e.g., unmanned aerial vehicle and backpack), remote sensing is entering the three-dimensional era and the observation platform become more diverse. These three-dimensional, multi-source and time-series remote sensing data bring new opportunities to fully understand ecosystem processes across different spatial scales. This paper reviews the advances of the application of remote sensing in terrestrial ecosystem studies. Specifically, this study focuses on the derivation of biological factors from remote sensing data, including vegetation types, structures, functions and biodiversity of terrestrial ecosystems. We also summarize the current status of the remote sensing technology in ecosystem studies and suggest the future opportunities of ecosystem monitoring in China.

Key words: near-surface remote sensing, lidar, unmanned aerial vehicle (UAV), hyperspectral, solar-induced chlorophyll fluorescence