Abstract:

During the past decade, unmanned aerial vehicle (UAV) based remote sensing has been increasingly used in the fields of vegetation inventory, natural resource management, and biodiversity conservation, due to its low cost and high flexibility. In this study, we present a reference for the selection of UAV platforms and remote sensing sensors, by introducing a UAV classification system and summarizing applicability in biodiversity monitoring using remote sensing techniques. For each UAV platform category, we also introduce the characteristics and capabilities of different remote sensing sensors that can be supported. Moreover, through the combination of a case study which collected high-fidelity UAV-based remotely sensed data, we discuss current research progress using UAV-borne remote sensing data to derive direct and indirect biodiversity parameters. Finally, we discuss the current limitations of UAV-based remote sensing platforms for biodiversity monitoring, such as the existing gap between hardware and software, the high cost of certain components (e.g. the initial measurement unit), incomplete laws and regulations, and the disconnect with traditional biodiversity monitoring methods. In summary, we believe that UAV-based remote sensing platforms can greatly help to fill the gaps between terrestrial measurements and aerial/spaceborne measurements, and can increase the accuracy and reliability of upscaling point-based terrestrial measurements to the regional scale. There is a need to launch more projects that address building a UAV-based biodiversity monitoring network, and therefore improve our capability to analyze and forecast biodiversity changes in hotspots.

Key words: UAV, remote sensing, sensors, LiDAR, multi-source data