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An integrated UAV-borne lidar system for 3D habitat mapping in three forest ecosystems across China

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ABSTRACT In recent decades, global biodiversity has gradually diminished due to the increasing pressure from anthropogenic activities and climatic change. Accurate estimations of spatially continuous three-dimensional (3D) vegetation structures and… Click to show full abstract

ABSTRACT In recent decades, global biodiversity has gradually diminished due to the increasing pressure from anthropogenic activities and climatic change. Accurate estimations of spatially continuous three-dimensional (3D) vegetation structures and terrain information are prerequisites for biodiversity studies, which are usually unavailable in current ecosystem-wide studies. Although the airborne lidar technique has been successfully used for mapping 3D vegetation structures at landscape and regional scales, the relatively high cost of airborne lidar flight mission has significantly limited its applications. The unmanned aerial vehicle (UAV) provides an alternative platform for lidar data acquisition, which can largely lower the cost and provide denser lidar points compared with airborne lidar. In this study, we implemented a low-cost UAV-borne lidar system, including both a hardware system and a software system, to collect and process lidar data for biodiversity studies. The implemented UAV-borne lidar system was tested in three different ecosystems across China, including a needleleaf–broadleaf mixed forest, an evergreen broadleaf forest, and a mangrove forest. Various 3D vegetation structure parameters (e.g. canopy height model, canopy cover, leaf area index, aboveground biomass) were derived from the UAV-borne lidar data. The results show that the implemented UAV-borne lidar system can generate very high resolution 3D terrain and vegetation information. The developed UAV-based hardware and software systems provide a turn-key solution for the use of UAV-borne lidar data on biodiversity studies.

Keywords: lidar system; borne lidar; lidar; uav borne

Journal Title: International Journal of Remote Sensing
Year Published: 2017

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