Biodiv Sci ›› 2019, Vol. 27 ›› Issue (9): 1021-1031.  DOI: 10.17520/biods.2019166

• Review • Previous Articles     Next Articles

Advances in LiDAR technology in the field of animal ecology

Shun Li,Liang Zou,Yinan Gong,Haitao Yang,Tianming Wang,Limin Feng,Jianping Ge()   

  1. Aumer Tiger and Leopard Biodiversity National Observation and Research Station, Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, National Forestry and Grassland Administration Key Laboratory for Conservation Ecology of Amur Tiger and Amur Leopard National Park, National Forestry and Grassland Administration Amur Tiger and Amur Leopard Monitoring and Research Center, College of Life Science, Beijing Normal University, Beijing 100875
  • Received:2019-05-16 Accepted:2019-08-10 Online:2019-09-20 Published:2019-09-25
  • Contact: Jianping Ge


LiDAR (light detection and ranging), a fairly new active remote sensing technology, is being widely used in the field of animal ecology by more and more scholars due to the recent development where forest parameters can be extracted and inverted from LiDAR. In this paper, we review the advances in forest parameter extraction from LiDAR and its many applications in studying wildlife habitat. We also analyze current research on forest parameter inversion algorithms based on LiDAR, mainly in forestry research, though we lack quantitative parameters related to the ecological significance of animals. Because few studies have applied LiDAR technology to animal ecology research in China, we consider foreign research in this field in three categories: (1) The relationship between species habitat selection and three-dimensional forest structure; (2) Three-dimensional habitat mapping; (3) Biodiversity assessment and species distribution model prediction. Compared with traditional methods, the high-precision three-dimensional structure information provided by LiDAR can significantly improve the efficacy of monitoring animal habitat quality and biodiversity and the modelling accuracy of species distribution models. These advancements contribute to deeper understanding of species habitat selection and the clustering process mechanism. However, the studies that utilize LiDAR to date have mainly focused on previously known ecological relationships, especially the relationship between canopy structure and species diversity. These studies fail to account for either forest understory habitat quality or biodiversity monitoring and evaluation. In short, the relationship between wildlife and its three-dimensional habitat needs to be further explored through analysis of LiDAR data. Future studies should focus on extracting three-dimensional structures of forest understories to improve the efficacy of monitoring habitat quality and biodiversity in the understory, and to provide standard quantitative indicators for the evaluation of animal ecology.

Key words: remote sensing, animal habitat monitoring, species distribution, biodiversity