Automatic bat counting and identification of bat species using terrestrial laser scanning

Abstract

The current practice in roosting bat population survey and species identification is either based on net capture, visual observation or optical-mechanical count methods. However, these methods are intrusive, tedious, time consuming and at best, only reports an estimation of the roosting population of bats. Here, the present study showed the use of Light Detection and Ranging (LIDAR) concept using terrestrial laser scanner was successful in remotely identifying and determining the exact population of roosting bats in caves. The laser scans accurately captured the three dimensional (3D) features of the roosting bats and their spatial distribution pattern in total darkness. Using LIDAR, the determination number of bats can be conducted, spatially analyze the 3D distribution of bat populations as well as generate a 3D topological structure of the roosting cave. This resulted in a high resolution model of the cave, enabling exact count of visibly differentiated individual bats. This successfully leads to the species identification of the Hipposideros larvatus and Hipposideros armiger reported in this study. This studies anticipate that the development of the LIDAR into a non-intrusive technique will open up new possibilities in bat roosting studies. This novel method would possibly allow future works accomplishment of researchers to study roosting behavior such as maternity roosting patterns, roost sharing and roost-switching patterns within the topographical context of the speleological (caves, subterranean spaces and caverns) internal surface, thus making rigorous quantitative characterizations of cave roosting behavior possible. The final results of this study would be an automated procedure for bat population count and the function of point cloud data in assisting the species identification.