Methods in Ecology and Evolution (Jul 2023)
ForestScanner: A mobile application for measuring and mapping trees with LiDAR‐equipped iPhone and iPad
Abstract
Abstract Ground‐based light detection and ranging (LiDAR) is becoming increasingly popular as an alternative means to conventional forest inventory methods. By gauging the distances to multiple points on the surrounding object surfaces, LiDAR acquires 3D point clouds from which tree sizes and spatial distributions can be rapidly estimated. However, the high cost and specialized skills associated with LiDAR technologies have put them out of reach for many potential users. We here introduce ForestScanner, a free, mobile application that allows LiDAR‐based forest inventories by means of iPhone or iPad with a built‐in LiDAR sensor. ForestScanner does not require any manual analysis of 3D point clouds. As the user scans trees with an iPhone/iPad, ForestScanner estimates the stem diameters and spatial coordinates based on real‐time instance segmentation and circle fitting. The users can visualize, check and share the scanning results in situ. By using ForestScanner, we measured the stem diameters and spatial coordinates of 672 trees within a 1 ha plot in 1 hr 39 min with an iPhone and in 1 hr 38 min with an iPad (diameter ≥ 5 cm; detection rate = 100%). The diameters measured by ForestScanner and a diameter tape were in good agreement; R2 = 0.963 for iPhone and R2 = 0.961 for iPad. ForestScanner and a conventional surveying system showed almost identical results for tree mapping (assessed by the spatial distances among trees within 0.04 ha subplots); Mantel R2 = 0.999 for both iPhone and iPad. ForestScanner reduced the person‐hours required for measuring diameters to 25.7%, mapping trees to 9.3%, and doing both to 6.8% of the person‐hours taken using a dimeter tape and the conventional surveying system. Our results indicate that ForestScanner enables cost‐, labour‐ and time‐efficient forest inventories. The application can increase the accessibility to LiDAR for non‐experts (e.g. students, citizen scientists) and enhance resource assessments and biodiversity monitoring in forests world‐wide.
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