A low-cost multi-sensoral mobile mapping system and its feasibility for tree measurements

This paper presents a novel low-cost mini-UAV-based laser scanning system, which is also capable of performing car-based mobile mapping. The quality of the system and its feasibility for tree measurements was tested using the system’s laser scanner. The system was constructed as a modular measurement system consisting of a number of measurement instruments: a GPS/IMU positioning system, two laser scanners, a CCD camera, a spectrometer and a thermal camera. An Ibeo Lux and a Sick LMS151 profile laser were integrated into the system to provide dense point clouds; intensities of the reflected echoes can also be obtained with the Sick LMS. In our tests, when using a car as a platform, the pole-type object extraction algorithm which was developed resulted in 90% completeness and 86% correctness. The heights of pole-type objects were obtained with a bias of −1.6 cm and standard deviation of 5.4 cm. Using a mini-UAV as the platform, the standard deviation of individual tree heights was about 30 cm. Also, a digital elevation model extraction was tested with the UAV data, resulting in a height offset of about 3.1 cm and a standard deviation of 9.2 cm. With a multitemporal point cloud, we demonstrated a method to derive the biomass change of a coniferous tree with an R2R2 value of 0.92. The proposed system is capable of not only recording point cloud data giving the geometry of the objects, but also simultaneously collecting image data, including overlapping images and the intensity of laser backscatter, as well as hyperspectral and thermal data. Therefore we believe that the system is feasible for new algorithm and concept development and for basic research, especially when data is recorded multitemporally.