# Development and Performance Assessment of a Low-Cost UAV Laser Scanner System (LasUAV)
## 1 Introduction
[PERSON] et al. (2016) developed a light and flexible UAV-based system at a low cost to perform rapid mapping for an emergency response. [PERSON] et al. (2016) developed a system based on the combination of charge-coupled device (CCD) cameras, a laser scanner, an INS, and GNSS for a UAV-borne three-dimensional (3D) mapping system, which has been experimentally used in recovery efforts after natural disasters (e.g., landslides, river flooding). [PERSON] et al. (2016) developed a low-cost mini-UAV-based laser scanning system, also capable of performing car-based mobile mapping, for tree measurements. [PERSON] et al. (2016) developed a mini-UAV-borne LiDAR system and the associated data processing involved in the coordinate triple, pulse intensity, and multi-echoes per pulse extraction for fine-scale mapping (e.g., tree height estimation, pole detection, road extraction, and digital terrain model refinement). [PERSON] et al. (2016) developed a low-cost UAV-LiDAR system and the accompanying workflow to produce 3D point clouds with application in the forest inventory [PERSON] et al. (2016) developed a small UAV-based laser scanner system for rice monitoring at low altitudes, while [PERSON] (2016) designed and tested a UAV mapping system for agricultural field surveying. [PERSON] et al. (2016) developed a LiDAR-based UAV for surveys in impacted areas to collect geospatial data useful in disaster management and environment reconstruction planning. In general, the overall budget for developing a UAV laser scanner system is quite challenging and the time required to develop the system ([PERSON] et al., 2016; [PERSON] et al., 2016; [PERSON] et al., 2016; [PERSON] et al., 2016; [PERSON] et al., 2016; [PERSON] et al., 2016) is more than two years. For instance, [PERSON] et al. (2016) had about 6 million USD at their disposal to spend in four years. In projects without such a large budget available, efforts in system development should be put toward containing the costs of subcomponents ([PERSON] et al., 2016; [PERSON] et al., 2016; [PERSON] et al., 2016). In addition, as there is no reliable, quick, cheap, and handy method for acquiring accurate high-resolution 3D data on objects in outdoor and moving environments with a laser scanner [10], in most cases, a laser scanner in combination with another sensor (CCD cameras and high-definition video cameras) is used [10; 13]. Efforts in the development of LasUAV have been concentrated on developing a system that is much lower in cost than what is currently offered in the market and streamlining the procedures to produce the point cloud. Costly integrated solutions are, in principle, more accurate, but the accuracy of an integrated LiDAR system comes from the combination of sources of uncertainty originating from the laser, positioning, and INS sensors. Thus, the optimal trade-off between cost and desired accuracy is hard to find when developing or purchasing a LiDAR system. If, for example, very accurate INS attitude data are coupled with relatively inaccurate laser sensors, or vice versa, the system will not be well balanced in terms of cost versus accuracy. For the UAV laser scanner system (LasUAV) which was developed by a research project that lasted two years and is presented in this paper, a compromise between development time, cost, and linearity in the point cloud processing process was reached considering the limited resources available. The aims of this paper are as follows: (i) to present in detail the development of a new low-cost laser scanner system capable of being used in environmental and forestry applications on an operational basis due to the low investment cost; (ii) to assess uncertainties associated with the different components of the system and their impact on total uncertainty; (iii) to quantify the optimum balance among system subcomponents; and (iv) to provide guidelines both for the development of a laser scanner system and for its optimal operation in specific applications.