Quantifying How Deliverables Change with Varying Acquisition Techniques
RME Geomatics has been operating 2 Riegl VUX LiDAR systems since the first production units were released, over 3 years ago. These scanners have been employed on RME?s Renegade UAV system, as well as Bell 206 and Cessna 206 platforms for operations across Canada in a variety of industries from mining and oil & gas, to corridor mapping and agriculture. This experience has seen a variety of requirements and expectations from customers, which in many cases need assistance in understanding the technical requirements (and limitations) of data accuracy and point density based on their application. A case study is presented using data that has been processed to showcase variables of accuracy and point density and the affect on typical deliverables for terrain modelling and infrastructure (beyond a point cloud). The analysis emphasizes the variation in resulting deliverables through techniques such as: watershed analysis, which provides different directions for water flow based on different point densities. Further analysis also shows the affects on final deliverables based on different approaches to dataset accuracy using different GPS baselines through the reprocessing of multiple projects against multiple baselines. This analysis makes use of LiDAR captured from a number of different platforms: conventional manned aircraft, unmanned aircraft, and mobile ground vehicles, as well as photogrammetric platforms: eBee and a M210. The case study presents a summary on the variation in deliverables through different data collection techniques and offers recommendations on minimum requirements in order to provide high quality and repeatable datasets for the customer?s end application.