Optimal flight parameters for unmanned aerial vehicles collecting spatial information for estimating large-scale waste generation

Large-scale waste and debris from disasters and building construction can cause secondary damage and environmental pollution. Satellite images and the Global Positioning System are being used to calculate the amounts of such waste. However, efficiency in terms of accuracy and cost remains problematic. To solve this problem, this study used an unmanned aerial vehicle (UAV) to build three-dimensional (3D) spatial information for large-scale waste generation. Appropriate parameters were selected to quickly and accurately estimate the amount of waste. Fifty-six scenarios were distinguished according to parameters such as flight altitude, image overlap, and number of ground control points (GCPs). Images were then registered by implementing the SIFT (Scale Invariant Feature Transform) and SfM (Structure from Motion) algorithms to build 3D spatial information and estimate the amount of waste. The accuracy was generally high when flight altitude and image overlap were high, and the number of GCPs was specific. Scenario A, with the lowest flight altitude and overlap, did not yield any registrable images. The results of the flight altitude showed a different tendency from those of existing studies. This could be attributable to the difference in the distance covered on the ground by an image in the width direction, which depended on the characteristics of study sites. Among all the scenarios, D-7 had the highest accuracy, with a root-mean-square error of about 0.08 m. In this scenario, the amount of waste was estimated to be approximately 767,571.3 m³. The top 10 scenarios in terms of the accuracy of x, y, and z locations displayed similar tendencies with regard to the amount of waste. In contrast, the bottom 15 scenarios showed a variety of results. When the accuracy and flight time of each scenario were considered, scenarios H-3, H-4, and H-5 achieved the highest accuracy in a short time. Thus, these scenarios were the most effective and applicable for estimating the amount of waste. Consequently, parameters such as flight altitude, image overlap, and GCPs need to be considered when estimating large-scale waste associated with a difference in elevation using a UAV.