Optimization of Land Area Mapping and Volume Calculations using Drone Lidar Livox Mid-40 Data with the Downsampling Method

Abstract

One reason for the growing acceptance of 3D point cloud-based research and applications is the quick advancement of 3D scanning technologies. However, there are still a number of serious issues that have an impact on point cloud utilization performance. Among these difficulties are controlling the quantity of points, irregular point density, and a deficiency of location proximity data. In this study, we use Livox Mid-40 Drone Lidar Data and a downsampling technique to compute land area and volume. However, it can be highly challenging and time-consuming to extract usable information from enormous amounts of gathered data. Motivated by these results, this study recommends using downsampling approaches to minimize the size of the final data set while preserving data integrity, which will facilitate and expedite. The Livox Mid-40 Lidar Drone data was optimal at 00:00:30 with a flying height of 75,719 meters and a measurement diameter of 50.3 meters. By using downsampling techniques, the number of points can be reduced by up to 40 percent from the previous number of data points. Meanwhile, the data size can be 10 percent smaller than the original data. To calculate the area of land of the same size, there is a difference of 0.53 square meters. Meanwhile, for the calculation of cubic volume, there is a difference of 1.63 cubic meters.

Keywords

• optimization
• land area mapping
• volume calculations
• drone lidar livox mid-40 data
• downsampling method