Unmanned Aerial Vehicle-Based Photogrammetric 3D Mapping: A survey of techniques, applications, and challenges

Abstract

Three-dimensional mapping is an increasingly important feature for recent photogrammetry and remote sensing (RS) systems. Currently, unmanned aerial vehicles (UAVs) have become one of the extensively used RS platforms due to their high timeliness and flexibility on data acquisition as well as their high spatial resolution of recorded images. UAV-based 3D mapping has overwhelming advantages over traditional data sources from satellite and aerial platforms. Generally, the workflow of UAV-based 3D mapping consists of four major steps, including 1) data acquisition by using an optimal trajectory configuration, 2) image matching to obtain reliable correspondences, 3) aerial triangulation (AT) to resume accurate camera poses, and 4) dense image matching to generate point clouds with high density. The performance of the algorithms used in each step determines the reliability and precision of the final 3D mapping products.