LiDAR and image point cloud comparison

Abstract

This paper analyzes new techniques used to extract 3D point clouds from airborne and satellite electro-optical data. The objective of this research was to compare the three types of point clouds to determine whether image point clouds could compete with the accuracy of LiDAR point clouds. The two main types of image point clouds are those created photogrammetrically, with two side-by-side images, or through feature matching between multiple images using multiview stereo techniques. Two software packages known for handling aerial imagery, IMAGINE Photogrammetry and Agisoft Photoscan Pro, were used to create such models. They were also tested with sub-meter resolution satellite imagery to determine whether much larger, but still truthful, models could be produced. It was found that neither software package is equipped to vertically analyze satellite imagery but both were successful when applied to aerial imagery. The photogrammetry model contained fewer points than the multiview model but maintained building shape better. While the photogrammetry model was determined to be the more accurate of the two it still did not compare to the accuracy of the LiDAR data.