ABSTRACT
The aim of this study was to investigate the properties of point clouds derived from aerial image matching and to compare them with point clouds from airborne laser scanning. A set of aerial images acquired in years 2010-2013 over the city of Elblag were used for the analysis. Images were acquired with the use of three digital cameras: DMC II 230, DMC I and DigiCAM60 with a GSD varying from 4.5 cm to 15 cm. Eight sets of images that were used in the study were acquired at different stages of the growing season - from March to December. Two LiDAR point clouds were used for the comparison - one with a density of 1.3 p/m2 and a second with a density of 10 p/m2. Based on the input images point clouds were created with the use of the semi-global matching method. The properties of the obtained point clouds were analyzed in three ways: - by the comparison of the vertical accuracy of point clouds with reference to a terrain profile surveyed on bare ground with GPS-RTK method - by visual assessment of point cloud profiles generated both from SGM and LiDAR point clouds - by visual assessment of a digital surface model generated from a SGM point cloud with reference to a digital surface model generated from a LiDAR point cloud. The conducted studies allowed a number of observations about the quality of SGM point clouds to be formulated with respect to different factors. The main factors having influence on the quality of SGM point clouds are GSD and base/height ratio. The essential problem related to SGM point clouds are areas covered with vegetation where SGM point clouds are visibly worse in terms of both accuracy and the representation of terrain surface. It is difficult to expect that in these areas SGM point clouds could replace LiDAR point clouds. This leads to a general conclusion that SGM point clouds are less reliable, more unpredictable and are dependent on more factors than LiDAR point clouds. Nevertheless, SGM point clouds generated with appropriate parameters can have better accuracy than LiDAR point clouds and present more detailed information about the terrain surface.