Application of Areal Change Detection Methods Using Point Clouds Data

Abstract

Surveying techniques such as Terrestrial Laser Scanner have recently been used to measure surface changes via 3D point cloud (PC) comparison. Since there are no signalized points when using laser scanners and no identical points between two epochs, judging an object change detection can only be based on areal methods. A surface based analysis is able to detect changes that are unknown and spread along the whole surface. Existing methods for point cloud comparison and the source of uncertainties are reviewed in the first part of the paper. Current comparison methods are based on a closest point distance or require at least one of the point cloud to be meshed. Better results can be achieved with using Least Square Adjustment of polynomial surfaces (planes and quadric height functions) applied on point cloud data. Examples for change detection based on measurements obtained from terrestrial laser scanning for a double-arc object are given. Two areal methods for comparing two point clouds are used and the obtained results are analyzed.