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P. Glira:
"Orientation and Calibration of Point Clouds from Terrestrial and Airborne Laserscanning Systems";
Talk: ETH-Geomatik-Seminar, Zurich, Switzerland (invited); 2016-04-07.

The orientation quality of point clouds is often unsatisfactory. To optimize it, a variety of surface matching algorithms exist. The most widely known surface matching method is the iterative closest point (ICP) algorithm, which can be used to minimize the differences between a single pair of point clouds. We extended the algorithm to handle an arbitrary number of point clouds simultaneously and published it as open source software. On this basis, a rigorous strip adjustment method for airborne laserscanning (ALS) data was developed. It can be applied to simultaenously optimize the orientation of all ALS strips by fully re-calibrating the laser scanning system and by correcting systematic measurement errors of the trajectory. Recently the strip adjustment method was integrated with the bundle block adjustment of aerial images. First results indicate that both data inputs, the laserscanning point clouds, as well as the aerial images, strongly benefit from such an integration.