Methods of laser scanning point clouds integration in precise 3D building modelling

• Existing and enhanced methods of homologous point pairs extraction were examined.
• The semi-automatic and automatic methods for extracting points were inspected.
• The biggest residuals has been observed for automatic point extraction methods.

3D city models are built on the basis of photogrammetric data, especially laser scanning (LS) data. Due to the increasing levels of accuracy required of 3D city models, terrestrial and airborne laser scanning are the most frequently used technologies. The models are often fragmentary, based on only one type of geodata, e.g. aerial photography or airborne laser scanning (ALS) data. This paper presents various aspects of integrating data from different laser scanning technologies (terrestrial and airborne), which are at the moment considered to be the most detailed and accurate systems for the direct acquiring of 3D geodata. The main issue discussed in the paper is the integration of data in the form of point clouds acquiring from different laser scanning systems. Integration will be understood here as an appropriate processing of both sets of data for orientation into a uniform spatial coordinate system. Thus, the problem of extracting characteristic points common for both sets, in a way which will allow for obtaining a basis for building a complete and accurate 3D city model, will be fundamental. The main challenge when performing this task is to correctly and accurately specify the homologous point pairs used in 3D transformation when both data sets characterise different accuracy, density and content. In the present paper, manual (direct), semi-automatic (indirect determination of characteristic points by approximation) and automatic (3D model) methods for extracting characteristic points are presented, along with the results of an accuracy assessment. Furthermore different transformation methods (isometric, conformal and affine) are also verified, compared and analysed.

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