Rock formations are among the most spectacular landscape features both for experts and the public. However, information about these objects is often stored inaccurately in existing spatial databases, their corresponding elevations are missing, or the entire rock object is completely absent. Cartographic depiction is also reduced to a point of areal symbology of a largely generalized character. This paper discusses options in identifying and analyzing rock formations from two digital terrain models (DTMs), DMR 5G and DMR 5G+, and irregularly spaced points of airborne laser-scanning (ALS) data with different point densities. A semi-automatic method allowing rock formations to be identified from DTMs is introduced at the beginning of the paper. A method to evaluate elevation models (volume differences) is subsequently applied and a 3D model of a selected rock object is created from terrestrial laser-scanning data. Finally, positional and volumetric comparisons of that 3D object are performed in 2D, 2.5D, and 3D. The results of the pilot study confirmed that the digital terrain models studied are a reliable source in identifying and updating rock formations using the semi-automatic method introduced. The results show that DMR 5G model quality decreases with increasing fragmentation and relative rock formation height, while the proportion of gross errors increases. The complementary DMR 5G+ is better in terms of location and altitude.
ABSTRACT:A large increase in the creation of 3D models of objects all around us can be observed in the last few years; thanks to the help of the rapid development of new advanced technologies for spatial data collection and robust software tools. A new commercially available airborne laser scanning data in Czech Republic, provided in the form of the Digital terrain model of the fifth generation as irregularly spaced points, enable locating the majority of rock formations. However, the positional and height accuracy of this type of landforms can reach huge errors in some cases. Therefore, it is necessary to start mapping using terrestrial laser scanning with the possibility of adding a point cloud data derived from ground or aerial photogrammetry. Intensity correction and noise removal is usually based on the distance between measured objects and the laser scanner, the incidence angle of the beam or on the radiometric and topographic characteristics of measured objects. This contribution represents the major undesirable effects that affect the quality of acquisition and processing of laser scanning data. Likewise there is introduced solutions to some of these problems.
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