Aerial laser scanning (lidar) has become a widely used technique for spatial data production. Although various rigorous error models of aerial laser scanning already exist and examples of a-posteriori studies of aerial laser scanning data accuracies verified with field-work can be found in the literature, a simple measure to define a-priori error sizes is not available. In this work the aerial laser scanning error contributions are described in detail: the basic systematic error sources, the flight-mission-related error sources and the target-characteristic-related error sources. A review of the different error-source sizes is drawn from the literature in order to define the boundary conditions for each error size. Schenk’s geolocation equation is used as a basis for deriving a simplified a-priori error model. By changing different geometrical parameters the simulation of error sizes is made and the influence of different error sources is studied. This simplified error model enables a quick calculation and gives a-priori plausible values for the average and maximum error size, independent of the scan and heading angles as well as being independent of any specific aerial laser scanning system’s characteristics. Spatial data production by aerial laser scanning is also limited by acquisition precision. The acquisition precision is defined by spatial data products (in our case: geodetic data for local spatial planning). The acquisition precision of spatial data products also defines the minimum point density of aerial laser scanning. The minimum point density when applying aerial laser scanning as a stand-alone-technique is defined through minimal sampling density or Nyquist frequency. Through measuring penetration rate for different vegetation classes in the test area the total usable point density is defined. The a-priori aerial laser scanning accuracy and spatial data product precision defines when the aerial laser scanning can be applied in data extraction process in Slovenia. Through this the acquisition methodology for different geodetic data for local spatial planning production can be optimized. The review on legal acts defining the local spatial planning is given. The current and proposed data processing methodology for different geodetic data used for local spatial planning is described
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