Airborne laser scanning (ALS) of urban regions is commonly used asa basis for 3D city modeling. In this process, data acquisition relies highly on the quality of GPS/INS positioning techniques. Typically,the use of differential GPS and high-precision GPS/INS postprocessing methods are essential to achieve the required accuracythat leads to a consistent database. Contrary to that approach, we aim at using an existing georeferenced city model to correct errorsof the assumed sensor position, which is measured under nondifferentialGPS and/or INS drift conditions. Our approach accounts for guidanceof helicopters or UAVs over known urban terrain even at night and during frequent loss of GPS signals. We discussseveral possible sources of errors in airborne laser scanner systemsand their influence on the measured data. A workflow of real-timecapable methods for the segmentation of planar surfaces within ALS data is described. Matching planar objects, identified in boththe on-line segmentation results and the existing city model, areused to correct absolute errors of the sensor position.
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Airborne laser scanning (ALS) of urban regions is commonly used asa basis for 3D city modeling. In this process, data acquisition relies highly on the quality of GPS/INS positioning techniques. Typically,the use of differential GPS and high-precision GPS/INS postprocessing methods are essential to achieve the required accuracythat leads to a consistent database. Contrary to that approach, we aim at using an existing georeferenced city model to correct errorsof the assumed sensor position, which...
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