ADVANCED DTM GENERATION FROM LIDAR DATA
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The introduction of laser scanning has triggered o a revolution in topographic terrain capturing, especially in the generation of digital terrain models (DTM). In this article refined methods for the restitution of airborne LIDAR data are presented which have been developed at the Institute of Photogrammetry and Remote Sensing (Institut f¨ Photogrammetrie und Fernerkundung, I.P.F.) at Vienna University of Technology. First, a technique for the calibration of laser scanner data is introduced. The (height) discrepancies between overlapping strips, as well as control points with known co-ordinates are utilised for a simultaneous adjustment and transformation of all strips into a state wide co-ordinate system. The next step of LIDAR data processing are the filtering (elimination of vegetation and building points, generally o-terrain points) and the interpolation of the (bald earth) surface. The method, developed at the I.P.F., distinguishes itself in the integration of filtering and terrain interpolation in one process (advantage: even in steep terrain ground points are classified correctly) as well as in the application of data pyramids (advantage: even in very dense forest areas and on large buildings, o-terrain points are eliminated). In order to generate a terrain model with high geo-morphological quality, methods are required for deriving structural line information (e.g. break lines) from laser scanner data. The first method which will be presented, proceeds by a simulation of rain fall over the preliminary DTM (water flow analysis). This yields an identification of the pits with their pit base and the outflow (overflow) point. Subsequently, the terrain shape is changed in order to eliminate the pits. In a further method 3D break lines are derived from the original laser scanner points. The precondition is that the ground plan of the break line is known approximately. The result of this step are 3D-splines which are integrated in the hybrid DTM, combining raster and vector data. KURZFASSUNG
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