Digital elevation model (dem) generation with lidar point cloud filtered by different algorithms

Digital Elevation Model (DEM) and Digital Terrain Model (DTM)are the important topographic products and essential demands for many applications. Traditional methods for creating DEM and DTM are very costly and time consuming because of land surveying. In time, Photogrammetry has become the first methods to generate DTM. Recently, airborne Light Detection and Ranging (LiDAR) system has become a powerful way to produce a DEM or DTM due to advantage of collecting three-dimensional information over a large area very effectively by means of precision and time. Airborne LİDAR collects information about not only from land surface but also from every object between plane and terrain that can reflect the laser beam. So filtering out nonground points from raw point clouds is the major step of DEM and DTM generation. DEM and DTM generation from Lidar point cloud is not fully automation. There are lots of different filtering algorithm due to several factors affect the filtering prosedures. These algorithms are working in different accuracy for different topographical areas. Because of topographical features is established based algorithms are not applicable to every land. DTM can be produced with different interpolations of the filtered data. However, filtering results directly affect the interpolation results. Because each interpolation method, create the model starting from the data set that is filtered. That's why filtering errors is also available in created DTM. DEM and DTM generated from filtered airborne lidar data with free license software are sensitive enough to be used as a base model for many projects. But airborne Lidar system's own inherent sensitivity and filtering caused outliers still affect consequences. To improve the results new filtering algorithms can be developed and and different data types may also be included to filter.