Point Cloud Data for Topographic Geospatial Analysis


A point cloud is a huge collection of individual points in 3D space. Such data is becoming ever more cheap and easy to obtain, for example using drones with on board LiDAR sensors.

Point clouds can be visualized either by spatially indexing and drawing the individual points or by generating a 3D model.

Both options are hard to combine efficiently with topographic geospatial analyses that work on digital elevation models.

The purpose of the Master’s Thesis is to evaluate different methods of directly making use of point cloud data in analysis and algorithms that work on digital elevation models.

This task is suitable for students interested in algorithms and data structures.


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