Another benefit of 3D data is that it can enable more advanced and accurate analysis of spatial phenomena. However, to achieve this, you need to know how to analyze the data accurately. This means applying the right techniques, algorithms, or models for your 3D data. For example, if you are analyzing point clouds, you may want to use clustering, segmentation, or classification methods to identify and extract features, or use interpolation, approximation, or reconstruction methods to create surfaces or volumes. If you are analyzing meshes, you may want to use geometric, topological, or morphological methods to measure and compare shapes, or use smoothing, simplification, or optimization methods to improve quality or performance. If you are analyzing extruded polygons or TINs, you may want to use spatial, statistical, or network methods to calculate and display distances, areas, volumes, or connectivity, or use overlay, buffer, or proximity methods to perform spatial queries or operations. You should be able to perform relevant and reliable 3D analysis for your data, and be able to interpret and communicate the results.