Summary

Elevation data can often provide a complete dataset for analysis and derivative products without any other data. In this chapter, you learned how to read and write ASCII Grids using only NumPy. You also learned how to create shaded reliefs, slope grids, and aspect grids. We created elevation contours using a little-known feature called contour in the GDAL library, which is available for Python.

Next, we transformed LiDAR data into an easy-to-manipulate ASCII Grid. We experimented with different ways to visualize the LiDAR data with PIL. Finally, we created a 3D surface or TIN by turning a LiDAR point cloud into a 3D shapefile of polygons. Then we colorized LiDAR using aerial images to create an almost photo-realistic 3D model. We also classified LiDAR so it can be an input to more sophisticated analysis models. And we saw that ocean seafloor data can be processed in much the same way as terrestrial data. These are the tools of terrain analysis that are used for transportation...