Georeferencing, Digitizing, and 3D Scenes

Georeferencing 

This week's lab was georeferencing - the process of taking an unknown (without coordinate data) raster image and placing it correctly on the map by using vector data of known provenience.  I took satellite images of the North and South campuses and georeferenced them using common points from the shapefiles of the campus buildings and roads such as intersections.  This process creates a stitched together map of the two places that has a placement accurate to the real world.

The more links (control points) between the unknown raster and the known shapefiles the more data ArcGIS Pro has to work with.  The method to evaluate the quality of an individual control point is to look at the residual values of the control points.  If a point has a high residual value it may be misplaced - or if it seems perfectly accurate than the other points may be the source of the inaccuracy.  It is also important that the points are evenly spaced around the image and not clustered in a certain area or all in a line.

Root mean square error (RMSE) is a means of measuring the accuracy of the georeferenced image as a whole.  A lower RMSE means an image is more accurately georeferenced.  Another way to get a an image more accurate is to have enough control points to have a 2nd or 3rd order polynomial transformation.  This gives ArcGIS Pro a greater ability to flex and bend the image it is working with so it can better distort to the control points.  Though sometimes this can distort an image too much so even if the RMSE is low it is important for a human to evaluate the final look of the geoferenced image.

Digitizing

Digitizing is the process of drawing in new features on the map.  In this part of the lab I drew in a polygon for the gymnasium that did not already exist as a building as well as Campus Lane based off of aerial photography.  When making the road it was important to activate edge snapping so that the new road connected to the other roads.

This lab also provided an opportunity to use buffers again as we had to put a buffer around a bald eagle's nest so that future campus construction can be planned around the protected area.  I made a multi-ring buffer - one ring at 330 feet for the conservation easement placed around the nest, and 660 feet protection area that is required by the FWC for certain kinds of development.  Ultimately, the map produced for this part of the lab shows where the eagle's nest in relation to current campus structures so that developers can work around it in the future.

A map of UWF's campus buildings and roads in relation to a known eagle's nest.

3D Scene

The final part of this lab was to make a 3D scene.  This means overlaying the roads, buildings, and georeferenced images over a digital elevation model (DEM).  To create the DEM I took a LiDAR layer and used the geoprocessing tool "LAS Dataset to Raster."  Using this created DEM as a ground for the scene superimposes the layers over it to create the 3D effect.  To make it more striking, I also made the buildings 3D by setting the building height provided by their attribute table to their maximum height in the appearances tab.

A 3D map of UWF's campus