Lab 6--Create a 3D Scene

Again, this portion of the lab built on the two previous products. By downloading a LiDAR layer from the National Map Viewer, I was able to create elevation and relief on the other layers.

To begin, I created a New Local Scene (Insert-New Map Dropdown) and added the LiDAR layer to the scene. In order to smooth the output, I filtered the image by selecting "Ground." I then searched for "LAS Dataset to Raster" in the geoprocessing pane in order to create a digital elevation model (DEM). When the DEM layer was selected, the image appeared to look like terrain features with different colors symbolizing different elevations. In contrast the previous incarnations were more pixelated and reflected off different surfaces.

Once the UWF buildings layer and roads layer were added to the resulting layer, they appeared to be "draped over" the terrain. For this project, I de-selected the DEM layer because I thought the World Elevation 3D/Terrain 3D layer looked better. Once this was complete, I added another layer for a map deliverable. Of course, the map had all essential elements. The only challenge was in rotating the 3D layer so that it was arrayed the way I wanted. There are many ways to do this; however, I went into the properties, and manipulated the degrees of rotation until I liked the result.
The resulting map is displayed below:

Map 3: 3D View of UWF Campus

The above map is the culmination of the entire lab. As stated, all essential map elements are present. The north arrow is arrayed to be the actual magnetic north of the raster layers. If I rotated the map, the north arrow would move in the appropriate direction. The original UWF roads are in red, the original UWF buildings are in light blue, Campus Lane (created feature) is purple, and Building 072 (created feature) is green. The scale bar is in feet because the overall map is in feet. I also added the map data which provides the author/date, sources, elevation ground surface method, and the RMSE and transformation degree.

Week Six Lab--Georeferencing

Part I of this week's lab taught georeferencing. Two UWF (north and south) raster projections were added to the map. Once added, they appeared on "Null Island" off the west coast of Africa until the layers were georeferenced and "knew" their actual location. To move the image from Null Island, I clicked on the "Fit to Display" button. Once the image was located on top of the current layer, I added control points to align the image with the actual map. A few lessons: Spread out the control points, consider the effects of shadows on building geometry, zoom into the layers for accurate control point placement, and place the control point on the unreferenced layer first.

Review the overall Root Mean Square Error to determine how close the points were to the actual location. Remove control points (view the control point table) with high RMSEs to reduce overall RMSE. Then, determine the transformation to use. The higher the transformation level, the more control points (6 for 2d Order Polynomial; 10 for a 3d Order Polynomial) are needed and the more the raster bends.

Another very interesting portion of the lab demonstrated the techniques to place an unreferenced copy of a drawn map. Once I added the survey map (as imagery), I then georeferenced the map to the referenced imagery as before. This was much more difficult because the map was much older, had limited information, and skewed excessively if control points were placed too close (next to each other versus opposite sides of the image).

Heritage Hall Georeferenced

The above image is the result of georeferencing a parcel survey and then placing it on a UWF Campus image. The control points are shown in red (parcel survey) and green (image) and the overall RMSE was 6.770932. The most efficient way to place control points was to use the edges of parking lots and the points of medians, since no buildings were drawn on the parcel survey. Again, place control points on opposite ends of the image (much like you tighten lug nuts on a tire) to reduce distortion. 

Projections

In this lab, I learned to download data (from FGDL) and input it into a project. We then explored projections and learned that ArcGIS Pro requires data sets to be in the same projection (on the fly reprojecting) to be displayed together and have full functionality for analysis.

To demonstrate how different projections alter the orientation, size, compression, etc. of map features, I compared four Florida counties. By transforming the county data set to Albers, UTM, and State Plane, I produced three maps with an associated data comparison of area.

I then worked with raster projections and learned to input my chosen coordinate system. This will ensure the JPEG World File (.jgw) will have the correct coordinate system, resulting in a correct location display. I am very comfortable with UTM, because I am in the military and work extensively with MGRS, which is based on UTM.

Comparison of County Area Outputs Using the Albers, UTM, and the State Plane North Projections

Produced by Terry J. Dokey, January 22, 2020