Module 11: 3D Mapping

This week's lab introduced us to 3D mapping. I enjoyed learning about this topic, as I've seen an been interested in 3D maps, but have never created them or had much exposure to them. This lab had 3 parts. The first part was the ESRI training, which taught us visualization techniques. The second part involved learning some applications and converting 2D data to 3D, and the third part reinforced some more 3D concepts. While 3D maps aren't ideal in every situation (road maps or maps where structures or the 3D element can obscure whatever element you wish to see), they are very useful and visually pleasing, and I enjoyed learning about them. Some learning objectives were:

- Performing techniques to visualize raster and feature data in 3D
- Convert 2D feature to 3D using lidar data derived elevation values
- Demonstrate proficiency with 3D Analyst Extension and ArcScene
- Export data to kmz and view in Google Earth
- Describe applications of 3D data

The ESRI training guide walked us through 3D mapping and 5 main concepts/tools:

1. Setting base heights for raster and feature data
2. Setting vertical exaggeration
3. Setting illumination and background color
4. Extrude buildings and wells
5. Extrude parcel values

Setting base heights was very useful and seems to be used in all aspects of 3D mapping. Setting the vertical exaggeration is very useful as well. It's usually used to exaggerate small variations in terrain so they are easier to visualize, although in one step of the module I needed to decrease the vertical exaggeration as well. Learning about illumination and background color was informative as well. I was able to change the illumination depending on the time of year, time of day, and you can even change the weather if you desire (at least on ArcGlobe). When extruding buildings and wells, I was able to extrude the buildings upwards to show the heights of the buildings and the wells downward to show the depth of the wells. I think extruding parcel values was one of the more useful parts of this lab. I was able to extrude buildings based on their total value, and it really shows that data well and would be very useful in urban planning scenarios. The ESRI training also taught us 3D visualization terminology and concepts, such as z-values, raster data, triangulated irregular networks (TINs), terrain datasets, multipatch features, and 3D features.

The second part of the lab involved converting 2D to 3D data. The raster surface for this dataset was provided but was derived using lidar (light detection and ranging). This part of the lab was mainly about learning 3D Analyst and its capabilities. After adding the building footprint and Boston.tif files, I used 3D Analyst to create random points. The objective is to generate these random points within the building shapefile and add surface (elevation) information to those points and summarize for each building. We created 100 random points per building (more points per building, of course, mean a finer resolution). I added surface information and used the Summary Statistics tool. Here is where I will need to be careful in the future. If I use the wrong field to join the mean Z value to the building footprint layer (OID being the wrong field), the building information would be for the building next to it (OID values range from 1-343, where FID and CID values range from 0-342). Just like in programming, this looks like it would be very difficult to spot once I progressed further through an exercise. I performed the join and exported the data to save it. I extruded the features in the layer, using the expression builder to extrude to "Mean Z." We wanted to share the data so that it's viewable on a platform such as Google Earth. I used the "Layer to KML Tool" to create a .kmz file of my data, which can then be used in Google Earth.

The objective of Part 3 was to compare and contrast two maps. One was of Charles Minard's map of Napoleon's Russian Campaign of 1812 in 2D, and the other is a 3D version of this map. Both are excellent maps, but I like the 3D version better because I like that on the 3D map, the portion of the advance into Russia is shown above the surface, and the retreat is below the surface. Temperature information is extruded downward (negative temperatures) and the 3D line visible expanded(shrunk) as the size of the army increased(decreased). It showed every bit of information the 2D map showed, but I feel it looked better, less "cramped". To me, the 2D map tries to put almost too much on one map, and the text was very small. The 3D map also incorporated colors that stood out, making it that much easier to see and analyze.