Scale Effect and Spatial Data Aggregation

In this lab we first looked at how the scale at which we analyze data can affect geometric properties. Looking at data at three different scales (1:1200, 1:24000, 1:100000) I was surprised by my final calculations. I thought that there would be a lineal proportional relationship along the scales, but I did not find this. It makes sense that the greatest resolution [1:1200] would have the most detail of geometric properties, but I was surprised that 1:100000 had greater geometric properties than the medium resolution.

I resampled the data using the Bilinear technique and found the following effect on DEM resolution.

As DEM resolution increases the average slope in degrees decreases. This makes sense because as you get closer, more in detail by getting closer, you are zooming in as actively seeing less features altogether.

In the last part of the lab, we looked into the Gerrymandering of districts in the USA. Gerrymandering essentially breaks up congressional districts in a manner that establishes an unfair advantage to a given political party. One can clearly see by the following example how oftentimes the way districts are broken up makes no sense whatsoever. In the following district in Michigan, this district is divided into 4 different sections that could have easily been absorbed by neighboring land.

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Utilizing ERDAS Imagine to Analyze Map Features

This week we learned how to utilize histograms and different bands to highlight different features in a map. On the following map that we worked on, dark bodies of water caused high peaks on the left of histograms while snow-peaked mountains were small blips on the far right. These simple distinctions help to quickly identify map features on a graph, that you can then utilize as a stepping stone to finding them on the image. I found it incredibly interesting how the different band layers highlighted different features on the map. Figure 1 below depicts three different features we found on the image. Figure 1: Distinct features found on an image using ERDAS Imagine. Feature 1: Large body of water. Feature 2: Snow-capped mountains transitioning to thick vegetation. Feature 3: Shallow turbulent body of water near urbanized land, transitioning to deep calm body of water.

Positional Accuracy: NSSDA

In this analysis, I compared the street and road intersect data collected for Alburquerque, NM by the City of Alburquerque and the application StreetMaps. I used an orthophoto base layer as the reference for this analysis, to compare and determine the accuracy of both the City and Streetmap layers using NSSDA procedures. The most difficult part of this analysis for me was how to determine what 20% per quadrant looks like. Because the reference map was divided into 208 quadrants, I had to determine how to subdivide all the quadrant's equality into 20%. After multiple trials and error, I decided to subdivide the entire area (208 sub-quadrants) into 4 equal-area subsections. In this way, I could do 5 random right intersection points per subsection or 20% per subsection. Map 1: City of Albuquerque city map data. Map 2: City of Alburquerque SteetMap data When selecting a random intersection to place the points within each quadrant, I choose a location that had data f...

Georeferencing, Editing, and Creating 3D Maps in ArcGIS Pro

During the last week of Intro to GIS, we learned how to utilize control points on an unreferenced map layer. This provided georeferenced points on the originally unreferenced map layer, placing it correctly on top of baselayers while using RSME as a guide to accuracy. Additionally, we edited map layers to add newer construction elements in the form of buildings and roads that were not previously on the map. Lastly, a LAS dataset was used in a Scene Map to create a 3D map of the main campus location of the University of West Florida. Below are the final maps for each of these steps. Figure 1: University of West Florida Main Campus Map. Ariel photographs georeferenced for accuracy, and new construction of gym building and Campus Lane edited into the map. A 330 and 660 ft buffer was also created around a protected eagles nest. Figure 2: 3D map of the Main Campus of the University of West Florida.

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