GIS4930 T2 M1
In this lab, I worked through a series of exercises designed to compare and apply two fundamental elevation data models: TINs (Triangulated Irregular Networks) and DEMs (Digital Elevation Models). The workflow highlighted how these models can be visualized, analyzed, and compared to better understand terrain.
Part A: Draping imagery over terrain
This part of the lab had us looking at Death Valley with a remotely sensed image draped over a TIN, which was used as an elevation layer to produce a 3d image. We added vertical exaggeration to reveal surface features that weren't noticeable in the flat imagery.
Part B: Ski run suitability modeling
Next, I built a suitability model using a DEM. I reclassified elevation, slope, and aspect into categories of suitability, then combined them in a Weighted Overlay. The resulting raster identified areas best suited for ski runs, with greens showing higher suitability and reds showing lower suitability (see screenshot below). I also got to use the illumination settings, and chose noontime at maximum brightness.
Part C: Exploring TINs
I then worked with a provided TIN and experimented with different symbology options. By coloring the surface by slope, drawing edges, and adding contours, I was able to display multiple dimensions of terrain information. I struggled a bit with getting the contour distance correct and navigating the symbology in this view. Having my contour lines too dense made slopes illegible at a distance, and I played around a lot with the symbology of each part before something looked right.
Part D: Creating and analyzing TINs
Finally, I created a new TIN from elevation points within a study area boundary, and DEM from the same points using the Spline tool. I compared the contours from this TIN with the DEM. The differences were the greatest in rugged areas with protruding features, sharp curves, etc; the TIN showed jagged lines while the DEM smoothed them into contours. This showed the relative trade-offs between using TINs and DEMs for resolution and accuracy.
Part A: Draping imagery over terrain
This part of the lab had us looking at Death Valley with a remotely sensed image draped over a TIN, which was used as an elevation layer to produce a 3d image. We added vertical exaggeration to reveal surface features that weren't noticeable in the flat imagery.
Part B: Ski run suitability modeling
Next, I built a suitability model using a DEM. I reclassified elevation, slope, and aspect into categories of suitability, then combined them in a Weighted Overlay. The resulting raster identified areas best suited for ski runs, with greens showing higher suitability and reds showing lower suitability (see screenshot below). I also got to use the illumination settings, and chose noontime at maximum brightness.
Part C: Exploring TINs
I then worked with a provided TIN and experimented with different symbology options. By coloring the surface by slope, drawing edges, and adding contours, I was able to display multiple dimensions of terrain information. I struggled a bit with getting the contour distance correct and navigating the symbology in this view. Having my contour lines too dense made slopes illegible at a distance, and I played around a lot with the symbology of each part before something looked right.
Part D: Creating and analyzing TINs
Finally, I created a new TIN from elevation points within a study area boundary, and DEM from the same points using the Spline tool. I compared the contours from this TIN with the DEM. The differences were the greatest in rugged areas with protruding features, sharp curves, etc; the TIN showed jagged lines while the DEM smoothed them into contours. This showed the relative trade-offs between using TINs and DEMs for resolution and accuracy.
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