This week's lab was a further familiarization with triangular irregular networks (TINs) and digital elevation models (DEMs). We have seen these two forms of models in prior exercises such as suitability analyses, cost-distance analyses, least-cost path analyses, and corridor analyses.
With the first TIN we were provided, we simply observed it in its two-dimensional form. We then added it as an elevation source in a local scene and observed the data's representation in three dimensions.
The next task was to develop a suitability map for a proposed ski slopes. The purpose of this section of the lab was to become familiar with the use of DEMs. We were provided with the DEM and coverted it from a raster image to a TIN with the 'Raster to Tin'' tool.
As exercised in previous labs, we then had to preform a suitability analysis. The criteria our ski slopes were required to meet in order to be considered an excellent choice for the proposed slopes were:
- Elevation is required to be over 2501 feet.
- Slope must be between 30 and 45 degrees.
- The slops must be facing southwest.
In order to perform the analysis, we needed to reclassify our DEM for elevation. Using the reclassify tool I was able to divide the elevation into 3 distinct elevation ranges and class them according to suitability. Next, the slope tool was used to calculate the slope from the DEM. The output was then reclassified to rank the appropriate suitability.
In order to determine which surfaces were facing which direction, the Aspect tool was used which coordinates each face via color to their corresponding direction. Once again, this was reclassified with the southwest directions being ranked as most desirable.
To create the suitability map, we were required to weigh our results in favor of elevation. Instead of using the Raster calculator to illustrate areas of highest value, we used the Weighted Overlay tool. This compiled our rasters, illustrating areas of the highest merged values weighted in favor of elevation.
This is the result:
Once this task was complete, we further investigated TINs by creating one from two shapefiles. One a point shapefile and the other a study area boundary polygon.
To accomplish this we simply used the Create TIN tool. We then added contours spaced at 100m and added the TIN ass the elevation source for three dimensional visualization.
For comparison, we used the Spline tool to create a DEM with the elevation point shapefile. The same contours were then added.
In comparing, the contours derived from the DEM created by the elevation points provided more visual detail especially at the top of the higher elevation points where isolines were omitted with the created TIN contours. An interesting facet of note was that the contour lines generated from the TIN represented actual measurements from the elevation points whereas the offers uniform rounded values at 100m intervals as its contour. The DEM contours also offered a stark contrast in regard to shape as they had well rounded smooth isolines whereas the TIN lines were straight and angled when direction was changed. Therefore, detail in regard to value detail is greater with the TIN though the visual appeal is greater with the DEM contours. Issues arise when investigating the higher elevation value contours in the DEM. As noted above, though they show more detail visually, some of these representations may be incorrect in regard to their real world existence. Focusing on the isolines representing 2000ft, there is a possibility that there is no land form there that reaches that height as no data point of that elevation was recorded. Therefore, it may simply be generated from inference and not reality.
Here are images of the two elevation model contours:
TIN:
DEM:
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