3D Mapping - TINs and DEMs

Moving on from Spatial Data Quality in GIS Special Topics, the next Lab focuses on surfaces with a comparison of the Digital Elevation Model (DEM) and Triangular Irregular Network (TIN). A surface in GIS is a geographic phenomena represented as continuous data. Continuous spatial data references geographic objects characterized by very gradual boundaries such as temperature or elevation.

The most common way to represent elevation data is with contour lines. Contour lines are 2-dimensional features with attributes containing the value of the surface at a given location. They can be derived by the TIN vector model or the DEM raster model.

TINs are used exclusively to represent a 3-dimensional surface. A series of linked irregular triangles comprised from elevation points (nodes) in 3D (X,Y,Z) coordinates (Manandhar, 2005) occurring at any given location represent the 3D surface. The topological relationship of the network of triangles creates a continuous surface. The normal vector of each triangle is used to assign the properties of Slope and Aspect.

 

DEMs are the simplest way to represent a topographic surface. A DEM is a regular raster that uses a regular rectangular grid method (Manandhar, 2005) with cell values representing elevation or spot height. The cell size of a DEM determines the resolution. Therefore a DEM with a high number of smaller sized cells provides more accuracy than a DEM with less larger sized cells. Data becomes more implicit with larger cell sizes.

One part of this week's lab utilizes a DEM to develop a 3-dimensional Ski Run Suitability Map. Initially the supplied DEM was converted to a TIN for the 3D component for the Local Scene. The suitability parameters included Elevation where areas exceeding 2,500 meters are most favorable, Slope where angles between 30 and 45 degrees rank highest, and Aspect where south and west facing slopes are most preferred.

Following reclassification, respective rasters were generated from the DEM using geoprocessing tools in ArcGIS Pro. These in turn were input into the Weighted Overlay tool where the suitability rate for aspect is 25%, elevation is 40% and slope is 35%.

The output Ski Run Suitability Map. Lighting enhancements include shadowing and adjustment of the sun angle. The Vertical Exaggeration is 2.50.

The next part of the lab further explores TINs with adjustments to symbology between elevation, slope and aspect. The deliverable included the generation of contours and selecting appropriate colors.

Cividis color TIN with 50 meter contours and 250 meter index contours.

The last section of the lab provides a point feature class that will represent the mass points for a TIN. Geoprocessing of these points were input along with a study area soft clip polygon boundary in the Create TIN tool. The resulting TIN was modified symbolically to show contours set at an interval of 100 meters.

The same mass points feature class was input into the Spline tool to create a DEM. Contours were subsequently generated from the DEM with additional geoprocessing. The two contour feature classes were then compared.

While not necessarily more accurate, the DEM based contours have smoother curvature resulting from the implicit data values from each grid cell (Manandhar, 2005). Appearing more jagged in areas with less slope, the TIN based contours are derived from every node, where 3D coordinates are more explicit. There are less Faces (triangles) in flatter areas.

References:

Manandhar, N. (2005). Comparison of TIN and Grid Method of Contour Generation from Spot Height. Nepalese Journal on Geoinformatics, 4, 1-8.

https://www.nepjol.info/index.php/NJG/article/view/51271/38351