Module 2.1 - Surfaces - TINs and DEMs

    This week's module involved comparing TIN and DEM elevation modules. TINs (Triangulated Irregular Networks) consist of a network of triangles. They can be good at representing areas where the surface is highly variable. A DEM (Digital Elevation Models) is a graduated raster grid where each cell has an elevation value. They can be easier to process than TINs due to their comparative simplicity. 

    Contour lines can be generated from both of these elevation models. The TIN contour lines were easy to generate as they were found as a check-box in the Symbology pane. The DEM contour lines had to be generated using the Contour tool.

    TIN contour lines are shown in red and black, and the blue contour lines were generated from a DEM. These contour line types can have remarkable differences, depending on the study area and type of analysis performed. In this case, the study area had spots of great elevation changes, and the differences between the two elevation types can be seen there. This module highlights the importance of choosing the right elevation model for the data and analyses required.

Module 1.3 - Data Quality - Assessment

     This week's module focused on accuracy assessment. We were tasked to analyze the completeness of two Oregon road networks, one sourced from Jackson County GIS, and the other sourced from the U.S. Census Bureau's TIGER shapefile. This module defines completeness as the measure of the lack of data and the comprehensiveness of the dataset in representing real-world objects (Haklay, 2010). 

    In order to perform the completeness analysis, I first used the clip tool on the centerline shapefiles in order to remove any road segments outside of the county grid. Then I used the Summarize Within tool to calculate the centerline length totals by grid. This tool allowed for the total lengths to be calculated for road segments contained within their respective grid polygons.

    Positive % difference indicates that the Jackson County GIS dataset had a greater coverage, whereas a negative % difference indicates that the TIGER dataset had the greater road network coverage.

     Afterwards, I used the Table to Excel tool to export the summarized grid features in order to calculate a numerical summary of the results. I used the Calculate Geometry tool to obtain the area of a grid cell.