Marshall Kirchner's UWF GIS Blog

This week's laboratory assignment covered the inputs, differences, and uses for DEMs (Digital Elevation Models) and TINS (Triangulated Irregular Networks). I often use these two topographical representations in projects and find them to both have their own pros and cons. This particular lab showcased that they are both fairly different and should be used based on what type of data is being shown and how it should be represented. I enjoyed learning about the differences between the two through a variety of spatial tools and analyses. Personalized TIN Symbology My analysis of TINS and DEMs proved to me that TINS are often superior to the standard DEM in many ways. TINS often do not generalize as much as DEMS, and showcase more data in areas that have higher densities of data. For example, the TINS generated contour lines were much more accurate and forming to the terrain present in part D of the assignment. TINS are generated from vector point data that contain x, y, and z coordinate

  Roadway Completeness Comparison This week's laboratory assignment concluded this course's focus on data quality, more specifically in data quality comparison and assessment. I particularly enjoyed this module, as I understand how critical data accuracy is and what it could mean in terms of analysis and change making. Minor differences in data quality could mean all the difference for decisions to be made on a particular matter. For this analysis, two sets of road networks were provided (both located in Jackson County, Oregon). Whilst they appear similar from a distance, there are many important differences that were highlighted in this analysis. From a bigger picture point of view, I determined that the TIGER 2000 road network is more complete, as it has a longer total length than the Street Centerlines network. Utilizing the Calculate Geometry tool, I determined the following total road network lengths:  Street Centerlines = 10,805.8 km TIGER Roads = 11,382.7 km Analysis Ste

Data accuracy is imperative in conducting assessments and making appropriate conclusions on spatial data. I often find throughout my GIS assignments, data can be skewed and unreliable based on how and when it was acquired. Thus, implementing data quality standards is an excellent way to ensure one's data is accurate before creating projects or making analyses. Making accuracy assessments is a great way to determine if one should use certain data and if it will be reliable for particular assignments or projects. I will certainly be comparing data accuracy in future assignments in an effort to ensure my data is reliable and spatially accurate. City of Albuquerque Data StreetMap USA Data Orthophoto Imagery with Digitized Intersections For the purposes of this assignment, I utilized the Positional Accuracy Handbook by Minnesota Planning (1999) to conduct an accuracy assessment. The following steps were taken in performing this assessment: 1. Determine if the test involves horizontal ac