GIS Graduate Seminars: Brandon Klein & Iftin Thompson
Adapting the Densify Sample Network Tool for a Site Suitability Analysis of Automatic Traffic Recorder Locations
Brandon Klein, GIS certificate candidate, Department of Community and Regional Planning
Adviser: Carlton Basmajian, associate professor, community and regional planning
Average Annual Daily Traffic (AADT) is a universal figure used in transportation planning to describe the average amount of daily vehicle traffic that travels on a specific roadway. This study focuses on using this variable to perform a site suitability analysis for automatic traffic recorders (ATRs), machines that continuously count traffic. This analysis will be used to answer the spatial question “what placement of ATRs will best improve the geographic distribution of non-covered roadway segments.” The study area for this analysis will be the rural primary roadway network for the state of Iowa. AADT sample points from current ATR locations will be used as the primary data set in an ordinary kriging spatial interpolation process to represent standard prediction error variability throughout Iowa. Concurrently, a weighted raster surface of Iowa will be created that represents the best possible ATR locations based on road slope, distance to intersections, and road curvature. Both outputs will be input into the Densify Sampling Network tool, which will populate the best candidate locations for new ATR sites based on suitable geographic location and the most impact on the prediction standard error.
Safety Effects of Access Point Density on Urban Areas
Iftin Thompson, GIS certificate candidate, Department of Civil, Construction and Environmental Engineering
Advisor: Peter Savolainen
Access management strategies, such as access point spacing and turning restrictions, are a complex issue and the impacts of such features on traffic crashes and injuries is in need of further research. The purpose of this study was to identify how driveway density, type, and spacing affect the rate of crashes among roadways in high-density development areas. Data was collected from twenty-eight urban and suburban corridors in the state of Iowa, which had collectively experienced significant growth in recent years. ArcGIS was extensively used in order to effectively gather information from each corridor. Methods such as table joins, digitizing, editing attribute tables, and linear referencing was executed. Driveway information was individually collected by digitizing points at each location. Crashes from 2010 to 2014 was gathered from the Iowa DOT crash database, but organized using a series of table joins and editing attribute tables. Other characteristics such as intersection density were also gathered for this study. Linear referencing was best used to determine the distance between each intersection along every corridor. A statistical analysis was conducted to better understand the relationship between driveway density and crash rates.