Linear Referencing

Pavement Conditions and Prevalence of Accidents

Problem:There are many causes of automobile accidents.  One city wants to know if to know if the condition of pavement is responsible for the number of reported automobile accidents.  We use a technique called linear referencing to determine whether or not pavement conditions should be considered in future road maintenance budgetary plans.

Analysis: I used both shape files and database files together to create a map of the number of accidents on a specific route, determining if the condition of the road had any part to play in the number of accidents.   This involved creating point and line events to assist with the analysis. This linear referencing process included using a linear file named Some_Routes that show different routes within Pitt County, NC, shape files that identify city and county boundaries, and finally accident and pavement database files that are used to identify points and segments on different routes.  The accident (point event) and pavement files (segment event) layers were combined together using the overlay route events tool to create a new layer.  We sought to identify the number of accidents specifically on Route1, by analyzing the statistical results from the summary statistics tool to identify the condition of the roads where the accidents occurred, and whether or not the pavement condition affected the number of accidents.  The accident frequency along this specific route was identified using pavement condition and the number of accidents. The results indicate that the road condition does influence the number of accidents.

Results:
Map identifying road segment
where condition influenced
number of accidents

Application and Reflection

Problem Description: Linear referencing can be used in my desired field of work to look at different hiking trails in remote areas, and determining where high levels of visitor dissatisfaction exist.  The data can be collected on site through visitor surveys, and then entered into a database.  Additionally, we can determine what types of trails are in these locations.  We can compare using linear referencing the type of trail, i.e., (location, width, slope, grade, erosion, etc.) to see if there are correlations between these variables.

Data Needed: Data for this analysis would include a database file that contains information as it relates to specific locations and satisfaction with a park setting.  This can be developed through conducting surveys of park users.  Additional data required are layers that include park boundaries and all of the trails within the park.

Analysis Procedures: This process would involve creating a point event layer using the survey results, creating segment events of the different trails, and then overlapping the two layers.  Results would be interpreted by identifying areas with high dissatisfaction by comparing results between trail types and levels of visitor use.