Linear Referencing

Determining the relationship between pavement conditions and accidents in Pitt County

Problem and Objective

A GIS analyst for Pitt County has been asked to investigate the relationship between pavement conditions and accidents near Greenville, NC. Additionally, the analyst has been asked to help customize the ArcGIS interface to make linear referencing tasks easier to complete.

Analysis Procedures

To address this problem, I used ESRI’s ArcGIS Pro 3.1 and customized the ArcGIS interface with the necessary Linear Referencing tools for completing the task. To determine the relationship between pavement conditions and accidents, the tools Make Route Event Layer and Overlay Route Events were used from the Linear Referencing toolbox.

To efficiently perform linear referencing and answer our study question, I first needed to extend the ArcGIS Pro interface by creating custom tabs and groups. This was done by opening the Customize the Ribbon window and creating a new tab called Linear Referencing Cust. Three new groups were then added to the new tab, Routes, Events and Add-Ins. Then to these groups, I added the appropriate Linear Referencing Tools.

The data for this task was obtained from the GIS 520 course webpage, which was supplied by the Pitt County government. This included two vector files, the county boundary, the cities within Pitt County, two tables with information on pavement and accidents, and a geodatabase containing the route features (roads).

I first added the data to the map frame and examined the data and attribute tables. I then used the Accidents table to make a Route Event layer to display the accidents along the roads. The common identifier field used for the analysis was Route1. I then used Select by Attributes to select only accidents along our focus route. I then performed the same steps with the pavement table, making a route event layer and adding it to the map.

The next task was to determine if there is a connection between pavement conditions and accidents along our focus route. A new field was added to the pavements table called “Seg_Len” to calculate the length of each segment in miles. In the pavement table, the ratings field was examined, and the road quality was considered good if the rating was greater than 75 and poor if the rating was less than or equal to 75. Using Select by Attribute, I determined the length of road that had good and poor road conditions.

Then, using the Overlay Route Events tool, I intersected our focus route with the accidents layer, creating a new layer with just accidents on our focus route. I then selected for accidents on poor and good pavement conditions and noted the results. Using this I calculated the number of accidents per mile on pavement with a good rating and poor rating, and determined there was not a correlation between pavement rating and accidents on this section of road.

 

Results

Application & Reflection

Many types of events are recorded as events along linear features, such as on pipelines, roads or streams. Without linear referencing it would be much more cumbersome to determine locations and would require the feature to be split into many tiny segments which would be confusing and difficult to maintain. One example of linear referencing in conservation is determining the location of events along a river or stream.

Problem description

A hydrologist wants to map a river system that has multiple field monitoring stations along the banks which help to collect information about water quality and flow rate. The hydrologist wants to find a way to easily locate these monitoring stations along a river without segmenting the line feature into multiple smaller segments.

Data needed

A vector map of river features and a table with the location of field monitoring stations along the river banks.

Analysis procedures

After adding the data to the map, the river features would first be converted to linear routes. The table with locations of field monitoring stations would then be converted into a Route Event Layer. This table would have a measure field for each field monitoring station, measuring how far it is from a certain point along the river. Using this measure field, ArcGIS would be able to place the field monitoring stations on the map at the correct location without having their exact coordinates. Then analysis could be run to determine flow rate in ArcGIS.