Integrated GIS maps improve data visualizations, spatial analysis, planning, and reporting.
One Visualization Worth 1,000 Pages
Maps have become a staple of our everyday lives. Whether you rely on your car’s GPS or an in-app map on your phone to find nearby restaurants, get directions to a hotel, or track the location of your Uber driver, you can enjoy the convenience of having location data at your fingertips.
Just imagine, then, the critical importance of maps for highway engineers and asset management professionals, who rely on highly complex spatial data to make the right decisions about projects to keep roadways safe, reliable, and in good repair.
As the former Director of Pavement Asset Management at Texas Department of Transportation (TxDOT), where I worked for 20 years, I like to say that a one-page map is worth a thousand pages of a tabular report. In fact, I know from my experience managing the largest state-owned roadway network in the United States—about 200,000 lane miles covering 25 districts and 254 counties in Texas—that maps are vital to a mature pavement management process. Specifically, they are crucial for data visualization, spatial analysis, project planning, and reporting.
Using Integrated GIS Maps: Examples from TxDOT
Just to clarify: When I talk about “maps,” I’m referring to integrated GIS maps that you can generate directly within your pavement management system, without having to import or export any files. TxDOT generates Esri® ArcGIS maps directly within the AgileAssets® Pavement Analyst™ solution, the agency’s system of record.
The maps in this blog post are all great examples of AgileAssets-integrated GIS maps. I’ll use them to illustrate how pavement managers and highway engineers can display, analyze, and communicate location data quickly and easily.
Visualizing Data on the Map
Effective pavement management requires dozens of types of data that fall into two main categories: inventory data—which provides information about the locations, features, and traffic levels of the pavement assets—and condition data, which measures the pavement’s smoothness and surface distress.
Some commonly used types of inventory data include pavement types, traffic classes, number of trucks per day, pavement surface widths, and number of through lanes. These types of data are critical for decision-making and planning processes. I’ll show examples of just a few of these types of data to give you an idea of how maps make them so easily accessible.
Let’s consider the three main pavement types: flexible pavement, jointed concrete pavement (JCP), and continuous reinforced concrete pavement (CRCP).
The pavement type is important because it influences data collection and analysis. An agency needs to collect different categories of data and use different models and decision trees to analyze the data specific to each pavement type.
The map below shows pavement types for TxDOT’s Austin district. You can see that the majority of roads consist of flexible pavements (shown in purple), while CRCP (shown in red) is used for very few major corridors. The map provides a very quick, intuitive display of the pavement types, and in a matter of seconds, you can see exactly where the CRCP pavements are.
Another type of inventory data is traffic classes or the average daily traffic. This data is very important for highway design and is a critical factor in project selections and decisions.
The map below shows different types of traffic classes for the Fort Worth district, which includes Tarrant County toward the east (right-hand side of the map). Tarrant is the biggest county in the district, and almost all its roads carry high traffic, as you can see from the red lines crisscrossing the map. Outside Tarrant County, toward the west (left-hand side of the map), most of the roads carry low to medium traffic (purple and green lines), except for a few corridors.
Again, the map provides a very quick visual display of lots of traffic data—and it’s much easier to read than pages of tables or spreadsheets.
Trucks per Day
Truck traffic is crucial in pavement management because the damage to the pavement from one truck is equivalent to the damage from 10,000 vehicles. The map below shows truck traffic for the San Antonio district.
As you can see, the I-35 corridor carries a lot of truck traffic, as shown on the bright red line running from the lower-left corner to the upper right-hand corner of the map. That’s traffic on an interstate that stretches from Laredo, Texas, near the border with Mexico, all the way north to Minnesota.
Note how convenient it is to see the truck traffic data immediately by looking at the map. We can even drill down to see the exact number of trucks per day for every section, as shown by the many numbers along the routes of the map below.
I’ve given just a few examples of types of data to display. I could give dozens of more examples of inventory and condition data. But even from these few examples, you can already see what a powerful data visualization tool these kinds of integrated maps provide.
The next step is to conduct analysis to determine how to act on the data.
Filtering Data for Spatial Analysis
To analyze data in AgileAssets® Pavement Analyst™, shown throughout this post, you can apply different filters to display specific routes or specific features. For example, I filtered the data in the map below to show only the roadways that have a width less than 24 feet, as you can see from the purple lines.
Different filters can be applied to different values and different criteria. For example, in the map below, I turned on the filter to show only the roads with truck traffic greater than 20%. As a result, the map displays sections in the medium and high traffic classes, shown in green and red. Those are the routes with more than 20% truck traffic.
Once we have filtered the data to show the relevant facets of the network that we need to consider, we can analyze the data and translate it into actionable project plans and stakeholder reports.
Planning and Reporting on Projects
GIS maps are a big part of TxDOT’s rigorous process for generating 4-year pavement management plans. Texas has 25 districts, and every district must present a 4-year plan each year for review by senior TxDOT officials. During the review, district officials use GIS maps to present their plans to a committee of senior administrators.
Each plan includes 4 years of construction projects as well as maintenance projects. The different layers of data can be turned on and off to display different combinations for project planning purposes. For example, you can drill down to display routine maintenance, preventive maintenance, and rehabilitation projects as well as pavement condition and surface age.
On the map below, I’ve turned on the layers to display rehab and preventive maintenance projects for the years 2019 and 2020 in a specific district. The X’s mark the 2019 projects, and the plus signs indicate the 2020 projects.
As you can see, the map is effective at conveying information quickly in a way that is relevant and intuitive for both a tech-savvy and a non-technical audience. As a result, it supports both (technical) project planning and (non-technical) stakeholder reporting.
Below is another example of a 4-year plan in action, where we can see the rehab and preventive maintenance projects for the year 2022, shown by the red dots, and the year 2023, shown by the light orange dots.
There, too, you have a single image that doubles as a powerful, compelling tool for planning and reporting.
Mapping Improves Efficiency
From the TxDOT examples above, you’ve seen that maps are valuable tools for visualizing, analyzing, and communicating data as well as turning it into actionable project plans. But maps also provide more strategic benefits for the organization as a whole.
They improve data accessibility by providing a very quick, easy, and efficient way of sharing information. They also improve organizational communications, because district leaders can use maps to show senior administrative officials and legislators the state of the roads in each district.
Maps also improve cross-team collaboration, because district planning teams can share them with maintenance supervisors to help address immediate maintenance needs in a reactive manner, in addition to using maps proactively to plan upcoming projects. As a centerpiece of the pavement planning process, maps ultimately lead to greater operational efficiency, helping the agency save time and streamline workflows that impact multiple areas of the organization.
Ready to learn more? Register for my webinar, Using Maps to Advance Pavement Management, presented in collaboration with Esri.
About the Author
Magdy Y. Mikhail, Ph.D., P.E., retired as Director of Pavement Asset Management after 20 years of service at Texas Department of Transportation to join AgileAssets at Senior Consultant. A nationally recognized pavement management expert, he chairs the Transportation Research Board (TRB) Standing Committee on Surface Properties and Vehicle Interaction and is a member of TRB’s Standing Committee on Pavement Management Systems.