With so many technologies available for collecting geospatial data, it is increasingly difficult for contracting entities to decide which technology or data source will give them the best possible data for a given project. Understanding that each dataset offers specific benefits, many clients have begun asking for deliverables that are obtained through a combination of different technologies and datasets. This process, commonly referred to as data fusion, is generating a great deal of excitement throughout the entire geospatial industry. However, there are still many questions about data fusion and its use. 

One of the biggest concerns facing the end user is accuracy. Different data collection methods yield different accuracies, depending on the technology that was used during the collection phase. Merging datasets with accuracies that vary from 1 to 10 centimeters can be cumbersome, to say the least. To fully capitalize on the benefits of data fusion and reach a successful outcome, the project team must be capable and must fully understand the advantages and limitations of each data source.

A recent Michigan Department of Transportation (MDOT) project provides a good model for what can be achieved when the right variables are in place. The project involved conducting a full topographic survey of the I-96/US 23 highway interchange in Brighton. One of the busiest interchanges in Michigan, the I-96/US 23 junction consists of several right and left exiting and entering ramps, tightly merging lanes, and a long section of high speed curving expressway with rolling grades. The safety of the motoring public and of the surveyors mapping the roadway was a critical concern. Other issues included time, resources, traffic volume, lane closures and public opinion. The only way to address to these concerns while maintaining the ability to acquire highly accurate survey data was through data fusion using a combination of existing aerial photogrammetry, traditional ground survey methods, and mobile LiDAR using SSI’s Riegl VMX-250 system, known as MoLi.

The ability to use multiple data sources ensured that MDOT received all of the information that was collected while also giving Michigan taxpayers the best return on their tax dollars. Using mobile LiDAR gave the MDOT project team a more thorough and representative dataset, which will help the project team mitigate many unforeseen concerns that may occur throughout the project’s lifecycle. “New tools and technologies have rapidly changed the ways highway corridor projects are being surveyed,” says Kelvin J. Wixtrom with MDOT. “Each new technology provides its own unique advantages for acquiring portions of data better or more efficiently than other methods. Multiple tools generating several datasets are generally required to cover the entire project efficiently, [and] data fusion is becoming necessary in many more projects.”

Watch the video interview above to learn more about how data fusion is changing highway design projects. Look for an in-depth story on the I-96/US 23 interchange project in POB’s August issue.