In preparation for the Huntington traffic sign inventory, DLZ turned to the MUTCD sign standards to devise an attribute collection list in GeoJot. This list directed the field crew member to enter specific pieces of information about each sign, either by pointing and clicking on pick-list items or keying in customized responses. These attributes included the type of sign, its condition, obstructions and other vital details. (See the sidebar on attribute collection.) Survey rods were used to measure sign heights.


At each sign, the field technicians snapped one or more photos with the built-in camera. The iPad captured GPS coordinates of the location, and GeoJot enhanced the native accuracy of these points to the desired 3-meter level. Then the crews gauged the retroreflectivity of each sign using a retroreflectometer from RoadVista of San Diego. These handheld units are about the size of a police radar gun.

“Most signs have two surfaces that must be measured–the background and the legend (or lettering),” says Nelson. “Our field technicians took four measurements from each surface and an average value generated by the retroreflectometer was used for the background and the legend measurements, respectively.”

To measure the retroreflectivity of a surface, the technician placed the instrument directly against the appropriate part of the sign and squeezed the trigger. The device assigned a shot number unique to each sign and recorded the eight retroreflectivity scores under that number. The shot number was keyed into GeoJot as the link between the scores and the other sign data. At the time, the technician was unaware of whether the sign passed or failed and moved onto the next sign.

“We started out using two members in each crew, but later had one person doing the collection,” says Nelson. “Once our crews became proficient, they averaged five to six minutes per sign, including the time needed to walk from one to the next.”

DLZ captured information for 2,500 traffic signs in Huntington over a period of 400 staff hours using the iPad data collection technique, including some office time.


At the end of each day’s mobile data collection, the crews returned to the DLZ Fort Wayne office with their equipment. Although they had an option of wirelessly transmitting photos from the field over the cloud, the crews used the standard iPad connection cord to download the photos and attribute data from GeoJot directly into the GPS-Photo Link software running on a desktop computer. Likewise, the retroflectivity scores were transferred to an Excel file in Microsoft Office on the same computer.

The photo-mapping software gave Nelson and his team the opportunity to review and edit all of the attribute inputs and GPS points. They were able to quickly view the photographs, looking for sun glare and other quality issues that may warrant a retake the next day. GPS-Photo Link charted the progress of the field work by annotating a satellite image of Huntington with icons showing the locations of the photos. The crews used this to methodically move across the city without missing any streets.

DLZ performed a similar editing of the retroreflectivity scores by reviewing the spreadsheet to make sure appropriate measurements had been collected for each sign. The retroreflectometer data was output into an Excel spreadsheet. Nelson then created a temporary sign attribute file, also in Excel, as an output from GPS-Photo Link and used the shot number to merge the scores, making them permanent attributes in the database attached to the appropriate signs in the photo-mapping software.

GPS-Photo Link then output the integrated dataset as a GIS shapefile ready for ingestion as a new data layer in the Huntington GIS. DLZ delivered the shapefile with a digital file folder containing the photos, each stamped with time, date and location coordinates.


Integrating the sign inventory as a layer in the GIS is critical to Huntington’s ability to create a replacement plan, explains Goodnight, because the system can be queried on any of the collected attributes. For example, the public works department can search for all stop signs that failed the retroreflectivity test or that have tree branches obscuring their views. These can be displayed as icons on the GIS map, when personnel click on an icon to see the sign photo and other details.

“We’re going to be able to create lists of items that need to be addressed based on priority,” says Goodnight. “And we will generate work orders with the locations [of signs that need replacement].”

Due to budget limitations, the public works department has not yet decided how it will approach installation of new signs. It may query the system to pick out signs whose backgrounds and lettering failed the retroreflectivity test so it can be changed first. DLZ is working with the city to establish a localized degradation rate for sign backing materials so that they can project when signs will fall below the thresholds. The city will be able to monitor the degradation using its retroreflectometer and adjust the rate, perhaps buying more time and saving resources.

“We’ll get an idea of what the actual cost would be if we replaced all the signs that failed,” says Goodnight. “Then we’ll look at replacement options over a period of five or 10 years.”

Huntington is so impressed with the iPad-based GIS data collection system deployed by DLZ that it has already ordered its own tablets along with the GeoJot app. Initial plans call for equipping the crews with the tablet for use in sign replacement jobs. Beyond that, Huntington has already begun a pilot program with its water department using the tablet and mobile data collection app to inventory other city assets.


 Kevin Corbley is a business consultant working in the geospatial profession. He can be reached at For more information about DLZ Corp., visit The GeoJot+ field data collection system can be found at