Visualizing Pavement Distress – The Complete Story of Pavement Inspection
Pavement management incorporates data collected utilizing various methods to gain a complete view of how the pavement is performing through its life-cycle. One of the most common practices in pavement inspection is imaging utilizing high-resolution cameras mounted on vehicles outfitted with precision GPS and inertial navigation. This imaging, when combined with laser profiling, constitutes a typical pavement inspection setup utilized by many DOTs as well as Local government agencies.
Pavement Inspections tend to follow a process that in many cases is proprietary and “black box” in nature. This makes it hard for the purchasing agency to see how their roads were inspected and how the resulting pavement condition scores were generated. Our team of Engineers and GIS professionals have worked hard to develop a process to remove the “black box” related pavement inspection and to make it easy and simple to trace inspection results back to their originating distresses from the field.
First, our entire process is geospatial in nature from the get-go. Our van’s location is tracked in six-dimensions in real-time and this information is used to calculate the exact location of pavement cracks in the resulting images. Next, the pavement images are geospatially referenced in 3-d and 1mm-pixel resolution, making it easy to extract low-severity cracks in a true 3-d environment. This process then allows us to create GIS vectors (points, lines and polygons) of each distress for each pavement image and deliver them to our clients as part of the pavement inspection deliverables.
This is a crucial piece to the pavement inspection “story” because it shows the purchasing agency exactly what distresses were identified and measured when creating the pavement condition scores for a section of road. Being able to see these distresses on a map helps to complete the story by providing the ability for a rigorous QA/QC process utilizing some simple GIS tools.
Each Section of road can be colored by the condition score and its range of values. This tells one component of its story. The underlying distress information tells the rest of the story related to “How” a section of road was scored and assigned its inspection score. By having this information at their fingertips, pavement inspection personnel have a GIS-centric and user-friendly tool that allows them to QA/QC pavement inspection data efficiently.