What is PAS 128 - Underground utility detection about?
PAS 128 on underground utility detection provides a way to accurately map underground utility networks.
Who is PAS 128 - Underground utility detection for?
PAS 128 on underground utility detection can be adopted by:
- Practitioners (surveyors, geophysicists, subsurface utility engineers)
- Clients (engineers, constructors, project managers)
- Utility owners
Why should you use PAS 128 - Underground utility detection?
Sponsored by the Institute of Civil Engineers, it specifies requirements for the detection, verification, and location of existing and new underground utilities.
PAS 128 on underground utility detection applies to active, abandoned, redundant or unknown underground utilities and the location of their associated surface features.
PAS 128 applies regardless of where these utilities are located (e.g. in urban or rural areas, in the street, on private sites, such as hospitals or airfields). It applies to utilities buried no deeper than three meters.
PAS 128 sets out the accuracy to which the data are captured, the quality expected of those data, and a means by which to assess and indicate the confidence that can be placed in those data.
Specifically, it covers:
- Project planning and scoping process
- Classification system for quality levels based on survey category type, location accuracy, inclusion of post-processing, and level of supporting data
- Desktop utility records search
- Detection
- Verification
- Location
- Deliverables
The benefits of the PAS 128 on underground utility detection are:
- It enables those involved to make informed decisions using more complete, up-to-date, and accurate data. This reduces conflicts, delays, utility service disruptions, redesigns, personal injuries, and even loss of life
- Accurate utility data could also lead to as yet unrealized benefits, such as the use of remote robotic techniques to maintain asset networks in busy highways in the future, reducing the need for intrusive road excavations
- Accurate mapping of utility networks could improve asset modelling capabilities