Between the Poles

An update on the Canadian Underground Infrastructure Register initiative

In this blog last month, Geoff introduced the Canadian Underground Infrastructure Register (CUIR) initiative to his readers and outlined the basic intent and reasoning for the CUIR (rhymes with “cure”) initiative and other similar initiatives underway or already in service in jurisdictions outside of North America. Although the intent of each of these initiatives is essentially the same, to reduce the risk and cost associated with working on or near buried infrastructure by providing better information to the stakeholders, each one has its own set of variables that will impact or have impacted the functional design of the delivered solution.  

This article intends to update the CUIR Team’s progress and to provide details on the proposed process and its similarities with aspects of other current international initiatives including how the data is managed, and how system access and database security concerns are addressed.

The CUIR project started in earnest at the beginning of the year, and we currently have over forty individuals on the team representing various stakeholder groups at the Federal, Provincial, and Municipal levels, non-government organizations, and various industries and service providers. Our primary focus areas are continued stakeholder identification and engagement, research activities related to like initiatives, business requirements gathering, and preliminary architectural and process design work. 

Focus area findings and opportunities

The project team is growing each month, however, we still need to ensure that every group in the stakeholder community is represented. If you work for a firm with underground assets and you are involved in damage prevention or other EHS activities in your company, we would like to hear from you so that we can ensure that your industry group is adequately represented in the project.

As mentioned above, there are like initiatives either underway or deployed in other countries. We are reviewing each of these initiatives with the view of engaging with them to work together to exchange design ideas and functionality, and to support each other by working on elements that are common in nature such as the data exchange agreements, formats, and processes.

For example, the National Underground Asset Register project in the UK, the Cable and Pipeline Information Portal (KLIP) in Flanders (Belgium), and others are using the Open Geospatial Organization’s (OGC) Model for Underground Data Definition and Integration (MUDDI) as the basis for the integration of datasets from different models. The OGC MUDDI is the model that we propose to use for the exchange of data in the CUIR initiative.

We intend to provide registered users the asset location information, but due to data security concerns, we will not be providing users access to a separate database or access to a system of record. Very much like the Belgian KLIP initiative, we will employ a process where the registered user draws the area of interest on a map to initiate the information request. Below is an excerpt from the article “Nobody Knows What Lies Beneath New York City” written by Bloomberg’s Greg Milner, and provided to us by Alan Leidner currently working on the New York University’s Underground Resilience Measures (UNUM) project in New York City.  

Not just anyone can gain access to the Belgian map. A contractor who wishes to dig underground must submit the coordinates of the work area via a computer portal called KLIP. The request goes out to all stakeholders with infrastructure running beneath the area, which is required to turn over their data. The information is then synthesized and sent to the requester as a single document. 

“We have a decentralized architecture concept,” says Jef Daems, a KLIP official. “All network utility companies have their master database, and it is only a very small part of the network that is provided to the contractor.”

State and Provincial One Call Centers

We are hoping to engage with the One Call Centers and have them become the backbone of the system and employ their “Click before you dig” process to create a ticket showing a polygon of the area of interest and when each affected member receives the notification, they would use the extents of the polygon as a spatial filter to identify the infrastructure, if any, that they have in the area identified in the ticket.  As each utility owner sends the requested data, much like the NUAR and KLIP systems, the information from each asset owner would be imported as a layer and conflated onto a common base map that the requestor can then view by selecting the One Call ticket on a computer or mobile device as a set of layers that can be switched on or off. 

For Designers, using this information will provide them with a basic appreciation of the location of existing buried infrastructure to help them make better design decisions. Capturing accurate infrastructure location data to ASCE 38:22 Standards during subsequent pre-construction site investigation in support of the design work and providing it back to the asset owners will provide Owner’s a great opportunity to improve the accuracy of their records at virtually no cost.

For Locate Service Providers, receiving a locate request containing a showing the extent of the excavation site, and the location of each utility by the owner will allow them to ensure that during the mark-outs using stakes or paint, nothing is missed. By capturing the precise location of each infrastructure item electronically using GPS, the locate technician will also be able to provide an “as-found” file back to each asset owner to improve the accuracy of their records at little to no additional cost. 

In both of the above scenarios, the information captured electronically prior to the start of construction can be made available to the contractor as a map showing the work site and an overlay of the various layers depicting the existing utilities. The provision of an electronic map to the contractor showing the location of each facility on the work site will improve the situational awareness and safety of personnel.  As Geoff mentioned in a post last August, a contractor on a Colorado DOT Highways project estimated that the ability of their excavation crews to see an electronic map showing the accurate location and nature of buried facilities on a job site has translated into an over 90% reduction in the number of lines strikes, cost of damages, schedule delays, and risk of injury to personnel. Every project that involves soil disturbance not only presents an element of risk for excavators, but also provides an opportunity for asset owners to benefit from that work in the form of data gathered that can be utilized to improve the records in their database.

We continue to reach out to other like initiatives underway to engage with them and see if there are opportunities to collaborate to learn from, and support, each other.

 

Submitted by: SteveSlusarenko,Process Design Consultant

"I am working with some like-minded individuals that are proposing a major improvement to the damage prevention process here in Canada. Our intent is to virtually eliminate line strikes on buried infrastructure during any type of excavation or other ground breaking activity.

 

Eliminating the as-built backlog by automating field utility data capture

The as-built update backlog is the time it takes for as-builts submitted from the field after completion of construction for newly installed network equipment to get entered into your utility GIS.  It is generally measured in months which is appalling today when we have real-time or near real-time data about so many aspects of the real world from traffic to weather.

Field sourcing

The key to solving this problem is to enable crowdsourcing of updates from the people who actually do the construction, the field workers, so construction crews can make those updates where and when the work happens. In order to do that, we really need data capture tools that are much faster and simpler, in other words, more automated than today's solutions.

There are a number of enabling technologies that can change the way that we approach this problem; computer vision, machine learning, augmented reality, voice interaction, and reality capture can all play a role. A lot of these things are being driven by other industries outside the geospatial technology industry. Part of the challenge in bringing together a solution for the as-builting process is looking broadly at these different types of technologies and where they're applied and bringing them together into a solution for utilities. You need to enable the people doing the construction to capture accurate location and attribute data quickly and efficiently. Anyone should be able to use the system with minimal or no training and it should use inexpensive commodity equipment.

Automating feature recognition

As an example, we're in a new subdivision construction site and we're going to do some as-built data capture of some electric equipment using an iPad. We point our mobile device at a piece of utility equipment and the application automates the process of detecting what the equipment is. The user just taps the screen to add the feature, an electrical pedestal. Next, we point our mobile device at the neighbouring electric meter. And again, it's automatically recognized and we tap to confirm that we want to add it.  We can then scan the meter to add more detailed attributes according to rules that we've set up.

Now we want to add a cable. If the trench was still open so the cable was visible, we could automatically recognize it like we did with the other features, but since it's hidden, we select it from a list and then just tap to add points along the path of the cable. As we walk, you can see the cumulative distance of the cable path being shown at the top. Lastly, we'll add an electric cabinet in the same way and scan its attributes, including the transformer number and manufacturer on the front side. Then the KVA from the yellow 50 on the side. We zoom in more closely to get additional attributes like the serial number, work order number from the smaller label.

Once we have completed scanning the various objects, the data gets pushed automatically to the GIS with no user intervention needed. We can see the features that we just captured on a map with their attributes plus photos. The newly captured data about the equipment is immediately available in any GIS client. For example, we can see the newly captured equipment data on a handheld mobile device or it can be viewed on any web browser. The data can then be pushed on from the GIS to real-time systems like an ADMs outage management system or network management system.

The app is able to automatically recognize features and attributes using machine learning based image recognition, to tell what type of feature it is, read barcodes and QR codes, and use text recognition to capture detailed attributes. The additional attribute information also reinforces the feature recognition in some cases. YYou can also use voice recognition as a backup if there's a scenario where you have to correct something that was misrecognized or something that can't be identified correctly.

Lastly is an example of capturing very detailed attributes quickly. We captured 22 attributes in just over a second from an electric meter.

Location accuracy

Location accuracy is particularly important for underground assets. AR gives much greater relative accuracy than consumer GPS and phones do. It measures accurate distances and angles in 3D for recording of relative asset layout. In a range of tests we found AR is accurate to about 1%. As a simple example. we measured a 10 foot distance next to a tape measure. We've added a virtual pipe and you can see the measured distance in the augmented reality app is 10 inches and it's within an inch of the 10 foot mark or within about 1%. Tests of up to about 100 feet have found the same 1% accuracy. AR provides much better accuracy than you could get with anything except the very highest precision GPS.

Visual positioning system

Apple's GeoAnchors is their implementation of the AR Cloud. The idea is that as you're moving your mobile phone around among 3D objects captured in a street view scene, it uses the camera view to match what the camera is seeing against the highly accurate street view type imagery, which Apple calls look around imagery and that refines the position.

Conclusion

Field sourcing of data is key.. You need to enable the people doing the construction to capture the data, and these new technologies really open up some very exciting new ways that we can provide systems to the construction workers to enable them to capture accurate location data. We foresee that visual positioning systems are very likely going to supersede high precision GPS in a lot of scenarios.

This post is based on Peter Batty's (SSP Innovations) talk at the Subsurface Utility Mapping Strategy Forum (SUMSF).

ASCE standards reduce risk and expedite public highway construction projects

What the engineer does during planning and design has a multitude of impacts: traffic disruptions to the public, safety for workers on construction sites, avoiding delays and budget overruns on projects, decreasing risk to contractors, and reducing cost to the rate paying public. It really is a matter of public welfare and that's why the ASCE 38 and 75 standards are engineering standards. What we'd like to do is enter into a world where we we have as reliable information about the subsurface as we do about the above ground and the location of underground infrastructure is well understood in the design stages.  Then we can start applying modern 3D BIM design technologies, virtual design, and new other technologies to enable the construction process to proceed as rapidly as possible with the least amount of risk and rework. And that's going to save everyone money and a lot of headaches.

Regulating the public ROW

With respect to underground utilities the key idea is to avoid, accommodate and then relocate. This will require changing the mindset of agencies such as DOTs that should be regulating work in the public right of way. Currently many DOTs allow the utility operators free rein to build and operate in the ROW. They take a hands off approach saying it is not their responsibility, it's the utilities operators/owners problem. At this point it is generally recognized that this approach no longer works because everybody is accountable when things go wrong and a gas main gets broken and a building explodes. If we can accurately locate, map and accommodate underground infrastructure during planning and design, just as we do using above ground surveys, we expedite the project by taking the risk arising from underground utilities out of the critical path. By speeding up these jobs you can really save a lot of money on major construction projects.

ASCE 38-22 for SUE Surveys

In contrast to the 38-02, the latest version of the 38-22 standard for SUE investigations is both prescriptive and a performance standard. It is prescriptive in that it specifies the minimum actions that must be undertaken to achieve (or attempt to achieve) a particular quality level. As a performance standard it describes the professional judgment that needs to be exercised to determine the appropriate timing, sequencing, location and scope of a utility investigative effort to achieve the goal of reducing utility issues during planning and design by achieving Quality Level B or A for all underground utilities. ASCE 38-22, unlike 38-02, specifies levels of positional accuracy. 

We wanted to provide better definitions so that there's greater clarity in what constitutes a SUE survey.  The SUE survey must be stamped by a professional engineer and In addition be accompanied by an engineering report that goes with the submittals to help lay out what has been found, where issues and discrepancies were encountered, and the things you need to be especially careful about. It includes our recommendations going forward on the project, what you need to consider and  where you may need to do more advanced geophysical investigations or vacuum excavations to better define the design, where you need coordinate closely with utility owners, how to prepare construction documents and plan construction. The liabilities behind this document is significant. To protect the owner, the contractor, and the engineer whoever has provided the SUE data and service must be able to document what they did sufficiently to be able to stand up in a court of law and say, "We met the standard of care."

ASCE 75-22 As-installed

We define the spatial and the attribution properties of the facilities that we want to record, so that at the end of the day, we can actually create a digital twin in a user friendly format and consistent format. We have defined minimum, optional and conditional attributes and the minimum requirements, list the information we must have to create a digital twin or very useful 3D model of our infrastructure in a standardized manner.

In Montana we have a permitting system for work in the public ROW and we can collect these attributes and an approximate alignment at the time of applying for the permit. The person filling out the permit application understands the required attributes and can plug them right in. And then when the actual work is performed, the approximate alignment's upgraded to the actual observation via the survey data. ASCE 75 has been implemented in Montana for several years now and has won both Montana and national engineering awards.

We also support absolute spatial positioning and have have a framework for data exchange by having a standard datum. At the National Oceanic Atmospheric Administration (NOAA), this is the same thing we do for nautical charts and hazards to navigation. We're just applying it to hazards to excavation. Everything is referenced to the National Spatial Referencing System. That gets rid of all the distortion that happens when you're trying to take something on a sphere and flatten it on a flat plane. You get distortions, there's different projections, state plane, county coordinates, UTM and they all distort the image. By having everything referenced to the National Spatial Referencing System, when you bring it together, it's going to go in the same spot every time. And it accounts even for plate tectonics and crustal drift ln places like California, Whenever you're turned on your GNSS system, you're tied into the National Spatial Reference System. It is being upgraded and the next version should come out in another year.

ASCE 75 specifies levels of positional accuracy. There's an accuracy table that goes with the standard, which we basically piggybacked off CSA S-250, the Canadian standard. We have CSA S-250 people on  our 75 standards committee. They also told us three things that they wish they had included with CSA S-250; make it a digital standard, secondly make it 3D and thirdly include above ground infrastructure with the standard. So we made sure we brought those into ASCE 75-22.

The Open Geospatial Consortium (OGC) has adopted both ASCE 38 and 75 as important input to their Model for Underground Data Definition Initiative (MUDDI ). The MUDDI model provides a base conceptual data model for interoperability and data exchange.  It is being adopted world wide including by the NUAR initiative in the UK, the UNUM project in New ,and other jurisdictions.

Securing sensitive information

Data stewardship includes issues of sensitive and secure information.  Here in the U.S, we're using 49 CFR Part 1520, which talks about how to manage sensitive secure information that TSA has determined to be Sensitive Security Information, as defined in § 1520.5. (This part does not apply to the maintenance, safeguarding, or disclosure of classified national security information.) It's a big issue with many utility owners. They don't want that information available to everyone. The 49 CFR Part 1520 guidance defines what information needs to be kept secure and that has helped alleviate the data protection concerns of the utility owners.

Conclusion

With the imminent availability of the ASCE 38-22 and 75-22 standards, every underground utility segment that's depicted can be assigned Quality Levels based on ASCE 38-22 for existing infrastructure or from the ASCE 75-22 "As-installed" standard for newly installed infrastructure. For example, in Colorado both draft standards are mandated for all work in the public ROW. This enables a world where we we have as reliable information about the subsurface as we do about the above ground and the location of underground infrastructure is well understood in the design stages. Then we can start applying modern design technologies to produce better designs which enable the construction process to proceed as rapidly as possible with the least amount of risk and rework.

This post is based on Phil Meis' (UMS and ASCE) talk at the Subsurface Utility Mapping Strategy Forum (SUMSF).

Combining traditional data with advanced GPR provides a complete picture of the subsurface

When we look at some of the major projects that have gone sideways, it often can be attributed to the lack of planning for underground infrastructure. This is a global issue and we know that the best way to manage the risk from underground infrastructure is to map it before construction begins. For example, the Sydney light rail project in Australia was problematic with a serious budget overrun because there was so many underground unknowns discovered during construction. Another example is a hospital project where what was thought to be a complete inventory of underground utilities missed a 20 inch gas pipe and a six inch gas pipe that were encountered on the project site during construction.  Neither was documented and they were not on the asset owner's records. The challenge is to find these assets before construction in the early stages of planning and design so as to be able to mitigate any project impacts and safety concerns. Very few major projects move forward without an environmental investigation and a geotechnical investigation, so it's not clear why there's resistance to doing a subsurface utility investigation when the immediate risk to the project and the public is considerably higher.

Legacy data

Legacy data is often proprietary asset owners' "as-planned" engineering records. Relying solely on these legacy utility asset records for location information is unreliable, but augmented by GPR and other remote sensing data they provide valuable information.

Modern GIS also cannot be relied on to always provide reliable data. This image is from a GIS with an xref in the background. The middle of the street is where the asset owner believes the water line to be, but a subsurface survey actually found lines on the top and the bottom side of the street, which is nowhere near the placement according to the asset owner's records.

Even more disconcerting is that some asset owners have stopped updating their records. In one example we encountered, the last update and revision to a telecom owner's documents was in 1998. Obviously by 2022, we know there's a lot more utilities added into these streets.

The challenge for practitioners is how to find this information.  Fortunately, advanced technologies, such as multi-channel, multi frequency ground penetrating radar, can augment the available legacy and EM data to provide a complete, accurate and current picture of the subsurface.

Underground locating combining traditional and advanced techniques

At DGT Associates our typical workflow starts with collecting and compiling legacy maps.  We collect all legacy data that is relevant including client information and all the asset owners' maps. We add our institutional knowledge from decades of experience with construction in the particular region where we're working. We then perform our traditional EM pipe locating and add that data to the legacy data we have compiled. Together this provides the background for our ground penetrating radar scanning.

Advanced ground penetrating radar

This is a picture of DGT Associates' new ground penetrating radar setup, a drivable rig with a mobile mapping unit. This is a 24 channel system, so it captures 24 slices every time we scan. It is also a multi frequency system. Low frequencies penetrate deeper with less resolution, while higher frequencies have better resolution but don't penetrate as deeply. This system can collect about 10 miles of data per day with 24 channels for a total of 240 miles of GPR data.  With Boston's soil conditions this system is collecting vertical slices down to about 8 feet. In addition with multiple frequencies we are simultaneously collecting horizontal slices. 

Value of GPR in subsurface surveys

GPR is not magic and is not replacing any of the previous techniques. What is the value of including advanced GPR in locating and mapping subsurface utilities ? The first thing is safety. With our rig we do not require boots on the pavement.  Secondly we get fast data collection compared to traditional locating. Thirdly, we can determine depths with GPR really well. When we see the top of the pipe, we're able to trace it in the cross section. GPR is also good at confirming the location of facilities shown on legacy maps or detected by EM. But GPR can't see everything, For example, we often can see a trench where there is likely a utility even if we can't see the actual pipe or cable. We typically need to determine from other techniques, legacy drawings or EM scanning, what type of utility we are seeing. 

A major strength of GPR is finding unknowns. Going through the depth slices, we can see each one of the lines representing a utility. The type of utility is derived from legacy and EM maps and is colour coded according to the standard with blue being water, orange telecom, purple unknown, and so on. Something that's really striking in this GPR scan is the purple utility buried only a foot and a half deep, crossing diagonally across the street. Nobody knew about this utility before we went out and scanned it with the GPR.

GPR data showing rectangular pits

One of the best examples of how combining GPR with legacy data enables us to detect unknown utilities, determine what they are and confirm they are still present is in Cambridge. We had compiled comprehensive legacy background information before we went out to do a complete GPR scan of the site.  Among the things we found were these unique rectangular pits, shown as purple circles (colour coded for unknown). Each pit is about one foot by two feet wide, and they're regularly spaced at 12 feet. If all we had was the GPR data, we would have no idea what these were.

Background legacy data revealing abandoned gas pipe

But because we had the legacy background maps, we were able to see that these pits line up  with old legacy data showing an abandoned gas pipe. Without the background map, we would have had no idea what the GPR scan was showing. The GPR scan confirmed the location of the abandoned gas pipe and showed that it was still there.

A typical subsurface survey deliverable is colour coded according to American Public Works colour coding. All of the lines are annotated to conform to the ASCE 38-02 quality standard. Every line is represented not only by its annotations for reliability, but also includes the number of conduits and other measures of capacity, and asset owner information. Together it provides as complete a picture of the underground assets for the project site as can be assembled from existing data.

Conclusion

The light rail in Sydney went from a $2 billion to a $3 billion job because of the lack of a comprehensive subsurface survey during planning and early design. There's plenty of proof including ROI studies that there are very good reasons to use SUE surveys. There are good practitioners all over the world who can carry out subsurface surveys. Just as with above ground surveys knowing accurately the location of underground utilities and other infrastructure enables good designs because you can make informed decisions based on information collected by professionals who know what is underground and where it is.

What we see in the coming years is that subsurface surveying is going to become even a bigger business and it's going to become more lucrative. We expect to see more practitioners and more investment in innovative technologies for detecting and mapping underground utilities.

This post is based on Mitchell Lidell's & Michael Twohig's (DGT Associates) talk at the Subsurface Utility Mapping Strategy Forum (SUMSF).

Accurately locating and mapping utility infrastructure underwater

In New Jersey there was a $320 million project to replace a bridge connecting Stafford Township to Long Beach Island. There are many utilities involved including telecom, Comcast, water and sewer, and electric and conduits. They have carried out a SUE survey prior to construction to try to determine where the utilities are and have also come up with mitigation plans to reduce risk. 

However there was a complication. They need to build a new drain line because there has been increased flooding during the rainy season and also because of high tides. It is planned to build the drain line into the water parallel and fairly close to an existing water main. But the water main that provides water to the island runs under water and all they had for locating the water line was an "as-planned" map from the water company engineering department, which is not reliable data. Cross-boring into the water main would leave the whole island without water. Traditional locating equipment, such EMI and GPR, cannot be used under water so an alternative locating technology was required. 

PRISUM Technologies provides a technology called inertial navigation technology, gyro mapping or inertial measuring unit (IMU) that relies on a battery powered autonomous probe with on-board gyroscopes, accelerometers, and odometers. The mapping tool records changes in direction and speed at a hundred samples per second (every foot) to create an accurate, high frequency 3D profile of the pipe segment being traversed. Inertial mapping avoids the major limitations of surface-based EM and GPR techniques; it is not sensitive to soil conditions and extraneous electromagnetic noise, is water resistant, works with all types of pipe materials and is safe because it does not require boots on the pavement. It can map sewer and water mains, electric power or telecom conduits, gas and oil of any material, plastic or metal.  Pipe diameter can range from an inch and a quarter to 30 inches. The key to the technology is that the IMU is completely autonomous. There is no tethered cable and it does not communicate a signal to above ground equipment. All the data is stored within itself.  Basically it is comprised of a battery, memory and various inertial devices such as accelerometers and odometers in a compact device that can be pulled or pushed through a pipe or conduit. Once the IMU tool has been run through the pipe or duct, it is removed from the pipe and connected to a laptop to download and process the data.  The output is a report and a CSV file or a standard GIS format such as a shape file. Because of its autonomous nature, it can map utilities which are going under rivers or other obstructions, even a hundred feet or deeper. The IMU tool has the capability to map up to 5,000 feet recording X,Y and depth every one foot.  To georeference the collected data, accurate GPS coordinates are recorded at the insertion point and and at the end point.  With that information the entire path the autonomous unit travelled can be determined. 

In New Jersey the IMU was inserted in one end of the water pipe and pushed through to the other end and then pulled back.  This was repeated providing four runs. The data from the four runs showed a high degree of repeatability providing confidence in the accuracy of the data. According to the New Jersey DOT, the locating standard tolerance is plus or minus 2.74 feet horizontal and 1.09 feet in depth. The 3D mapping data collected by the IMU was much more accurate, 0.26 ft in XY, and 0.3 ft in Z.

This project entailed a one day activity where we were able to both run the IMU tool through the water main collecting data and also process and show the results to the New Jersey DOT on the same day. The overall operation time for the IMU run was two hours.

It was found that the water main actually had been installed at an angle.  If the team had not had the accurate location from the gyro mapping run, shown by the the red line, they would have risked cross-boring into the water main with major consequences for the project and the island's water supply. With the accurate location of the water main in hand, the team went back to the drawing board and redesigned the new drain line ensuring a safe separation from the water main.

This post is based on Santosh Saride's talk at the Subsurface Utility Mapping Strategy Forum (SUMSF).

Developing a subsurface digital twin for Singapore requires data quality management

Singapore has severely limited land, but unlimited space and has started to build many types of activities underground to save the land above ground for the better living of citizens. Many of the traditional utilities such as electric power, water, wastewater and others, as well new type of utilities, such as the Pneumatic Waste Conveyance System are almost one hundred percent underground. Parts of the transportation network, such as the metro, are also underground.  In addition some storage, waste disposal and national defence facilities are underground.

Data quality

As underground development expands in Singapore reliable data about the location of underground infrastructure becomes increasingly essential. Data quality is a huge issue. Virtually all stakeholders are aware that much of the available information is unreliable and that this has repeatedly led to losses of time, money and opportunities.  From the perspective of planning and land administration, infrastructure development, and planning and design there are important benefits in the form of reduced uncertainty and risks to be derived from reliable underground data.  These include reduced costs, avoiding unnecessary rework, minimizing destruction to the environment, avoiding disruption of consumer services, and greater safety for people working in the environment as well as the general public in general.

To address this issue the Digital Underground (DU) initiative was started in 2017. The objective of DU is to develop a reliable map of Singapore's subsurface infrastructure for planning and land administration. The DU has four phases. The objective of Phase 1 was to identify the problem and create a road map. The second phase involved looking into what was required to create a utility mapping ecosystem. The current phase involves looking at the underground utility workflow which has many components that will contribute towards reliable data.  The final phase is the operational phase when we implement a new utility mapping ecosystem.

In Phase 1 an assessment was made of the reliability (locational accuracy, completeness, and currency) of the existing data. It was concluded that the data quality of the data is seriously deficient. In terms of location, it is  inaccurate, much of it is out of date, and it is also incomplete. It was also found that the quality level of the data is undefined, in other words, no quality level has been assigned to each facility for example based on a quality standard like ASCE 38 or PAS 128. We do not know which piece of data is of higher quality or which piece of data is sufficiently reliable to be relied on for planning and land administration.

Road map for improving data quality

Addressing data quality involves fundamental survey, locating and mapping issues. In addition to assessing data quality an objective of Phase 1 was to develop a road map for addressing the data quality issue. First we wanted to ensure that going forward data for all newly installed utilities would be reliable. In 2017 we implemented a strategy requiring certified survey quality as-builts. Secondly, we started to look for opportunities to improve the data quality of existing below ground infrastructure. We are looking at several new technologies, such as ground penetrating radar and gyro mapping for detecting underground utilities and LiDAR and photogrammetric capture with a smart phone of trial trenches. We are also exploring ways of capturing not just vector data, but integrating 3D point cloud data of an open trial trench in our GIS so the next person interested in this section of road doesn't have to open up the trench to see what's there.

A key part of the road map is governance, especially accountability and transparency; assigning responsibilities for data capture, data quality improvement, and data quality management. We want to introduce a new framework so that we can ensure high quality utility data ongoing in the future. We are suggesting a process that would not interrupt or change the current utility workflow, but add a new data quality workflow on top of the current workflow. Asset owners will be able to continue to do their work the way they have in the past, but will be required to submit their data to a Data Quality Hub for quality control to ensure that data quality standards are complied with. We intend to implement quality control on the front end when data is submitted to the database, not at the tail end of the information supply chain. Eventually this process is intended to ensure that we are getting reliable and high quality data that can be shared back again to the end user, the planners and land administrators.

Community of practice

Creating a utility mapping ecosystem requires buy in from network owners, transportation agencies, excavators, and others. The Digital Underground Connect is a platform where we provide people to meet, to learn and to improve.

 

This post is based on Victor Khoo's talk on the Singapore Digital Underground Project at the Subsurface Utility Mapping Strategy Forum (SUMSF).

Key initiatives of importance to the global geospatial+AEC subsurface digital twin community

Two initiatives of importance to the global geospatial community will begin this June.

Expanding Responsibility for the BetweenThePoles blog

First of all we are expanding the BetweenThePoles blog from a single content provider (Geoff Zeiss) to an industry collective that will be able to mine many more geospatial industry players. Geoff is stepping down from day to day responsibility for the blog (he doesn't like the word retiring) and ownership and administration will transition to GoGeomatics Canada, advised by a collective of industry leaders in the geospatial+AEC sector.

The content and aims of BetweenThePoles will remain the same. The blog encompasses the application of geospatial technology in architecture, engineering, and construction (AEC) and utilities. Primary focus areas are worldwide legislation, governance, regulations, and new technologies for mapping underground utilities and enabling subsurface digital twins, CAD+GIS and BIM+geospatial integration to enable full lifecycle construction, and innovative technologies for vegetation management for electric power utilities.

By way of background the BetweenThePoles blog was initiated in 2006 by Geoff Zeiss. Since then the blog has hosted over 2,500 posts and received over 1.3 million lifetime page views. Currently 3,500 active users access the blog each month. The blog will be continued with its current focus; mapping underground infrastructure,  BIM+geospatial integration, and innovations in vegetation management for utility transmission and distribution.

Making Subsurface Utility Mapping Strategy Forum (SUMSF) and Annual Event

The second initiative follows on the very successful Subsurface Utility Mapping Strategy Forum (SUMSF 2022), which was a follow-up event to the Canadian Underground Forum in 2021.

The genesis of SUMSF is found within Canada’s National Geospatial Conference, GeoIgnite. In 2021 Jonathan Murphy and Geoff Zeiss came together over the idea to create a leadership and technology forum on the theme of underground infrastructure mapping. With the help and financial support of the global underground mapping industry the Canadian Underground Forum (CUF 2020) was held virtually in 2021. From this success, a new and larger stand-alone event with a new global brand and perspective was launched in 2022, the Subsurface Utility Mapping Strategy Forum (SUMSF 2022). 

SUMSF 2022 was held virtually March 22nd and 23rd 2022 again with the support of the underground mapping industry. SUMSF was themed to bring together individuals and organizations to share information about and contribute to improving the mapping of underground infrastructure. This online conference brought together exceptional speakers in the underground locating and mapping sector and was well attended by the geospatial and engineering community.

Based on the success of these two events GoGeomatics Canada has decided to make the conference an annual event. Next year, SUMSF will be held virtually March 6th and 7th. SUMSF is hosted and presented by GoGeomatics. Like BetweenThePoles blog, it will be advised and supported by industry leaders with the support of the SUMSF LinkedIn Group. 

BetweenThePoles will remain an important platform for communication and engagement on the the application of geospatial technology.  

Anyone interested in joining the collective for the BetweenThePoles blog are encouraged to contact Jonathan Murphy at GoGeomatics Canada. As well anyone interested in joining the advisory committee for SUMSF 2023 is encouraged to do the same.

Geoff Zeiss

Standards-based subsurface data model key objective of New York's underground infrastructure resilience project

Improving disaster resilience requires accurate data about subsurface utility and other infrastructure. New York has has experienced several disasters over recent decades, foremost among them 9/11 and Hurricane Sandy. The experience of 9/11 and Hurricane Sandy showed that communities interested in addressing utility resilience currently have little access to underground infrastructure information, which is typically siloed in network owners/operators' proprietary systems, is rarely integrated with other data sets, and is inaccessible to the excavators, disaster planners, emergency responders and others who need it. The UNUM project, funded by the National Science Foundation, is designed to address the challenge of creating a single accessible map of all of New York's underground infrastructure to support emergencies and disasters such as 9/11 and Hurricane Sandy.

Underground infrastructure mapping in NYC

Over the past decades the City of New York has initiated several projects involving underground utility networks. The first project was the conversion of citywide paper maps of water mains into CAD format. The water supply map was near completion when the city began the development of the citywide base map in a GIS. The base map provided locationally accurate platform, including block, lot, street, buildings and photogrammetric imagery of the entire city. Since then most agencies have contributed their data to the base map project which is virtually all open and publicly available. The city's sewer paper maps were entered into the GIS and the water main maps were converted from CAD to GIS.  Both sewer and water main maps were integrated with the city base map, demonstrating the ability to use city's cadastral map data for underground mapping as well.

9/11 emergency

Within hours of the World Trade Center attack, an interim site was equipped to response to the emergency. The Emergency Mapping and Data Center was set up to respond to map requests. The map grid of the site was developed by the Fire Department of New York to enable first responders to navigate the site safely. In addition, maps were developed to advise citizens of street closing and outages of utilities. Maps were submitted to the media and newspapers with daily updates of these conditions for citizens. Thousands of maps were created and distributed within a six week period.The operation was nonstop for more than 18 hours a day for three months. The Deep Infrastructure Group (DIG) team digitized data of the World Trade Center site provided by infrastructure agencies and utilities. The digitized maps enabled first responders to navigate the site safely.  The combination of photogrammetry and LiDAR, revealed the location of fires burning underground. Freon becomes a poisonous gas when heated and locating the underground tanks enabled safe removal of the freon and the tanks themselves, preventing loss of life of workers on the site and residents in surrounding areas. This is a classic example of the value of knowing the location of  underground infrastructure.

The 9/11 emergency clearly demonstrated the value of compiling an integrated data set with a common base map that can be shared easily and quickly among all players. But the 9/11 experience also revealed the difficulty in achieving an integrated map with the currently available data sets and integration tools and was a primary motivation setting the directions for the UNUM project.

Unification for Underground Resilience Measures (UNUM)

To directly address the challenges experienced during these events the Unification for Underground Resilience Measures (UNUM) project was initiated to investigate subsurface data development, integration and interoperability options. Overcoming these barriers to data integration requires the design of an integrated 3D data system with robust security and data protection that is capable of integrating data from different network owners, municipal and other sources based on a standardized subsurface data model and a willingness to share data securely among all stakeholders.  One of the key goals of the the project is the development of a detailed road map for the implementation of a standards-based subsurface data model capable of integrating all of NYC's subsurface data from multiple sources into a single map.

UNUM involves two pilots in NYC neighbourhoods: Sunset Park, Brooklyn and the Grand Central Business Improvement District. These community test beds will be used to refine an infrastructure data integration strategy and to assess the vulnerabilities of utility infrastructure. The New York City pilot area are far apart in terms of demographics, diversity of their populations and their economic bases. They also differ widely in the types of underground infrastructure problems they have experienced.

Use cases addressed by UNUM

The UNUM project, which is supported by a National Science Foundation (NSF) grant, addresses emergencies and disasters that are related to underground infrastructure. Emergencies are typically characterized as localized incidents with limited damages while disasters are more wide ranging, cover a lot of area, cause a large amount of very expensive destruction. NYC has experienced two disasters in the last two decades: 9/11 and Hurricane Sandy.

There are many use cases that involve underground infrastructure. The UNUM project is focused on just two uses cases; emergency response and disaster planning and response. Other projects in NYC target other cases including excavations, excavations for new foundations, maintenance, smart cities, digital twin, and so forth.  For UNUM's use cases the data focus is on the subsurface utility networks, their features and attributes and their relationships to one another.

Quality and availability of subsurface infrastructure data in NYC

Over the past years extensive research has been carried out to determine what data is available in NYC and who is responsible for each data set.  It has been found that there is actually a fair amount of data. New York City itself, which manages the water and sewer utility systems, has very good data which is open and publicly available. In contrast for private utilities such as Con Edison, National grid and Verizon, knowledge about the structure, depth, and reliability (completeness, currency, and accuracy) of their data is uncertain because other than the through the 811 Street Markup (one call) system, there's very little sharing of this data. In general most of the underground utility and communications network data in NYC is within silos that are rarely, if ever, integrated into a single data set and are inaccessible outside of the networks owners themselves.

Single integrated map

The  The vision which motivated UNUM is a single integrated data set that can show all the different utility layers reliably (accurate, up to date, and complete) in 3D, together with other related GIS layers, registered to a common base map and georeferenced to a common, horizontal and vertical datum. This would reveal conflicts, interdependencies, and risks for cascading effects for NYC's utility network. Subsurface utility engineering (SUE) surveys are becoming more commonplace and data like this is becoming available for individual construction projects. This data is being captured in a GIS and compiled entire networks making it possible to see how different networks (electric, gas, water, sewer, steam, fibre,copper, etc) relate to one another.  Especially important are interdependencies such as telecom systems that require power, pumped water and wastewater systems, and virtually all utility systems that rely on digital communications because of the potential for catastrophic failure involving multiple networks.

An open standards-based model for underground infrastructure

To achieve the vision of a single map of New York's underground infrastructure will require developing a data model that encompasses all of NYC's underground infrastructure and that could form the basis for a subsurface digital twin for the city.  Bringing the relevant data together during 9/11 took weeks to do because the different data sets were not only in a variety of formats but each had a different data model. UNUM decided to take a standards-based approach and has adopted the Open Geospatial Consortium's Model for Underground Data Definition and Integration (MUDDI).  This model has the additional benefit that it is  is supported by the American Society of Civil Engineers (ASCE) 38-22 and 75-22 underground utility standards.  For NYC adopting the MUDDI model makes it possible to build on the work already done by other jurisdictions including Scotland, the Ordnance Survey of Great Britain, Denmark, Flanders, Netherlands, Singapore and others. Experience to date with the model has shown that the MUDDI model is comprehensive and able to describe all the key features that are found underground in NYC.

The illustration shows a conceptual picture of all the things that can be captured and integrated through the MUDDI model. At the centre are individual network features such as cables, pipes, valves, transformers, switches, and meters. Shown below the features it can be seen that each feature has attributes (age, material, location, dimensions, quality level, threat level, pressure, voltage, fiber capacity, etc) and lower right accessory features (access, support structure, container, serial#, etc). Underground facilities are surrounded by a natural environment (soil, geology, ground water, chemical contaminants). Together the network features, their attributes, supporting structures, and environment comprise the utility networks themselves.  Utility networks can be be represented in a GIS and related to other layers such as catchment areas, service districts, preservation districts, and so on.

New York intends to develop a detailed model (referred to as a profile) for the city's underground infrastructure based on the MUDDI conceptual model. The same conceptual model is being used in other jurisdictions. For example, in the UK the National Underground Asset Register (NUAR) project has created a UK profile for the excavation use case. Over the next few years based on this profile, all utility and communications networks in England, Wales, and Northern Ireland will be captured and integrated into a single map.

Conclusion

Improving emergency and disaster resilience requires accurate data about subsurface utility and other infrastructure. The 9/11 emergency clearly demonstrated the value of an integrated data set with a common base map that can be shared easily and quickly among all players. But the 9/11 experience also revealed the difficulty in achieving an integrated map with the currently available data sets and integration tools.The vision which motivated the UNUM project is a single, integrated and accessible map for New York City that integrates reliable location data for all of New York's underground utility layers in 3D, registered to a common base map and georeferenced to a common datum. To achieve this will require a shared data model enabling location and other data from different utilities and other sources to be integrated into a single map of New York's underground infrastructure  UNUM has taken a standards-based approach and has adopted the Open Geospatial Consortium's MUDDI model, also used by other jurisdictions such as the UK. The UNUM project is developing a road map for the creation of a shared data model encompassing all of the city's underground infrastructure based on the MUDDI model. 

This post is based on Rae Zimmerman's, Alan Leidner's and Wendy Dorf's talk on the UNUM project at the Subsurface Utility Mapping Strategy Forum (SUMSF).