Between the Poles

Automated feature recognition helps democratize utility mapping for producing infrastructure digital twins

In jurisdictions worldwide the low quality of underground location data has been identified as a top cause of underground utility damage. Existing underground utility data, most of which is stored in network owners' records, is often inaccurate, out of date or simply missing.  In North America in a survey of 402 locate professionals better facility maps received nearly unanimous agreement as a top strategy for improving the efficiency and quality of locates.  Singapore's Digital Underground project is unequivocal about the economic and social impact of low quality underground location data stating that "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."

Challenges facing the utility mapping industry

The root cause of the low quality of underground utility data is how utility mapping is structured as an industry. The primary activities of the utility mapping industry are data collection and how we keep and share this data with other parties.

Data collection

The way we collect is slowly changing, but predominantly we're still using traditional survey and locate methods. The survey methodology we are using hasn't changed in a hundred years. It's a very time and materials based, manual and analog process. Survey processes are slow and expensive to execute and require specialized equipment and skill sets, and safety is a big concern.

Locating underground utilities is one of the biggest causes of delays in construction schedules, service disruptions are a common occurrence, safety is always a major concern. and locate operations are slow to execute. Accuracy and timeliness are major issues. Locate operations require specialized equipment and skill sets which restricts locators to a small number of industry insiders.  A major shortfall is that underground utility location data is rarely available during the crucial planning and design stages of civil engineering projects.

Democratization of utility mapping

The utility mapping industry needs some fundamental changes. We need to move away from the monopoly that exists right now. There is just a handful of companies that are able to go out and collect underground utility data. We need to democratize data collection so that many more people can collect this data, targeting a crowd sourced approach and enabling multiple creators or collectors providing this data. This distributes the responsibility for the data as well. The more distributed the responsibilities, the lower risk and the lower the cost of failures will be.

We also need to change the skill level required. With current technology, we should be able to automate much of routine locating and thus enable many more people to do it. Using inexpensive technology will lower the cost of collecting and aggregating locate data. As data becomes lower cost to capture, data retention will become less expensive which will encourage people to retain the location data they acquire rather than simply painting/marking the ground and not capturing the data digitally.

Democratization is the real future of 3D infrastructure mapping. Right now data is still very siloed. We'll always have the traditional mapping companies, survey companies, line locating companies and asset owners going out and collecting their own data. But through crowdsourcing data from routine day to day locating and mapping, infrastructure projects, and other sources, aggregating that data and distributing access to that data is how utility mapping will really come to the forefront.  It should be easy to upload data into a central register where it can be made accessible to multiple stakeholders. Compliance with Open Geospatial Consortium (OGC) standards provides a basis for full interoperability enabling open access to every single conduit, cable, pipe, or other piece of infrastructure in real time from your phone, your tablet, your laptop or other applications.

Infrastructure digital twin

We think the best paradigm for producing and capturing asset data is through collecting it into an infrastructure digital twin. Digital twins have made a lot of progress in a variety of industries. Most importantly, for the utility mapping industry, it should be noted that creating a digital twin is much easier than it was even just a few years ago. We think the time is right for an infrastructure digital twin and it can be just at the asset level for one particular company, but we believe it should be at a regional level. Cities, municipalities and regional governments around the world are beginning to develop comprehensive digital twins of all of their physical infrastructure; buildings, roads, trees, power lines, and subsurface utilities and they're pouring resources into it.

And we think that Canada and the United States should start doing the same thing. And for us in the utility industry, data collection costs are lower than they ever have been. There's clearly interest among stakeholders and governments to start dealing with infrastructure and utility mapping problems, particularly to lower the number and costs of strikes, injuries and the loss of life. We now know a lot more about how to create data from other data sets, using different types of analysis and artificial intelligence to piece disparate data sets together. Using AI machine learning in the cloud is much less inexpensive compared to just a few years ago. And nowadays one of the things that makes infrastructure digital twins readily accessible to the utility industry is the fact that storing huge volumes of data in the cloud has become very inexpensive.

What is infrastructure digital twin ? First of all, a digital twin needs to result in effective action. It's not just enough say we have a digital twin philosophy The purpose of having a digital twin is to result in effective action that improves your business. It needs to use real time and historical data, which is paramount for us in the utility mapping industry, and it's going to be motivated by outcomes. For us in the utility industry, it is to reduce and even eliminate utility strikes during construction and the associated risks of injuries and fatalities.

The infrastructure digital twin has to be stored and managed in a relational database so it can be queried, analyzed and improved on through time, and related to other data sets. Processes for collecting data and maintaining data must be simple so that we can break the barrier of restricting underground utility mapping to a specialized group of people. If we truly want to democratize and compile data from disparate data sets, we need very simple processes to get data into the database, analyzed and maintained.

An infrastructure digital twin should be captured and maintained in 3D, even though most utilities in the ground are within just a couple of meters of the top of the ground. The 3D component is vital, because part of analyzing a data set is that much ancillary data is 3D such as overhead power lines that come down the side of a pole into conduits below the ground,

Imagery that's taken looking straight down at the ground, like traditional satellite imagery, can be visualized on a map and incorporated directly into a GIS database. But other types of imagery such as oblique, 360-degree, street-side, and inspection imagery need to be treated differently.  Oriented Imagery has a range of possible applications. For example, a construction company might use it to review asset inventory photos taken by field workers at a construction site. A telecom company or electric utility would use it to examine close range inspection images of electrical and telecom towers from many different angles. Oriented imagery applications enable you to see exactly where the image is on the map as you pan or zoom in the image. There are spatial navigation tools designed to work specifically with oriented imagery. You can query oriented images using spatial and temporal filters.

Finally, it is very important to have standardized formats, including storage formats and cloud formats.  It improves our ability to inexpensively use machine learning to do associative analyses of disparate data sets to make a larger, more conflated data sets.

Automated feature extraction

Maintaining accurate, up-to-date, comprehensive data about assets, above ground and below ground, has been a challenge for utilities for decades. Now new technologies including machine learning are being applied to automate real-time maintenance of utility network information and provide a foundation for infrastructure digital twins.

Automated feature extraction has advanced dramatically in the last few years.  This is an example where high density LiDAR and ultra high resolution imagery was used on a very low, very small diameter gas distribution install from an open trench. You can clearly see the ease with which the LiDAR produces a 3D representation of all of the local utility infrastructure.

Much of the the advancement in in automated 3D mapping have derived from the autonomous vehicle industry which have trickled down to other parts of the GIS industry.  The hardware and software are vastly easier to use and produce vastly better data. You can see from these ortho images collected from our system and the LiDAR overlaid on it. Feature extraction was used to automatically define top of pipe, top of ditch and actual joints in the pipe. Automated classification of LiDAR removes the need for someone to go out there with a Pogo stick and find the top of pipe. It makes it possible to simply drive alongside and scan with a mobile LiDAR system an open trench containing a newly installed pipe to produce a detailed 3D model with centimetre accuracy without having a person present. It is much safer - no boots on the pavement - and it drastically reduces the cost.

We prefer mobile mapping systems as opposed to handhelds because mobile mapping systems produce a tremendous amount more data and its registration tends to be vastly superior. It is much safer because it eliminates a need for someone to get out of a vehicle - so no boots on the pavement. Anytime you're still getting out, whether you're using handhold laser handhold mapping system, or a Pogo stick, you still have a person outside the vehicle walking around a street. With a mobile system you eliminate that risk, and you also drastically decrease the time required to do the collection. Here is another example where automated feature extraction was used to identify the electro fused coupling. You can see the butt joints, you can see the Ts and so forth. All this can be done very simply now with automated feature extraction.

Data registers

While surveyors may have had experience with a provincial or other types of survey register, utility location data identified during routine locate (one call) operations in general is only used to mark the ground and is rarely recorded, digitally or otherwise. Practically this means locators going back to the same location they were at just a few weeks ago to repeat the locate operation for another project. People in the locate industry are very familiar with this and the  amount of schedule and cost expense it causes. Exposing people to relocate or remap an area that was just done not too long ago is doubling their risk. Secondly, because the data is not retained or kept in easily accessible ways, we can't analyze it.  For example, we might want to confirm that we have correctly identified the type of utility, the accuracy of its location, or determine if there have been changes in its location, type, or current status since we last detected it. And because the data is not being retained and centrally managed at a global level or at a large scale level, there's no real opportunity for organic data enhancements or improvements.

The CGA Next Practices Report to Industry has made the case that a comprehensive national GIS map of buried infrastructure is among the opportunities for systemic improvement with the greatest ROI for industry. The benefits of a national register are greater safety, enhanced construction efficiency; reduced design, construction, and maintenance costs; greater regulatory compliance; improved locate efficiency; fewer project delays and budget overruns; fewer service disruptions to the public, less traffic disruptions and loss of custom and other inconveniences for the public.

Sharing maps of underground infrastructure is not totally new to Canada. For example, the City of Calgary's Joint Utility Mapping Project (JUMP) system, the ICI Society in British Columbia, the City of Toronto's Digital Map Owners Group (DMOG) and others have been sharing underground utility information for years.

The Canadian Underground Infrastructure Register (CUIR) is a new national initiative started at the beginning of the year. The CUIR initiative is intended to enhance current practices in a way that enables all stakeholder groups to benefit from the initiative; construction contractors, network owners, government transportation agencies, design engineers, subsurface utility engineering (SUE) engineers, surveyors, locators, workers in the field and the public. The CUIR initiative has been inspired by the National Underground Asset Register (NUAR) project currently being implemented in the UK. The objective of NUAR is to develop a register of location data for all underground infrastructure in England, Wales and Northern Ireland that is accessible to all network owners and government agencies.

This post is based on Joseph Hlady's (Lux Modus) talk at Subsurface Utility Mapping Strategy Forum (SUMSF).

An infrastructure digital twin provides a dynamic environment for managing underground assets of a multi-utility campus

For organizations managing a campus such as educational facilities, healthcare facilities, commercial real estate, utilities, and municipalities managing public works, storm sewer systems, and parks which are characterized by having many different utilities and and other infrastructure, an infrastructure digital twin provides owners, operators and third-parties with a streamlined, cloud-based solution that maps, manages and shares a wide range of subsurface and above ground assets, including fibre, pipes, electric power cables, lighting, conduits, and other structures enabling campus asset owners to not only track their assets but to provide all the information about their assets; their history, their replacement cost and their current cost without which you cannot justify your financial demands, be it a budget request for next year or a bid bond for a major project.

Infrastructure digital twin

A major challenge for legacy asset management systems is that documents are hard to access. Problems in the field are hard to identify because it takes too long to access the relevant documents and other information in the field. It's hard to share architecture and utility drawings with contractors and other stakeholders. People are really copying large blueprints or as-builts and delivering a set of documents to a new contractor who's just been onboarded and the contractor has to spend weeks studying these documents and comparing this information to what's there, what's underground, what's above ground and matching it together.

The way we address this challenge is by creating an infrastructure digital twin which provides accessible information to all stakeholders through a subscription service. A full digital twin of your campus, is a big, costly project, but an infrastructure digital twin is simpler and much faster. It involves site verification and infrastructure mapping as a service including drone imaging, site surveying, walking the campus and verifying objects. If the customer is using some type of infrastructure detection, the accurate information from that system plugs into our system, so it remains live. We support Open Geospatial Consortium standards to ensure interoperability. We onboard all of the data and we do that for any new updates on the campus. If something is wrong in the map and it's not in the site, or in site and not in the map, or if the drone gave us a better accuracy, we detect that and make corrections. For example, customers often hire utility engineering firms to conduct subsurface utility surveys (SUE).  We load that information and match it with everything we have in the system about their underground and other assets. Full onboarding requires 40 days or less. And more importantly, all the data is owned by the client all the time.

We've loaded over four million assets for our customers. Those assets are being used by thousands of users, including facilities, teams, construction managers, engineering and architecture firms, local utilities, fire departments and others.

You can share data immediately with anyone you want. And there are no limits on the number of users in any of our systems. If you onboard a new construction company for a new project, you just provide them with a login, specify what they can access and see, and they are onboard.

Dynamic view of your assets

The system provides a dynamic view of all your assets. It's not a static image, GIS or CAD files which you update every several months. It's real time, live presentation of information coming from a database and it is integrated with all your other systems. You can drill down on every single conduit, cable, pipe, or other piece of infrastructure and query all its attributes and see the sources of the data. You have access to the data in real time from your phone, your tablet, or your laptop because it is a fully cloud solution. We are able to do that because we are compliant with the Open Geospatial Consortium (OGC) and follow OGC standards. We are using open systems in terms of representing all the attributes about every item.  For a typical campus environment, ranging from a few blocks to a college campus or hospital complex, for example, you may have 20,000 assets. All of those assets and their associated attributes are captured and live in that database. We're building IOT integration, so you will have real time data on top of their various asset layers. You can see the water flow and the temperature and the pressure from the sensors. To go back to the updates. We are building integration with augmented reality. so that all underground assets can be visualized in 3D AR.

We provide a dynamic way of having base maps. You can use Google Maps, Esri World Imagery, or OpenStreetMap or even a mix of these. You can add your own imagery. 

In addition to the dynamic view of the locations and attributes of all your assets, you also have a plan room. All your documents are there, your engineering drawings, as-builts, survey and SUE reports, legacy maps, and other sources of underground data. You can search them by date or by the contractor or surveyor who supplied this data to you. These documents are accessible to you at any time from any device.

Managing asset budgeting

More importantly, the system provides an executive summary of all your assets. For example, in this site, which we have built as an example (we cannot share real data publicly) we have included about $4 million worth of assets. FM people need to deliver projects on time, minimize disruption of services to those people who are using these facilities, and improve the sustainability of their facilities. To do this requires that you can justify your CAPEX and OPEX budget. For some capital projects, you might be able to look at the total cost for adding a new building. But for budgets for operations and maintenance, retrofitting a fiber network, changing your irrigation network, it's really difficult to do that without having access to everything about your assets, their history, their replacement cost and their current cost. Without this information you cannot justify your financial demands, be it a budget request for next year or a bid bond for a major project.

The key to managing budgets is by replacement costs. If you want to replace your electric network, you need to know how you built the electric network in the first place. The database provides access to all this information. You can break your assets down by type of structure; electric power, conduits, lighting, water, wastewater and gas pipe networks. You can see their life expectancy, aggregate them based on their expected time of expiry and then decide on remedial action. You also need to worry about the impact of potential accidents and most importantly your liabilities. If a major underground gas line is damaged, then you might face heavy liabilities because it might interrupt gas service not just to your campus but for the entire area or even an entire municipality.

Our system has an ROI calculator so you can compute your potential savings. This has helped customers secure grants because they were able to compute the information needed to submit a bid bond.

Conclusion

An infrastructure digital twin provides immediately accessible information to all your assets for all stakeholders through a subscription service. It's a real time, live presentation of information coming from a database and it is integrated with all your other systems. For critical budgeting operations and maintenance, you have immediate access to everything about your assets; their history, their replacement cost and their current cost that enables you to justify your financial demands, be it a budget request for next year or a bid bond for a major project.

This post is based on Moufid Charafeddine's (BetterGIS) talk at Subsurface Utility Mapping Strategy Forum (SUMSF).

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).

Visualizing underground infrastructure for multiple utilities on a single map

The National Underground Asset Register (NUAR) is intended to be a comprehensive digital map of all underground pipes and cables owned and operated by 650 asset owners in England, Wales and Northern Ireland. When deployed it will provide immediate access to UK underground asset data online from handhelds and other devices to qualified excavators and their contractors.  A unique capability that differentiates NUAR from other underground data management systems lies in its ability to combine and visualize underground infrastructure of many different network operators on a single map.

Background to NUAR

In 2018 the Northumbrian Water Group Innovation Festival brought together 20 utilities, telecoms, and local government authorities in Newcastle upon Tyne to voluntarily collaborate in developing a shared underground infrastructure map showing the location of water, wastewater, gas, electricity, telecoms and other underground services provided by the network owners. Later extended to Central London, it became the pilot for what subsequently became the NUAR project sponsored and funded by the Geospatial Commission, part of the UK Government Cabinet Office.

Integrating underground data from different utilities

One key differentiator of the NUAR project is combining and visualizing underground utility data sourced from different utilities on a single map. Globally every utility has developed its own terminology for describing its network facilities, its own ways of graphically symbolizing different equipment, its own choice of base map showing road centre lines and other land base features and its own standards for network documentation.

A major advantage of mapping infrastructure in the UK is that every network operator records the location of their facilities against the same national base map, the Ordnance Survey's MasterMap. In North America in contrast every utility uses a different base map. Conflating utility data to the same base map is a complicated process which inhibits the development of a representation of underground infrastructure on a single map. In the UK the common national base map provides a foundation for displaying data from many utilities on a single base map. But to meaningfully combine and visualize data from different utilities on a single map requires that data providers agree on standards for data elements, terminology, symbology and templates for network documentation.

Developing a harmonized data model

The first version of the data model was developed in conjunction with about 40 utilities who participated in the North East of England and Central London pilots.  Fortunately the development of the Open Geospatial Consortium's open standard for exchanging underground data Model for Underground Data Definition and Integration (MUDDI) coincided with the NUAR pilot. The NUAR project became the first project to implement MUDDI in the real world.  MUDDI supports profiles that enable the MUDDI model to be adapted for different uses cases and countries. For NUAR the UK Excavation Profile was used. Participation in the MUDDI initiative enables the NUAR data model to be openly available to network operators and other organizations who choose to adopt it as a standard for their own data operations.

The central guideline that has guided the development of the model from its inception during the pilot was the need to minimize structural elements that hardwired the model. With a rapidly evolving model it was essential to be able to change different aspects the model without having to reconfigure the entire model as each new utility's data brought new changes. The result was the development of ways of modelling utility networks that differed from what had been used in previous utility models. Examples include defining general feature types that could be qualified using attributes rather than structures making them more flexible, allowing a single feature table to support multiple spatial data types (points, lines and polygons) rather than separate tables for each data type, and implementing codelists separate from the data model making it possible to change them without republishing the model.

During the initial build phase of the project each it was found that new utility data source continued to bring changes to the model. At this point it had become more essential to carefully manage changes resulting from incorporating data sets from new asset owners because of the potential impact on the data that had already been brought into the model.  

As new data is brought into the system, new feature types are discovered, for example, EV charging points, so that over time the data model is becoming more comprehensive with the potential for supporting additional use cases. In addition it is important to support the interaction of NUAR with external systems by making data types general and accessible to multiple systems and incorporating fields for capturing codes unique to the external systems. In the future this will make it possible to support work flows in which network operators' data systems provide direct data updates to the NUAR database.

One of the important realizations during the development of the Ordnance Survey MasterMap was the critical importance of object identifiers (OIDs). As new data flows in to be analyzed and brought into the NUAR model, it is being found that many asset owners have not implemented feature identifiers. One of the long term benefits of the development of the NUAR data model may be instilling in industry data modelling practice the importance of unique feature identifiers.

Progress of NUAR build phase

At the time of Amy Manefield's presentation at the SUMSF conference in March, the NUAR team had engaged with all 250 asset owners in the three initial regions of the North East of England, Wales and London. Data Exploration Agreements (DEA) had been signed with 88 of these utilities. The DEA allowed the data from these utilities to be explored, analyzed and the process of transforming it to be initiated. Of the utilities with DEA agreements 42 had already shared their data with the NUAR team and over a dozen of these data sets had been successfully transformed to the NUAR harmonized data model.

 

This post is based on Amy Manefield's talk at the Subsurface Utility Mapping Strategy Forum (SUMSF). Amy Manefield is NUAR Head of Data Operations at the NUAR project of the Geospatial Commission.

Streamlining connectivity for all with open, decentralized data

Guest post by Wade Anderson, Vice President, SMB, IQGeo

5G is predicted to have the same economic impact on the US as commercializing the internet did 25 years ago. The technology is the motor of a new data economy built around artificial intelligence, autonomy, cloud computing, and the Internet of Things. 5G is essential to produce and transport data and new knowledge faster and more seamlessly to support an increasingly digital and interconnected economy. The proliferation of IoT applications across industries is showing no signs of slowing down, presenting a huge opportunity for business growth. According to GSMA, the global IoT market will be worth $900 billion in revenue by 2025 – an almost threefold increase on 2019.

With global 5G adoption expected to almost triple in 2021, the distribution of telecoms networks will need to grow to match this projected demand. The US has ambitious plans to achieve nationwide 5G coverage through a combination of state incentives and market forces. The Biden administration pledged $100bn to improve broadband infrastructure across the nation, with the ultimate aim of providing high-speed broadband connectivity for all Americans by 2029. As a result of the COVID-19 pandemic, ensuring connectivity for all has risen further up the agenda for the telecoms industry and for municipalities, government agencies, universities and corporates that support their own fiber and 5G networks.

Major US telecoms providers are deploying superfast Ultra-Wideband 5G services across cities, stadia, and airports. The US is also ahead of many other advanced countries in allocating high-band and low-band spectra for 5G. North America has the world’s largest share of the market in ‘dark fiber’, unused additional capacity that could help share and spread 5G coverage. Yet the breadth of coverage is patchy and inconsistent and lags behind competitors such as South Korea and China. There has been growing frustration with the pace of the rollout across much of the US. There are also concerns over the lack of market diversity and the limited number of vendors following the US ban on Huawei. There remain major challenges in filling gaps in provision, particularly in remote and rural areas where major new infrastructure investment from large providers is unviable. Currently, it is estimated that over a third of Americans living in rural areas lack access to a quality standard of broadband.

Yet the expansion of high-speed broadband to all states and regions is essential to ensure equality of connectivity. To reach rural or small-town locations we cannot rely solely on major telecoms operators but need a diverse market of innovative providers, Wireless Internet service providers (WISPs), and organizations such as transport, governmental, and commercial operators willing to lease out bandwidth. These smaller providers can help complement large networks to reach under-served areas that may not be commercially viable for major infrastructure investment.

Tackling information silos to accelerate rollout

A major challenge that organizations continue to face is the existence of information silos which prevent organizations from planning the most efficient and effective paths to new markets and wider coverage. There is often a lack of structured network documentation as many smaller operators have not implemented a System of Record (SoR) which identifies an authoritative data source for each data element. In addition, there continue to be silos between workflows such as maintenance and construction and between datasets such as geospatial data and data such as asset records, repairs, or upgrades. Providers need to be able to integrate everything from meteorological to economic data with internal processes and workflows to spot new hazards or opportunities.

For example, data from the nearby natural or built environment, such as trees that could obstruct signals or tall buildings that could host 5G antennae, is crucial to maintenance schedules and planning new provision. Similarly, integrating accurate geospatial information on existing networks with data on nearby infrastructure would help organizations identify opportunities to lease out ‘dark fiber’ to others, thereby organically increasing nationwide 5G networks. Open, decentralized internal data is critical to speed up the deployment of 5G and foster a healthy, competitive culture across the industry. A diverse, dynamic telecoms market able to collectively achieve nationwide coverage will require more open and dynamic telecoms data.

To facilitate more agile broadband infrastructure planning, organizations must develop system of record (SoR) strategies and break down internal silos by encouraging efficient and joined-up data sharing. Operators should make their internal geospatial network data accessible to all departments so they can seamlessly incorporate external data such as street maps or satellite data into all their survey, construction, and maintenance processes. Geospatial network data forms a ‘digital thread’ connecting all external data to a specific location in the network and thus revealing the subtle interdependencies between networks and their local environment.

Opening up their internal systems so that disparate departments and divisions can seamlessly incorporate relevant external data into all processes. For example, IBM Weather Group’s LIDAR and satellite data on vegetation cover could be overlaid onto geospatial network data to help companies plan new 5G antennae to minimize signal obstruction from nearby vegetation. Similar organizations could open their datasets to telecoms companies to help create a complete picture of the hazards and opportunities to network expansion. By integrating external data with internal network information, new market entrants could see opportunities for efficient deployment of broadband into new geographies and accelerate the process of ensuring nationwide coverage.

A flow of telecoms data between departments enables open, decentralized information sharing. Open-source, geospatial data supports smaller and larger telecoms players to maximize the reach of high-speed broadband, addressing the growing digital divide of nationwide connectivity.

The ‘dark fiber’ opportunity

Accurate, real-time geospatial data can also help organizations spot opportunities to lease out bandwidth. Many organizations are sitting on goldmines of unused, ‘dark fiber’ network capacity that could be sold to companies or leased to nearby communities to increase coverage. We helped a large university in the western US audit and update their network asset records and uncovered over 200 underutilized ‘dark’ broadband fibers, helping streamline their network and identify extra capacity. They also used advanced geospatial information systems to predict future capacity and find the most efficient pathways to coverage across their campus.

The same data could be shared with telecoms operators or other organizations to help plot the most effective paths to extend coverage using existing capacity. North America already leads the world in the ‘dark fiber’ networks market and has an opportunity to leverage this to accelerate the nationwide 5G coverage without new infrastructure spending. Discovering unused extra broadband capacity in this way helps to increase efficiency for large and small operators alike by allowing them to extract maximum coverage from minimal resources and grow revenue potential in the process.

Other companies are digitalizing and decentralizing their network data and making it accessible to everyone from field technicians to call-centre staff. These companies are moving away from traditional centralized GIS, siloed spreadsheets, proprietary apps, or paper maps towards ‘open’ network data that can be accessed from smartphones and tablets or exported through open APIs. This means that data on current networks can be easily merged with other datasets to spot opportunities to maximize coverage with minimal resources and risk.

Achieving nationwide 5G coverage and the digital transformation of the economy will require a parallel digital transformation of telecoms, fiber and 5G operators. Companies will need to embrace an open, transparent approach to capturing and sharing data while creating the ability to capture and integrate data from across all departments and external sources to develop a holistic picture of the risks and rewards across every region. This new digital transformation will demand the democratization and decentralization of all organizational data so that every operator can see the clearest and quickest route to reaching under-served communities across the country.

Initiative to develop open standards for AEC and geospatial interoperability

The effects of population growth, urbanization and climate change are motivating us to contemplate serious changes in how we build and maintain buildings and infrastructure. This change will require new tools. There are important industry drivers that suggest that AEC (architecture, engineering and construction) and geospatial interoperability is one of them. A specific challenge currently facing the AEC and geospatial industries is integrating building information models (BIM) and geospatial infrastructure models for full life-cycle project workflows. Autodesk and ESRI have announced a partnership to further the integration of AEC and geospatial models and data which is already showing tangible results, but in a proprietary environment. A recent paper by the Integrated Digital Built Environment (IDBE) joint working group working group, a collaborative effort by buildingSMART International (bSI) and the Open Geospatial Consortium (OGC) to further open standards for AEC/geospatial interoperability, has identified the conceptual and other incompatibilities between the geospatial and AEC modeling of built infrastructure and suggested a way forward toward addressing incompatibilities.

Clashing tectonic plates

The BIM+geospatial problem is the latest symptom of a broader problem. I began working in the utility and telecom sector in 1993, specifically in developing software for records management (called network documentation outside of North America), and at that time the magnitude of the AEC+geospatial cultural mismatch problem was just beginning to be appreciated by utilities and telecoms. The Between The Poles blog is nearly 15 years old and one of the persistent themes from the very beginning in 2006 was the challenge of integrating CAD and GIS data in a common workflow (some examples; 2006, 2007, 2008 ). In utilities and telecoms planners tend to use GIS tools, engineers and designers CAD tools, construction folks in the field paper CAD drawings, and asset managers GIS integrated with their FM tools. Fashioning AEC and geospatial data into an efficient data flow from planning through design and construction to operations and maintenance continues to be a challenge.

There are parallels between what happened in the 1990s in unsuccessfully addressing CAD+GIS interoperability and the current challenge of BIM+geospatial interoperability. But there are also important differences which provide grounds for optimism that the availability of open standards for both BIM and geospatial, a vibrant open source geospatial community, and a new willingness on the part of major software players in the BIM and geospatial industries will make it possible to successfully address the latest interoperability challenge facing the AEC (architecture, engineering and construction) and geospatial industries.

Building information modeling (BIM) has been applied to design-build construction projects for many years. A growing number of countries are mandating BIM for public projects. While the UK government has said that "...we know that the largest prize for BIM lies in the operational stages of the project life-cycle", until recently there has not been hard data to support this conjecture. Similarly there has been only anecdotal support for an integrated BIM and geospatial approach for design, build, operate and maintain projects. Now we are beginning to see data from real world projects that offer evidence for the benefits of an integrated BIM+geospatial full lifecycle approach for construction projects.

Research in the Netherlands at the Delft University of Technology delved into interoperable digital building and infrastructure model standards developed to serve the AEC (architecture, engineering and construction) and geospatial sectors. Specifically, the research was focused on translating the geometry and topology of 3D digital BIM models represented in buildingSMART's Industry Foundation Classes (IFC) standard into 3D forms compatible with the Open Geospatial Consortium's CityGML standard. The researchers found is that there is more than one way to transform a BIM model to CityGML. While it was possible to transform most BIM models, it is not possible to convert all BIM models to CityGML.  The findings of this research has reemphasized the challenge of integrating AEC and geospatial data, the first major industrial symptom of which appeared over 25 years ago in the form of 2D integration of CAD and GIS.

Comparison of IFC, CityGML, and LandInfra

The IDBE working group is a joint collaboration between buildingSMART and the OGC.  Among the first products of IDBE is a paper Built environment data standards and their integration: an analysis of IFC, CityGML and LandInfra that described the incompatibilities and similarities among three open standards used in the AEC and geospatial worlds.

The three standards are IFC (Industry Foundation Classes), developed by bSI, is used predominantly for exchange of rich, fine-scale building and infrastructure data in the AEC industry, CityGML, an OGC standard, for capturing large scale urban data including buildings and transportation infrastructure originally for simulations, and LandInfra, jointly developed by bSI and OGC, for modelling land and civil engineering infrastructure facilities and designed as a successor to LandXML.

An important difference among the standards is how real-world objects are conceptualized.  IFC represents a building as an aggregation of building elements such as walls, doors, and windows, CityGML represents internal building volumes as rooms, and LandInfra represents buildings as features of a facility with only an outer shape and footprint.

Another important difference is coordinate systems. IFC uses a rectilinear coordinate system to represent structures in engineering precision over relatively small, flat surfaces.  CityGML and LandInfra model structures that need to take into account the Earth's curvature and therefore use an appropriate geographic projection system.

The standards use different geometric representations of objects.  CAD and BIM design tools use splines, nurbs, spirals and many other parametrized forms.  Geospatial applications generally use points and multi-point lines and polygons.

Topological relationships are also handled differently. In CityGML, topologies such as containment or spatial adjacency are represented implicitly in the boundaries between different geometric objects.  IFC defines objects and their geometries and separately and explicitly identifies topological relationships between them.

Level of Detail and Level of Development (LOD) are handled differently.  CityGML uses LOD to progressively define more detailed representations of a structure. For example, for a house; LOD 0 is a building footprint; LOD1, a 3D volume; LOD 2 includes a 3D roof geometry, LOD 3, windows and doors, and LOD 4 detailed structures and furniture. Levels of Development in BIM refer to levels of progress through a construction project and does not correspond to LODs in CityGML. There is no concept of LOD in LandInfra.

Conclusion

The consequence of these differences among the standards is that software interoperability and data integration are difficult.  Three approaches to resolving this interoperability challenge have been proposed.

• Schema mapping: This approach attempts to map each object in one standard to be mapped onto its nearest match in another standard.  The TU Delft research described earlier investigated this approach and concluded that unambiguous mappings between CityGM and IFC was not possible in all cases.
  
• Federation: Another approach is to support multiple schemas in one representation.  For example, a Revit BIM model can be displayed in a geospatial environment.This limits the generality of some operations such as spatial search, spatial analytics, and CAD and BIM operations.
  
• Link referencing: A third approach is a linked federation using embedding links in the primary model to components from instances of secondary schemas. The feasibility of such an approach was confirmed in OGC Testbed 4 (2007), in which web services were used for 'merging' CAD, GIS and BIM data.

Next steps

The IDBE has made several recommendations for moving forward to resolve the latest AEC/geospatial interoperability challenge in an open, standards-based way.

• Identify and prioritize uses cases.
• Compile a shared vocabulary and a shared resource for identifying synonyms across different domains.  An example of the latter is the CB-NL developed in the Netherland for mapping synonyms across the construction life-cycle.
• Develop a best practice document for coordinate systems for 3D georeferencing.
• Devise a system of common unique identifiers (Oids) for real-world, physical objects that remain
  constant and unique.
• Collaborative approach for harmonizing conceptual models.
  

I would add that owners of buildings and infrastructure, recognizing that an important benefit of open interoperability standards is increased competition among software vendors, should consider ways that open standards are incorporated into their procurement requirements.  Government procurement was a major driver that motivated virtually all BIM tool vendors to incorporate IFC support into their products.

Accelerating progress in open spatial data infrastructure at the municipal level in Canada

At the SDI Summit in Quebec City Gordon Plunkett offered an interesting perspective on the penetration of open spatial data infrastructure (SDI) at the municipal level in Canada.  Local governments are traditionally responsible for local services such as safety, infrastructure, environment, and recreation that directly impact citizens' daily life. But citizens are often not aware of available services. To increase citizen engagement local governments should make their services more easy to use, understandable, and relevant by providing them in visual form via web pages and web apps.

Background

Open data has been gathering momentum among governments initially driven by United States Federal Government data being in the public domain (since 1909.) The principle of free and open access to government geospatial data has been adopted by many governments including US Federal, Canada, Japan, South Africa, Brazil, California state and counties, and by the City of Vancouver and other cities.  In 2013 G8 leaders (Canada, France, Germany, Italy, Japan, Russia, United Kingdom, United States, and the European Union) signed a charter on open data.  The Ordnance Survey in the UK began releasing some of its data with open licensing as part of its OpenData initiative in 2010, but it wasn't until 2018 that the OS Mastermap was made openly available for the public and businesses to use. But being able to access prepared maps and other derived material is just a first step, governments need to provide access to raw geospatial data in commonly used Web-friendly formats. In the U.S. Data.gov was launched in late 2009.  In 2013, President Obama issued an Executive Order making open and machine readable the new default for federal government information in the United States.

In Canada the Government of Canada announced its Open Government Action Plan in 2012.  The fundamental principle was a government-wide directive making government information and data available to the public by default. Geospatial has led the development of open data in Canada.  Of the 80,000+ datasets that are available on the federal government's open data portal, 69,000+ are geospatial. Currently in addition to the federal government eleven provinces and territories and over 60 municipalities have open data portals. At the municipal level Vancouver has been in the forefront of municipal open data - Vancouver's open data portal was initiated in September 2009.  In November 2009  the City of Toronto launched Toronto.ca/open, the City of Toronto's official beta data set catalogue, which provided open access to city data.  In January 2010 the City of Edmonton opened Edmonton's open data catalogue, which made city data including geospatial data openly available.  In 2010 Ottawa created an Open Data Ottawa site to encourage digital innovation, improved service delivery, and stimulation of economic growth.

A major motivation for open data has been government transparency.  But there is also evidence that open geospatial data contributes to the economy.  In 2008  Australia and later New Zealand commissioned studies of the contribution of spatial data to the national economy that have concluded that with appropriate government policies the contribution to the GDP, estimated to be on the order of 1%, could be doubled.  In 2015 Natural Resources Canada released the Canadian Geomatics Environmental Scan and Economic Value Study that estimated the contribution of the geospatial sector to the Canadian economy to be on the order of $21 billion.

Current state of open SDIs in Canada

Interoperability is key for an effective SDI. The inability to easily share data is a serious constraint on the value that can be derived from it. Gordon presented a simple SDI interoperability maturity matrix. Most municipalities probably fit into what he called syntactic interoperability, the ability to share data using common file formats and APIs.  Some have ventured in sharing data at the semantic level, which means recognizing content through shared data models such as the Canadian Municipal Data Model (CMDM), National Road Network (NRN), and NENA standards for 9-1-1.  A few are venturing into addressing the issue of different names for the same objects in different jurisdictions or in different disciplines.

Patterns of use for SDI include mapping and visualization, monitoring, field mobility, data management, analytics, sharing and collaboration, decision support, citizen engagement, and design and planning. 

Perhaps the top challenge for local governments, who hold the data that is most directly relevant to citizens, is making them aware of what is available and how to use is to address their every day concerns. Gordon presented some examples across Canada of interesting open data portals: Kamloops, British Columbia; Saint John, New Brunswick; Halifax Regional Municipality, Nova Scotia, which have made a lot of geospatial and other data available on open portals; St Albert, Alberta which enables citizens to report broken infrastructure and track progress in resolving issues; Regina, Saskatchewan which also makes a lot of data available on an open portal; Red River Planning District, whose site is heavily used during the annual Red River flood season; Brampton, Ontario, a poster child for open data and citizen engagement; Repentigny, Quebec, which enables users to easily determine the availability of municipal services close to where they live or intend to live; Prince Edward Island Hydro, which shows current electricity outages; and Mount Pearl, Newfoundland, whose portal include a parcel map in addition to roads and other basic map layers.

I would suggest that another data layer that should be part of every comprehensive SDI and that is missing in virtually all local, provincial, and federal SDIs is accurate maps of underground infrastructure in public right-of-ways.  Not knowing the location of underground cables and pipes has important implications for citizen safety and the reliable delivery of essential services.

In summary, local governments are traditionally responsible for local services such as safety, infrastructure, environment, and recreation that directly impact citizens' daily life. But citizens are often not aware of available services.  Local government can improve citizen engagement by making their services to more easy to use, understandable, and relevant by providing them in visual form via web pages and web apps.

Geospatial + BIM interoperability essential for the development of smart cities

Integrated geospatial and BIM is increasingly being recognized as essential for full lifecycle construction and for enabling urban digital twins.  At this year's Geo Business in London the importance of integrating these technologies was asserted by several speakers.  From the perspective of developing smart cities, Hong Kong has made integrating these technologies a policy priority for its goal of becoming a smart city.

In an award winning paper at a 2011 conference organized by Britain’s Association for Geographic Information (AGI), Ann Kemp, then head of GIS at Atkins Global, the design and engineering firm, asked the question ‘BIM isn’t geospatial — or is it?’ and then argued that integration of geospatial and BIM was essential to address the challenges of the 21st century.  At that time within the UK construction company this was a radical suggestion, but since then the need to integrate geospatial and BIM has been gaining traction in the construction industry.  Among the construction vendor community it was adopted by Bentley, Hexagon, and Trimble a number of years ago and in 2017 Autodesk also jumped on board, forming an alliance with ESRI.  At this year's Geo Business event in London the importance of an integrated geospatial and BIM approach in construction was recognized by several speakers.  For example, Marek Suchocki, Autodesk argued that GIS and BIM are not separate, quite a change for Autodesk compared to a couple of years ago.

Hong Kong has the highest population density (26,100 per km²) in the world.  In Hong Kong 50% of the construction industry is government providing government with a key role in moving the entire construction industry, both public and private, forward. The city is quite advanced in adopting BIM.  BIM is mandatory for projects over HK$30 million. The city has developed a BIM Data Repository prototype to allow BIM models of public structures to be shared among government departments and with the public.  BIM has been accepted for General Building Plan submission (permitting) and all of this has been done in collaboration with the Construction Industry Council (CIC).  Finally a study of BIM/GIS integration has been completed.

In his inspiring talk at Geo Business Thomas Chan, Director of Lands, Hong Kong SAR Government, asserted geospatial has to go hand in hand with BIM in creating the common spatial data infrastructure (CSDI) that will underpin Hong Kong as a smart city. As a basis for moving toward a smart city Hong Kong has adopted common spatial data infrastructure,  3D GIS city model, and open data as public policies.  The city has already initiated a pilot open CSDI data portal with over 70 data types available.   But the BIM-GIS integration study found that it is currently difficult to bring BIM models into GIS.  Thomas Chan mentioned the OGC standards CityGML and IndoorGML as essential smart city standards.  Research has shown these standards have some incompatibilities with buildingSmart BIM standards. He is strongly encouraging the geospatial and BIM communities to collaborate to ensure that BIM models submitted to the city can be easily brought into the city's CSDI.

I would suggest that the most important takeaway from this is that in addition to the now widely recognized benefits of geospatial+BIM integration for the construction industry, it is also essential for creating a common spatial data basis for smart cities.  If we cannot resolve AEC+geospatial interoperability now through collaborative work between the two communities, we will continue to be plagued by this issue for decades to come much as we have been by CAD/GIS incompatibility for the past 25 years.

Autodesk signals commitment to BIM + geospatial integration for improving construction productivity

We are beginning to see data from real world projects that offer tangible evidence of the benefits of an integrated BIM+geospatial full lifecycle approach for construction projects.  A few firms such as Parsons Brinckerhoff, Atkins Global, and several Dutch firms including Arcadis and Royal BAM, in the construction sector realized a number of years ago that BIM+geospatial integration provide greater value to projects that involve not just design and construction but also operations and maintenance.  Recently Autodesk, arguably the market leader in BIM design software, has been signaling its commitment to geospatial + BIM integration, joining other firms in the construction software industry in improving construction workflows involving BIM and geospatial data and applications.

The BIM and geospatial interoperability challenge is the latest symptom of the broader problem of integrating AEC and geospatial workflows, that has contributed to low productivity in the construction sector.  Fashioning AEC and geospatial data into an efficient data flow from planning through design and construction to operations and maintenance has been an ongoing challenge for owners for decades.  The Between The Poles blog is over ten years old and one of the persistent themes from the very beginning in 2006 was the challenge of integrating CAD and GIS data and applications into efficient workflows (some examples; 2006, 2007, 2008 ).

A few firms such as Parsons Brinckerhoff, Atkins Global, and several Dutch firms including Arcadis and Royal BAM, in the construction sector realized a number of years ago that BIM+geospatial integration provide greater value to projects that involve not just design and construction but also operations and maintenance. It has been shown that BIM+geospatial integration provide greater value to projects that involve not just design and construction but also operations and maintenance. A leader in this procurement space, Rijkswaterstaat, the Dutch transportation authority, began offering design-build-finance-maintain (DBFM) projects a number of years ago which has motivated private Dutch engineering and construction companies to adopt an integrated geospatial+BIM approach to construction. For example, the firm Royal BAM Group nv/BAM Infraconsult adopted integrated BIM + geospatial because of market developments including more complex construction assignments and an increasing demand from customers for service provision throughout the entire life cycle of a project.   AECOM, which is a US$18.2 billion a year firm in the construction sector and has been ranked for eight years running it has been ranked #1 in Engineering News Record‘s “Top 500 Design Firms”, uses BIM + GIS on design, build, finance and operate (DBFO) projects including the external campus of Denver International Airport, and to lease management at Orlando, Hong Kong, and South West Florida international airports.

Major firms in the construction software industry such as Hexagon, Trimble, and Bentley have integrated geospatial + BIM to varying degrees in their approach to construction for years.  For example, Bentley decided fifteen years ago to support real-world coordinate systems in all of their products including Microstation. Bentley calls this capability geo-coordination and it provides a location-aware foundation which facilitates workflows that require integrated engineering and geospatial data and applications. According to Bentley geo-coordination adds value for asset performance with a very high return on that investment.  Integrating CAD and GIS into an efficient workflow for records management (aka network documentation) has been a challenge for utility and telecom operators for decades. While utility and telecom operators have found ways to address this problem, it is rare to find the benefits for these systems quantified. At Year in Infrastructure 2019 iForte Solusi Infotek presented concrete benefits of a records management system integrating CAD and geospatial worklows that has been in operation for several years for managing their fiber optic networks in Jakarta and on the rest of Java. For these activities iForte estimated that it has realized a return on investment of 203% over three years. The primary benefits of the new system were realized in planning, network maintenance and sales, and there were a number of intangible other benefits.

Over a year ago Jack Dangermond and Andrew Anagnost announced a partnership to build a bridge between Autodesk and ESRI technologies.  I have reviewed the technical progress that the two companies have made in furthering interoperability between the AEC and geospatial worlds which suggests that the new relationship between Autodesk and ESRI appears to be being translated into concrete actions. There is a considerable distance to go yet, but there are grounds for optimism that there is a commitment to BIM and geospatial interoperability so that in the future workflows that involve both AEC and geospatial data and software will be able to surmount the CAD+GIS barriers that have represented major inefficiencies for the construction, utility and other sectors for decades. 

Further evidence of a serious commitment to furthering efficient integrated BIM and geospatial workflows is provided in a recent article in Geospatial World by Nicolas Mangon, Vice President of AEC, Business Strategy & Marketing at Autodesk, has acknowledged that "there is a growing recognition in the collective AEC industry that geography provides a common language for collaborating on projects." Furthermore, "bringing GIS technologies and BIM processes together provides a broader and deeper understanding of infrastructure in the larger context of the built and natural environment by integrating information and content."  Expanding on the recently announced Autodesk and ESRI partnership, Mangon says that "Autodesk is bringing that knowledge from manufacturing to AEC and our ESRI partnership allows us to improve the way we create spatially accurate digtial representations of the physical. Our current plan is to expand the integration further into our detailed design applications like Civil3D but also connect GIS data into out cloud BIM platform."   This is an important statement from the market leader in BIM software and suggests that the days when architects, engineers, and construction contractors work with an isolated 0,0 coordinate system are numbered.

This is another signal from a major player in the BIM design space of a serious commitment to overcoming the BIM/geospatial integration challenge and ending the decades long clash of tectonic plates between the AEC and geospatial worlds that has contributed to low productivity in construction, utilities, telecommunications and other industries.  It will also an important first step toward the development of maintainable near real-time digital twins of urban infrastructure.

Growing evidence of the benefits of an integrated BIM+geospatial full lifecycle approach to construction

Building information modeling (BIM) has been applied to design-build construction projects for many years. A growing number of countries are mandating BIM for public projects.  While the UK government has said that "...we know that the largest prize for BIM lies in the operational stages of the project life-cycle", until recently there has not been hard data to support this conjecture.  Similarly there has been only anecdotal support for an integrated BIM and geospatial approach for design, build, operate and maintain projects.   Now we are beginning to see data from real world projects that offer evidence for the benefits of an integrated BIM+geospatial full lifecycle approach for construction projects.

The McKinsey Global Institute estimates that the world will need to spend $57 trillion on infrastructure through 2030 to keep up with global GDP growth. This is a massive incentive for the  construction industry to transform productivity and project delivery through new technologies and improved practices.  McKinsey reports that large construction projects typically take 20 percent longer to finish than scheduled and are up to 80 percent over budget. Construction productivity has actually declined in some markets since the 1990s and financial returns for contractors are relatively low and volatile.  Construction has been slow to adopt process and technological innovations. R&D spending in construction lags most other industries - construction R&D  is less than 1% of total industry revenue compared to 3.5-4.5 % in the auto and aerospace sectors.  McKinsey & Company suggests that the construction industry is ripe for disruption and two of the technologies that it believes will be key in that anticipated transformation are geospatial and BIM. 

The UK Government as part of its building information modeling (BIM) initiative has said repeatedly that it expects the big payoff of a digital model will be during operations and maintenance, which typically represents 80% of the cost of a facility.  Companies who take on design, build, and maintain and/or operate projects find significant benefits from a full lifecycle BIM + geospatial strategy. For example, EllisDon in Canada considers BIM+geospatial as best practice for its PPP projects, Rijkswaterstaat pioneered design, build, finance, and maintain (DBFM) projects in the Netherlands, Crossrail, which is currently the largest engineering project in Europe, has adopted this approach, Malaysian firm PESTECH International Berhad employs this approach for build, operate and transmit (BOT) projects, and major U.S. construction firm AECOM is applying BIM+geospatial on large design, build finance and operate (DBFO) projects. But to date there has been little reported quantitative evidence supporting the benefits of this approach.  This is changing with several projects providing estimates of benefits including ROI of an integrated BIM+geospatial full lifecycle approach to construction projects.

Integrated BIM+geospatial full lifecycle approach to construction

On many projects information provided by the construction contractor is handed over months after completion of the project. It can take the operator of the facility a year to go through this information to find the information required to operate the facility. This period is what is called the "blind spot" corresponding to the time the facility operator is managing the facility with limited information. Since for many types of equipment the highest probability of failure is in their first month or two of operation - just during the period that the building operator often doesn't have access to information about warranties and extended warranties - this increases the risk of equipment and even facility failures. In addition there is a cost associated with just finding the information required to service equipment. A NIST study across several industries estimated that the cost associated with this is 23 cents/square foot which adds considerable cost to operating the facility.

A full lifecycle facilities information flow starts with a facilities information specification from the owner identifying the building information to be included as part of the final deliverables at the time of commissioning.  The facilities information specification is part of the contract between the owner and the designers and contractors who will construct the building.  The facilities information required by the owner's specification are entered into the BIM database during design and construction by the designers and contractors.  At the completion of construction the facilities information data collected by the designers and contractors and stored with the BIM model in digital form represents a key deliverable to the owner together with the BIM model.   The facilities information can then be used to populate the building manager's asset management/facilities management system database including links to the BIM model of the facility to identify where each element or piece of equipment can be found. Most of the spatial and non-spatial data collected during construction is useful during operations. 100 % of floor plans and most of the 3D model (geometry and associated data) are needed in operations. Some owners find that just the BIM model including geometry and associated data is adequate for managing the facility. Others augment the BIM model by a Computerized Maintenance Management System (CMMS) which adds financial, occupancy, maintenance history and other information.

In an award winning paper at a 2011 conference organized by Britain’s Association for Geographic Information (AGI), Ann Kemp, then head of GIS at Atkins Global, the design and engineering firm, asked the question ‘BIM isn’t geospatial — or is it?’ and then argued that integration of geospatial and BIM was essential to address the challenges of the 21st century.  The need to integrate geospatial and BIM has been gaining traction for some time.

BIM+geospatial integration provide greater value to projects that involve not just design and construction but also operations and maintenance.  A leader in this space, Rijkswaterstaat, the Dutch transportation authority, began offering design-build-finance-maintain (DBFM) projects a number of years ago which has motivated private Dutch engineering and construction companies to adopt an integrated geospatial+BIM approach to construction.

A few firms such as Parsons Brinckerhoff, Atkins Global, and several Dutch firms including Arcadis and Royal BAM, in the construction sector realized a number of years ago that BIM+geospatial integration provide greater value to projects that involve not just design and construction but also operations and maintenance.  For example, the firm Royal BAM Group nv/BAM Infraconsult adopted integrated BIM + geospatial because of market developments including more complex construction assignments and an increasing demand from customers for service provision throughout the entire life cycle of a project. 

Geolocation plays a key role in integrating GIS and engineering data and applications for optimizing asset management workflows.  One of the foundations for an integrated system of this type is Bentley's decision many years ago to geospatially-enable all of their products Bentley calls this capability geocoordination. It provides a location-aware foundation for workflows that require integrated engineering and geospatial data and applications.

Benefits of Integrated BIM+geospatial full lifecycle construction

Recently, Microdesk has reported case studies including hospitals, a medical research facility, an airport and a university. For each facility several use cases were included in the ROI analysis.  For example, dealing with plumbing leaks, electric power shutdowns, passing on tribal knowledge from senior staff to new hires, and conducting infectious risk assessment (ICRA/PCRA), and so on.  After introducing BIM models for facilities and asset management, FM staff were surveyed and asked whether they found dealing with a plumbing leak, for example, using BIM easier, the same or more difficult than the traditional approach. The analysis quantified the time required to resolve a plumbing leak before and after the introduction of BIM.

Two very interesting examples of the ROI analysis performed by Microdesk relate to maintenance operations in a hospital. Passing tribal knowledge on from the older generation of FM staff to the younger involves a junior FM staffer accompanying a senior staff member walking the building for about a month. This requires about 200 hours of staff time. The hospital hires about 12 people per year so this amounts to 2400 hours per year. With BIM and virtual reality (VR) this was reduced to 22 hrs per person, a very significant staff time savings.  In another example, a review of infectious risk assessment (ICRA/PCRA) analysis in a hospital takes about 152 hrs and this has to be repeated 200 times per year. With BIM the time required to conduct these analysis was reduced to 74 hrs per review saving 15,600 hrs annually.

At the conclusion of five years running on the projects, the ROI analysis found a positive BIM in all cases, and estimated that introducing BIM for FM saved on average 5 % of operating costs per annum. It was estimated that introducing BIM reduced the time looking for things by 83% of the 23 cents per square foot cost for doing this from the NIST study. Since operations and maintenance are roughly 75% of the total cost of a facility, these results represents a substantial savings over the full lifecycle of a building.

The Napgur Metro, which is a US$1.3 billion project underway in Nagpur, is the first project in Asia to integrate a digital twin with an asset management system to eliminate information loss about assets during design and construction.   A 23 digit asset code was used to link 3D models developed using Bentley BIM tools with SAP financial management making it possible to track assets right from design through to operation and maintenance. BIM best practices followed the British PAS 1192 guidelines. Since the Nagpur system implements a full-lifecycle approach to project management, the location of each of the 500,000 assets comprising the systems is recorded making it possible to click on an asset in SAP and be shown the location of the asset in a 3D map.  Final deliverables are digital models rather than paper drawings providing a basis for digitalizing operations and maintenance.  The benefits of a 3D BIM+geospatial approach have been projected based on a 25 year lifetime for the project.  It is estimated that this will result in US$400,000 savings during plan, design and build, a reduction in operating manpower requirements by 20%, and increased availability and reliability.  The really big payoff is an estimated savings of US$222 million over the lifetime of the project.

 

PESTECH International Berhad, the winner of a Year in Infrastructure award, used geocoordinated digital design for the development of a new substation Kratie and Kampong Cham, Cambodia.  The decision to use geocordinated design technology for this project was partially motivated by the requirement that the company would not only be responsible for designing and building the substation but also for operating it for a period of 25 years before transferring it to the utility.

 

A number of projects in the Netherlands have been initiated by Rijkswaterstaat (RWS), the Dutch highway authority, using a design-build-finance-maintain (DBFM) approach. The Rijkswaterstaat (RWS) board is convinced of the benefits of BIM and BIM/geospatial integration and rolled out BIM/geospatial for four DBFM projects with the intention to require BIM on all DBFM-contracts in the future. Royal BAM Group nv / BAM Infraconsult was responsible for several of these projects.  A DBFM project at BAM starts with 2D geographic data that is visualized through a GIS web portal. The web portal gives everyone on the team an early perspective on the project site including underground utilities and aboveground structures before design begins. During the tender process the geospatial data is combined with 3D data including 3D representations of nearby natural and man-made features as well as proposed designs to create a 3D environment for assessing alternative designs. The 3D environment improves collaboration among the team members as well as enabling better communication with the client through 3D visualization of proposed designs. After award, the first step is conducting LiDAR scans of the site/proposed route. At completion of construction, the data collected during design and construction is migrated to an integrated GIS + asset management system system to support maintenance activities. 

 

In Canada public–private partnership (P3) have been remarkably successful for building and maintaining infrastructure. For EllisDon, a major construction and building services company, integrated BIM + geospatial is considered best practices on full lifecycle projects P3 projects in Canada.  EllisDon was involved in its first P3 project in Canada fifteen years ago. Since then the P3 business has grown and now P3 is a big part of EllisDon's business. For P3 projects EllisDon builds a wide variety types of structures including hospitals. In the P3 world the contractor often shares the risk of operating and/or maintaining a facility for an extended period. This means that people who are going to be running and managing a facility need to be involved in designing the facility right from the beginning. It is necessary to cost out the lifecycle of each piece of equipment whether it be a carpet, baseboard or cooling unit because you have to be able to maintain it and at the end of the 30 year period you are expected to turn over a hospital that looks brand new. For this reason P3 projects are very different from design+build projects.

 

AECOM, which is a US$18.2 billion a year firm in the construction sector and has been ranked for eight years running it has been ranked #1 in Engineering News Record‘s “Top 500 Design Firms”, uses BIM + GIS on design, build, finance and operate (DBFO) projects around the world.  At AECOM, the discussion has shifted from CAD/BIM alone to include geospatial and its capabilities specifically for design, build finance and operate (DBFO) projects. This mirrors the Dutch experience with design, build, finance and maintain (DBFM) projects encouraged by the Dutch highway authority. AECOM has found that by adding real world coordinates they increase the value and types of data for all stakeholders across the entire lifecycle. Integrated geospatial + BIM connects data types together. BIM holds the utility content and GIS is a visual platform for maintenance linked to a maintenance workflow. AECOM has applied this approach to the external campus of Denver International Airport, and to lease management at Orlando, Hong Kong, and South West Florida international airports. For the West Kowloon Cultural District (WKCD) in Hong Kong AECOM developed and maintains a central repository with district-wide data from various sources including all operational data - architectural planning and engineering- for the district. The advantage of an integrated BIM+GIS approach based on a centralized integration of information is that it allows the client to make strategic decisions during the design, build and operate phases of the construction lifecycle.

BIM+geospatial interoperability

Fashioning AEC and geospatial data into an efficient data flow from planning through design and construction to operations and maintenance represented a challenge that remains a problem for owners.  The Between The Poles blog is over ten years old and one of the persistent themes from the very beginning in 2006 was the challenge of integrating CAD and GIS data and applications in an efficient workflow (some examples; 2006, 2007, 2008 ). It is indicative of the importance of the integration of BIM and geospatial data and technologies that Autodesk and ESRI, 800 lb gorillas in their respective areas of AEC and GIS, have announced an agreement (for the second time) to collaborate to help bridge the gap between CAD/BIM and GIS/geospatial. 

 

Over the past decade, there has been impressive progress in developing open standards for the integration of geospatial and AEC (architecture, engineering and construction) views of city infrastructure which provides a standards-based basis for full lifecycle management from design through to operations and maintenance of infrastructure projects. 

 

The Netherlands has led in the development and application of open BIM+geospatial standards‎ in the construction industry. The Netherlands has created a BIM Gateway that is intended to be a national portal for information about open BIM standards including related geospatial standards. 

In the AEC world Industry Foundation Classes (IFC) are the open and neutral data format standard for the exchange of building information models (BIM) that is widely used in the AEC (architecture, engineering, and construction)  sector.  The IFC standard was developed and is supported by buildingSMART International.   The IFC BIM standard is used in the construction industry in many countries and is mandated in countries such as Finland.  The first versions of IFC were intended for buildings (vertical BIM).  Recently buildingSMART initiated the IFC for Infrastructure project to extend the IFC standard to support linear transportation infrastructure (horizontal BIM or BIM for Infrastructure) such as rail, road, bridges, and tunnels. 

In the geospatial world a widely used international geospatial standard for cities is CityGML.  Thomas Kolbe and co-workers are the developers of the CityGML standard that has been adopted by the Open Geospatial Consortium.  Kolbe et al. are translating a vision of the city as an interactive system comprised of functional components, utility networks connecting components, and interdependencies between utility networks into standards-based intelligent models that can be used to analyze urban environments for a variety of purposes including risk- and disaster management energy consumption, carbon balancing and city life-cycle management.

Currently CityGML includes 3D geometry, topology, semantics, and appearance for urban environments. CityGML also supports a standard mechanism for adding extensions, called Application Domain Extensions (ADEs).  There are several Application Domain Extensions (ADEs) that have been developed to extend CityGML to other domains.  For example,  I blogged about a basic extension UtilityNetworksADE that was proposed for city utility networks.  The INSPIRE Data Specifications Annex III contains use case encodings and a data model for Buildings the development of which was strongly influenced by CityGML. There have been attempts to integrate or at least develop a mapping between IFC and CityGML. 

A major breakthrough in bringing the architectural and geospatial views onto a common footing is the OGC LandInfra Conceptual Model developed by the OGC in cooperation with buildingSMART International and approved as an OGC standard in August, 2016.  LandInfra  was developed by Bentley Systems, Leica Geosystems, Trimble, Australian Government Department of Communications, Autodesk, Vianova Systems AS, and buildingSMART International and provides a unifying basis for land and civil engineering standards including the OGC's InfraGML and buildingSmart International's IFC for infrastructure standards.  

buildingSmart International's IFC-Alignment project uses this common conceptual model of alignments for roads, railways, tunnels and bridges.  The objectives of the IFC-Alignment project is to enable the exchange of alignment information through the full infrastructure lifecyle from planning through design and construction to asset management. On the geospatial side  InfraGML is the OGC's application schema supporting land development and civil engineering infrastructure facilities.

Open source support for AEC/geospatial interoperability

Where there are recognized open standards, there are more often then not open source projects supporting those standards.  mago3D is a new open source 3D geo-platform.  It is open source and integrates many well-known open source geospatial products and APis.  The importance of this technology is that it shows that it is possible using the available open source, geospatial APis and tools - together with some genuine innovative development - to create an open, non-proprietary 3D geospatial platform for integrating geospatial and BIM. Given the critical importance of addressing the cultural and technical divide between the AEC and geospatial worlds, a viable open source alternative is essential for developing the innovative solutions to the challenge of interfacing the two worlds. 

Bentley has announced that it intends to build its products supporting digital twins around an open source project already on Github called iModel.js.  Bentley is committing its resources to developing an ecosystem around iModel.js. To quote Keith Bentley this is a huge change in direction for Bentley although Bentley had puts its toes in the open source water previously.  Bentley used open source geospatial components to develop a new front-end for its leading road and rail asset management system AssetWise Lifecycle Information Management solution (ALIM).  Bentley has also partnered with AGI to support the open source Cesium project.

Conclusion

As owners see the advantages of design, build, operate and/or maintain projects and are beginning to changing their procurement practices, construction companies are changing their  business processes to optimize facility maintenance and operation.  Construction companies that have taken on the challenge of design, build, operate and maintain projects are realizing that there are significant benefits from an integrated BIM+geospatial approach to full lifecycle construction.   The advantages of an integrated BIM+geospatial approach have remained for the most part company internal.  Now it appears that the word is getting out.  Standards organizations in both the AEC and geospatial worlds are making progress on BIM+geospatial interoperability.  Major software vendors Autodesk and ESRI have announced an agreement to partner for greater interoperability between their products.  The open source community is also addressing the issue of BIM+geospatial interoperability. We are now beginning to see data from real world projects that offer quantitative evidence for the benefits of an integrated BIM+geospatial full lifecycle approach for construction projects.