Between the Poles

Nanosatellites and drones represent a paradigm shift in measurement of methane emissions

Annual emissions of methane (CH4) have risen by almost 10% in the past two decades. The primary sources of methane are the oil and gas industry and agriculture, in large part from livestock.  Methane emissions are either measured on the ground, a slow, laborious process using a hand-held scanner or over a broad area using government-funded aircraft overflights or satellites.   But this is changing. In 2016 a privately-funded startup GHGSat launched a cubesat weighing 15 kg with 50 metre resolution to measure methane emissions from individual oil and gas wells, refineries, compressor stations, landfills, animal feedlots, rice paddies, and natural sources.

Background

Source Nature 14 July 2020

Annual emissions of methane have risen by almost 10% in the past two decades. Atmospheric concentrations of methane reached1,875 parts per billion in 2019 which is more than 2.5 times above pre-industrial levels.  The primary anthropogenic sources of methane are the oil and gas industry and agriculture, especially livestock production (enteric fermentation).

A study used spatial analysis to investigate the spatial distribution of anthropogenic methane sources in the United States by combining comprehensive atmospheric methane observations, extensive spatial datasets, and a high-resolution atmospheric transport model. Based on the results of this analysis the authors conclude that the US Environmental Protection Agency (EPA) underestimates methane emissions nationally by 50%.  The study found that methane emissions due to the animal husbandry and fossil fuel industries have larger greenhouse gas impacts than indicated by existing inventories.

A study by Robert W. Howarth, Renee Santoro, and Anthony Ingraffea concluded that the emissions of methane from shale gas wells are between 30% and 100% more than methane emissions from conventional natural gas wells.  The study estimated that between 3.6% to 7.9% of the methane from shale-gas production escapes to the atmosphere in venting and leaks over the lifetime of a well.  The study suggested that the leakages are sufficiently large to erase the advantage of natural gas over coal in producing energy with lower emissions.

Another source of methane in the atmosphere are leaks from natural gas distribution systems.  A partnership between the Environmental Defense Fund (EDF) and Google Earth released interactive maps showing methane leaks from gas distribution systems under the streets of Boston, Indianapolis and part of New York City.

In 2016 the Obama administration issues new rules regulating methane emissions from the oil and gas industry and requiring the monitoring and reporting of emissions.

The U.S. Environmental Protection Agency (EPA) has estimated U.S. emissions taking a bottom-up approach in which emissions from individual facilities are aggregated.  Other sources have used top-down measurements from aircraft overflights and satellites funded by government agencies.  A recent Environmental Defense Fund (EDF) study concluded that methane emissions from the U.S. oil and natural gas supply chain in 2015 amounted to about 2.3% of gross U.S. gas production and are about 60% higher than EPA estimates.

Measuring methane emissions

Measurements of oil and gas CH4 emissions are either captured by top-down (TD) or bottom-up (BU) collection methods. Top-down measurement of methane use aircraft and satellites and estimate emissions from many sources across large geographies. These are generally government funded.  Bottom-up studies measure emissions from individual pieces of equipment, operations, or facilities on site or directly downwind and can be industry funded, government funded or funded by a not-for-profit such as the EDF. Currently the way to scan an oil or gas field for methane emissions is visiting each facility and pointing a handheld device at the facility and looking for a telltale wisp indicating a methane leak. For an oil and gas field this can take weeks.  New technologies including nanosats and drones are radically changing how methane emissions are measured.

GHGSat

In 2016 a venture capital funded startup GHGSat based in Montreal launched a demonstration cubesat weighing 15 kg and named Clair.  The objective was to provide satellite-based methane measuring device that would enable private industry to estimate emissions from its own facilities anywhere in the world. An important business driver is the global carbon market which is currently estimated to be about $50B and growing. This provides a financial motivation for industrial emitters to measure and manage their emissions.

Claire orbits the Earth every 90 minutes. Its field of view is roughly 12 km x 12 km and it has spatial resolution of less than 50 metres. Claire is able to measure emissions from over 1,000 sites per year. 

The next two satellites (GHGSat-C1, or "Iris" and GHGSat-C2, or "Hugo") are scheduled for launch in 2020.  Iris, scheduled to launch in the middle of August, will have higher resolution (25 metres) than Claire and will be able to measure emissions much more rapidly.

Drones

In a recent Microdrones webinar, Bret Burghdurf described how drones are being used to measure methane emissions from 30 to 80 feet up in the air.  Capturing methane emissions using a methane detector carried by a drone is generally reliable, the only areas where it may not be are over standing water and deep snow.  The drone carries a camera in addition to the methane sensor allowing the facilities being monitored to be captured visually.  The device is capable of capturing 10 readings per second.  Typically over a facility such as a chemical plant, tank farm, compressor station or landfill a grid pattern is flown. Over a linear asset such as a pipeline the flight plan follows the pipeline.  The market for this type of measuring is typically the oil and gas industry itself.

Sentinel 5p TROPOMI

The European Space Agency (ESA) launched the Copernicus Sentinel 5 Precursor (5p) with the TROPOMI sensor onboard in 2017.  It can capture regional emissions of methane, nitrogen dioxide, sulfur dioxide and other gases and aerosols for the entire earth every day. Sentinel 5p weighs about 900 kg and captures a swath width of 2,600 km with a pixel size of 7 km x 7 km.

MethaneSAT

Intended to launch in 2023 MethaneSAT will cover a 200-kilometer view path with a revisit time of every few days. The satellite weighs 350 kg and has a resolution of 100 m x 400 m across a 260 km swath. MethaneSAT is being developed by a subsidiary of the non-profit Environmental Defense Fund (EDF).

Conclusion

Methane is a greenhouse gas whose concentration in the atmosphere is rapidly increasing.  The source of most of this increase is anthropogenic and being able to efficiently measure and monitor methane emissions is going to be critical in controlling and reducing emissions.  New technologies from privately funded companies and others including nanosat- and drone-based methane sensors are providing more efficient and higher resolution devices for measuring methane emissions from many different sources in the fossil fuel industry and agriculture.

New satellite constellation will capture 30 cm imagery with up to 15 revisits per day

I remember back in August 2014, when the first images from WorldView-3 were being downloaded. WorldView-3 was the first one-foot-resolution commercial satellite. It operated at an altitude of 617 km, flew in a sun synchronous orbit and could collect up to 680,000 km² per day.  It had 31 cm panchromatic resolution, could capture 680,000 km² per day, and had an average revisit time of less than a day.  In 2021 MAXAR is planning to launch the WorldView Legion constellation, six satellites with 30 cm resolution, better than 5 meter absolute accuracy, able to capture 5 million km² every day, and with up to 15 revisits per day.

At GeoIgnite Online 2020 Kumar Navulur, Chris Formeller, and Kathryn Seitz presented an overview of the specifications and capabilities of the Legion constellation. The total land mass of the Earth is 148.9 million km2.  The new constellation will be able to capture 30 cm imagery of over 3 % of that every day.  Over much of the lower 48 states in the U.S. it will be able to revisit the same location 15 times per day. Over Canada it will be closer to 8 revisits per day.  Some of the satellites will fly sun synchronous orbits and others mid-inclination orbits.  What this means practically is that it will be possible to capture imagery at different local times of the day, unlike with sun synchronous orbits where imagery is captured at the same local time every day. For many customers imagery will be available within 24 hours of capture.

Innovative technology uses AM radio waves to detect underground infrastructure

In the last few years there have been important advances in technology for detecting underground infrastructure including capturing ground penetrating radar (GPR) scans at highway speeds, combined GPR and LiDAR scanning for simultaneous above and below-ground mapping, software to simplify the interpretation of GPR scans, inertial mapping of pipe networks, and acoustic locating to name a few.  Most recently a new technology originally developed for military purposes uses AM radio waves to detect underground assets.

Background

The $10 trillion global construction industry is facing a crisis. For many of the world's advanced economies including Japan, Germany, U.S., South Korea, and U.K. construction productivity has been stagnant or even declining for decades. Virtually all of the funding for infrastructure was sourced from government who were looking for a social return on the investment. Since the mid 2000s, an increasing proportion of investment in infrastructure has come from private sources; pension funds, insurance companies and sovereign wealth funds which together manage over $60 trillion. These sources of investment are expecting a financial return and that is driving a growing investment in construction technology to improve productivity. Historically, investment in research and development by the construction industry has been very low compared to other industries. Several years ago a McKinsey Global Institute study compared the degree of digitalization of nearly 30 industries and concluded that construction ranked right at the bottom with hunting. But there are signs of a change. Venture capital investment in technology startups in the construction sector is growing especially since 2018.

Detecting underground infrastructure

In the last few years there have been important advances in technology for detecting underground infrastructure. Advances in ground penetrating radar (GPR) now make it possible to safely capture scans at roadway speeds. One of the important challenges of GPR is interpreting the scans which has required a trained geotechnician. New software developments are simplifying the interpretation of GPR scans, enabling surveyors and other professionals to use GPR technology effectively. LiDAR is being applied to efficiently capture the location of newly installed underground pipelines. The simultaneous capture of above and below-ground scans using LiDAR and GPR creates a complete assessment for construction projects. Inertial mapping can be used to map underground pipe networks for up to two kilometers. Advances in acoustic locating show the technology can be effective in detection underground objects down to 30 feet.

Detecting underground infrastructure with AM Gradiometer

KCI reports that the AM Gradiometer can be configured to be hand-held or placed on a cart.

KCI is an engineering, planning and construction firm with customers across the United States. KCI recently had the opportunity to pilot and is now utilizing an innovative technology AM Gradiometer (AMG) to detect and map underground infrastructure. This is a patented tool that uses AM-band transmissions from radio station towers to detect subsurface objects. The device’s antennas detect AM radiofrequency signals reflected from underground assets. The device consists of multiple receiver antennas.  The spacing between the antennas determines the depth at which the device detects objects. A typical configuration includes three antennas. When closely spaced they detect shallow targets (5-10 feet). Intermediate-spacing detects targets at medium depths (10-20 feet), and more widely-spaced antennas can detect deep targets (30-50 feet).  The data can be exported in several forms including as a spreadsheet, a Google Earth map, and a CAD file.

An AM Gradiometer scan is performed in a grid pattern over an area of planned excavation. The device can be pushed on a cart or carried by hand.  The AM Gradiometer also includes GNSS capability and the ability to be tracked with a total station for accurate georeferencing. The device can detect electrical conductors, metal pipes, non-metallic conduits, liquid or air-filled void space, natural gas or fuel lines, brick or concrete sewer lines, shielded fiber optics cables, and hydrocarbon or saline moisture plumes.

Geospatial+BIM are a major contributor transforming construction

Geospatial and BIM have been identified as key technologies in the digital transformation of the global construction sector which has been underperforming for decades.  A recent report estimates the size of the contribution of geospatial+BIM technologies to the architecture, engineering and construction (AEC) sector.

The $10 trillion global construction industry is facing a crisis. For many of the world's advanced economies including Japan, Germany, U.S., South Korea, and U.K. construction productivity has been stagnant or even declining for decades. Virtually all of the funding for infrastructure was sourced from government who were looking for a social return on the investment. Since the mid 2000s, an increasing proportion of investment in infrastructure has come from private sources; pension funds, insurance companies and sovereign wealth funds which together manage over $60 trillion. These sources of investment are expecting a financial return and that is driving a growing investment in construction technology to improve productivity. A McKinsey report, Imagining construction’s digital future, presents data that shows 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. The report finds that construction has been slow to adopt process and technological innovations. R&D spending in construction lags 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. A McKinsey Global Institute study compared the degree of digitalization of nearly 30 industries and concluded that construction ranked right at the bottom with hunting.

But there are signs of a change. 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.Venture capital investment in technology startups in the construction sector is growing. 2018 was an inflection point with venture capital investment in the construction sector quadrupling. Two of the technology sectors that McKinsey & Company suggest will be key in the digital transformation of construction are geospatial and BIM.

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 and analytics that offer evidence for the benefits of an integrated BIM+geospatial full lifecycle approach for construction projects.

A recent study by Geospatial Media Analysis, GeoBIM Market in AEC Industry: Technology Trends, Value Propositions, Market Size, Readiness Index, and Maturity Model, has estimated the market size of geospatial+BIM technology in the global AEC sector which contributes about US$11 trillion to the global GDP.  It is estimated that the cumulative geospatial industry's value in the AEC sector is US$71.28 billion in 2019 and is expected to reach US$117.59 by 2023. The cumulative BIM market size is estimated to be US$7.9 billion in 2019 and growing at a CAGR of 11.06%.  The impact of geospatial+BIM technolgies on construction are significant.  For example, it is estimated that geospatial+BIM solutions reduce average design time by 22.2% contributing to overall savings of 5.9% on small scale construction projects. For large scale construction projects GEOBIM solutions are estimated to contribute approximately 13.1 % in overall project savings.

To make the key GEOBIM technologies concrete the report describes a GEOBIM Maturity Model that makes it possible to evaluate and assess the ability of an AEC firm to operate in an integrated geospatial+BIM environment. The GEOBIM Maturity Model extends across the entire construction lifecycle from planning, through design and construction to operations and maintenance.  The levels of the GEOBIM Maturity Model increase as more innovation takes place in digital GEOBIM technology and the importance of the integration of geospatial and BIM technologies is recognized. For example, for surveying traditional theodolite and chain is characteristic of Level 0 in the maturity model.  As more modern digital technologies are adopted levels rise; total stations (Level 1), laser scanning and GNSS, (Level 2) to mobile scanning, drones, ground penetrating radar and other underground locating and mapping technologies (Level 3).  For planning and design, the increasing use of digital technologies compared to drawings and paper maps (Level 0), include CAD and digital maps (Level 1), BIM and 3D point clouds (Level 2) to digital twins of both above and below ground infrastructure and mixed reality (Level 3). For construction, traditional constuction machinery and paper drawings are being replaced by BIM models, digital geospatial maps and automated construction with GNSS, and prefab and additive building.

A survey of the Facilities Management (FM) industry found that while 92% had heard about BIM and 84% agreed that BIM has the potential to deliver value add to FM, over two thirds said that the FM is not prepared for BIM. Evidence suggests that full lifecyle construction including FM is gaining traction in the construction industry. As owners see the advantages full-lifecycle thinking for construction 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.

In conclusion real world data and analytics are now revealing the benefits of an integrated BIM+geospatial full lifecycle approach for construction projects.

Thank you to Ananya Narain for bringing the GEOBIM Market in AEC Industry report to my attention.

New standard for capturing information about underground utilities exposed during construction

In Germany a new standard for documenting and exchanging information about underground infrastructure exposed during construction has been developed. Referred to as DIN SPEC 91419 it provides a standardized way to capture and share a wide range of information about the underground and has important implications for the continuous improvement in the reliability of location and other information about underground infrastructure.

Despite the documentation (records) about their networks maintained by utility and telecom network owners, what is actually underground and where it is located remains uncertain. A wide range of technical issues can only be identified after exposing underground infrastructure.  Information about the underground that is inaccurate, out of date and often missing means that engineering designs often have to be modified on site after construction has begun. This results in inconsistencies between design and what is actually built which are largely undocumented. "As-designeds" are submitted as "as-builts" and the viscous cycle continues.

Providing a mechanism for improving the quality of network documentation and records is being recognized as an essential component of a program for reducing damage to underground utilities. For example, The Colorado Department of Transportation (CDOT) has implemented a cloud and mobile system that incorporates elements of survey and GIS practice and technology. The system provides for recording and sharing the location and other information for underground utilities from SUE surveys, surveyors and other sources among CDOT, large and small construction contractors, network operators, and other stakeholders. Access to this data is provided over the web, enabling staff to access underground utility location maps on a handheld in the field at a construction site. The CDOT system includes an important capability that enables input from handhelds in the field during construction. This increases field staff engagement and enables staff to actively contribute to improving the accuracy of location and other information stored in records.

The prototype system developed for the National Underground Asset Registry pilots in the U.K. for sharing location and other information about underground assets among government roads agencies, network operators and others includes a similar field feedback mechanism.   Referred to as “observations”, comments on discrepancies between what is shown by the system and what is actually observed in the field as well as changes made during construction can be reported and are incorporated with their location in the NUAR database. I believe that the latest version of the KLIC system in the Netherlands also implements a similar capability.

The new standard for the documentation and exchange of data about underground infrastructure exposed during construction uses XML encoding.  It provides a standardized way to capture and share a wide range of information about the underground including

• Name, role and affiliation of data provider. Roles include surveyor, construction foreman, site manager, excavator, project leader, structural engineer, etc.
• Location of site where data is reported
  
• Content can include technical reports, observations, notes, photos and videos
  
• Keywords characterizing the information such as subsoil investigation, BIM model, gas pipeline, cable duct, storm sewer, sanitary sewer, etc.

Example of photo and other information about utilities exposed during excavation

An online system localexpert24 has been developed that allows sharing of information about the underground.  This system provides all stakeholders on a project access through a very simple interface to all the information about the underground that a local expert considers to be important - in essence providing a situation assessment for the underground.

To put this in a broader context procedures and technologies for raising the level of accuracy, timeliness and completeness of the location and other information about existing underground infrastructure is one of the most important measures for reducing damage to underground utilities during construction. Enabling direct input from the field, where staff can see what is actually in the ground, and sharing this information are indispensable to a program of continuing quality improvement in information about the underground.

Many thanks to Markus Becker, founder of localexpert24.de and one of the initiators and authors of the DIN SPEC 91419 standard, who brought this remarkable initiative to my attention.

Above and underground infrastructure comprise Rotterdam's open digital twin

The City of Rotterdam is developing a digital twin of the city.  3D vector and image data of the above- and underground infrastructure, zoning regulations and city by-laws, data streams from real-time sensors, applications and simulations will comprise Rotterdam's digital twin. It is envisaged that the digital twin will enable the city to assess the impact of proposed changes in bylaws and regulations by simulating them before they are implemented. Rotterdam, and in fact the whole of the Netherlands have adopted transparency and open data as a pillar of government and are basing 3D models on open national and international standards, intend for the 3D data to be open and accessible to the public, and intend to use open source software wherever possible.

Many cities have 3D models of their aboveground infrastructure; buildings, transportation networks, parks, and other infrastructure typically captured in 2D or 3D imagery from overflights or in 2D GIS maps.  Imagery is not very smart and extracting 3D vector objects such as building footprints, heights, profiles and transportation networks requires sophisticated post-processing.  Even more importantly, underground infrastructure is usually neglected, even though it is recognized that water and wastewater, energy (gas, electric power, and district heating),  and communications (fibre and copper) networks provide the life blood of the city.

Rotterdam has been developing its 3D model, which underpins the digital twin, for several years.  Currently it contains street furniture such as street lights, trees and underground parts of street furniture, a large scale basemap, a complete map of underground networks of cables and pipes, buildings, and non-physical content such as zoning regulations and  bylaws.  The 3D model is kept in sync with data repositories maintained by city departments and others.  In the future it will also include real-time data streams from a variety of sensors. 

The 3D model is open, based on open standards and many of the applications that have been developed for it are open source projects. For example, visualizations rely on Cesium, an open source initiative which has just announced support for visualizing underground utilities, mines, and geological layers. The rationale for the data being based on open standards is that an standards-based environment creates an open data commons where developers can devote their time to developing innovative applications rather than spending time converting data from one format to another.

The Dutch 3D standard is an integration of CityGML Application Domain Extension (ADE) and the existing national IMGeo standard for large-scale representations of roads, water bodies, and land use. The Dutch Kadaster, Geonovum, the Netherlands Geodetic Commission and the Dutch Ministry of Infrastructure and Environment initiated a "3D Pilot NL" to develop a national 3D standard.  Existing intnernational standards including CityGML(Open Geospatial Consortium), IFC (buildingSMART), and others were investigated. The findings of the pilot  resulted in a national 3D standard implemented as a CityGML Application Domain Extension (ADE) that integrates the latest version of the existing Dutch national standard IMGeo 2.0. 

Current applications (virtualcitySYSTEMS, ESRI, IMAGEM and Unity) use the 3D model as input for analytics and visualization. One can imagine many use cases for the data in the Rotterdam 3D model. Among these three use cases have been identified as low-hanging fruit; climate adaptation, viewsheds and energy performance of buildings. 

Much of Rotterdam is below sea level and managing rain water accumulation during heavy rainfalls is a major issue. which affects building basements, subway entrances, low-lying roads, electrical transformers, and other infrastructure.  To address this problem, the concept of "water squares" has been developed and the 3D model used to determine the optimum location for these..  Water squares are open areas where water can safely be allowed to accumulate during heavy rainfalls to avoid overstressing storm sewers. 

In another application of the 3D model data, building data can be filtered and streamed to energy performance applications that provide insights into how buildings perform.

Open standards and open data also enables the sharing of data among cities in the Netherlands.  The Dutch Kadaster has developed an open 3D map of the whole of the Netherlands, with scales ranging from 1:500 to 1:25,000 in collaboration with academic, private sector, and public sector partners.  All data in the 3D map is built on the basis of open standards.  The map was created by combining existing 2D data with the Elevation Model of the Netherlands resulting from a LiDAR survey which covers the whole of the Netherlands with a resolution of eight elevation points per square meter.

Open data and open standards also relate to a critical issue that is of growing importance. Many governments have adopted transparency and open data as a cornerstone of democratic policy.  But often digital twins for smart cities are being developed by private-sector firms or by public-private initiatives.  As William Davies points out in Nervous States, "the IT infrastructure used to build e-geovernment projects or "smart cities" comes from the commercial sector, and the companies that provide it often retain control over the data that results." 

For example, recently a joint Alphabet/Google/Sidewalk Labs and City of Toronto initiative to develop a smart city on Toronto's waterfront foundered and was cancelled.  One of the reasons, it is argued, is that a technology giant such as Google (or Facebook, Amazon, ...) is not a vendor in the traditional sense, but a "surveillance capitalist" that collects and analyzes behavioural data captured from users for its own economic imperatives.  In the context of a smart city the opportunities for data collection from citizens and from systems such as water and wastewater, transit, waste removal, traffic management, and others are immense.  If this data is appropriated and becomes proprietary, it puts a private entity in a position to supplant democratic government, which doesn't have access to this huge volume of data and the analytics which extracts information from it.  Relying on open standards and ensuring that data is open and accessible to the public are essential to avoid citizens' and municipal data becoming proprietary.  Furthermore, using open source software and, I would add, open training data for machine learning applications helps avoid the problem of the analytics also becoming proprietary.

Based on a Webinar by Christian Veldhuis, Advisor City of Rotterdam, Rick Klooster, CCO, FUTURE INSIGHT and Antje Kunze, Director Sales & Marketing, virtualcitySYSTEMS.