GIS and Digital Twins: Time to Close This (Narrow) Gap

Let’s Get This Term into Your Household

GIS, which stands for Geographic Information System, is not a household term—but it plays a role in every phase of your household’s creation, maintenance, and use. Your home or building’s land boundaries require precise definitions and legal status information tied to local authorities—all within the realm of GIS. Construction depends on an understanding of the layout and capacity of water and sewage lines—once again, GIS. After construction, your power and telecom distribution networks must be managed at the neighborhood or urban scale—also best handled by GIS. Even the traffic data used during your commute relies on a geospatial framework that goes beyond static road maps, enabling traffic jam predictions and intelligent planning.

Even a very brief and informal overview of GIS, as provided in the previous paragraph, is likely sufficient to evoke the sense that GIS is an excellent candidate for a digital twin model. In fact, GIS provides precise digital information such as boundaries, structural shapes, and distances, enabling meaningful calculations. This spatial data is further bolstered by attribute information, offering not only the geometry of real-world elements such as power lines and roads, but also usage types (e.g., electricity vs. fiber internet) and metadata such as building numbers, business names, and more. This combination of spatial precision and semantically relevant information forms a solid foundation on which a digital twin can be built.

GIS and I: A Devicebreaking Story

My personal history with GIS dates back to summer internships at various companies and municipalities between the ages of 13 and 18. My experiences included late-night processing of field data gathered via bulky GPS devices, manually entering a mind-numbing amount of tabulated information (I guess we weren’t so easily bored back then), and even an unfortunate instance of breaking a very expensive stereo imaging device (I still wince when I recall the moment).

Although I later detoured into mechanical engineering and robotics, it was GIS that earned me my first job interview—thanks to a desperate attempt to pad the very limited experience section of my résumé with summer internships. That interview turned into my first job and after many years working with control systems, AI, and IoT, I somehow found myself serving as a Chief Technical Officer for a platinum partner of Esri.

This feels like a good moment to pause for exposition—the last few sentences are already dense enough with acronyms to disrupt our heroic journey toward the digital twin landscape.

A Quick Tour of the Kitchen

Esri (Environmental Systems Research Institute), headquartered in Redlands, California, is currently the global leader in GIS-related software and services. Its software is used by 70% of the world’s largest companies, 95% of the largest national governments, and 80% of the largest cities.

While I wouldn’t go so far as to say that any one company can speak for an entire industry, the past years I’ve spent in the “GIS kitchen” (so to speak) of this dominant player have given me an exciting glimpse into where the geospatial world is headed—and how its trajectory may soon intersect with the digital twin revolution.

Over the last decade, Esri—along with other major players in the industry—has been pushing GIS to include more advanced 3D modeling and analytical capabilities. These features are critical when we consider the potential for developing sustainable solutions in urban environments.

3D spatial analyses can help identify optimal locations for solar panels (accounting for sun movement and surrounding structures), design building layouts that minimize heat loss, and create urban plans that are more resilient to natural disasters. Numerous other examples are being explored and showcased by forward-thinking urban administrators and academic researchers.

Tearing Down the Tower of Babel

Even without cutting-edge advances, GIS offers a unique set of core features that make it a powerful enhancer for any digital twin. Foremost among these is that GIS has always been a technology built for multiple stakeholders.

This may sound trivial—after all, most systems impacting shared environments like factories, airports, or hospitals would likely make the same claim. But in my experience, sites that don’t utilize GIS often devolve into a Tower of Babel scenario: a collection of siloed systems, each focused solely on its own domain, leaving integration as someone else’s problem.

So how does GIS overcome this issue?

One of the defining features of GIS applications is their use of a visual representation of location—such as a map or 3D urban model—as the primary interface, or at least as an integral part of it. The most common setups I’ve encountered feature a nearly full-screen map, accompanied by a sidebar for layers and a top row of buttons that reveal tools for measurements, complex queries, launching forms, and more.

In fact, if you’ve ever used a popular map application like Google Maps, Yandex, or Bing Maps, you can think of GIS applications as specialized versions of those—slathered with a healthy dose of steroids.

Constructing a Sample Use Case

To clarify why this is such a big deal, let’s visualize a construction site—specifically, a school building planned for an empty urban lot. Even for a seemingly self-contained structure like a school, the work doesn’t happen in isolation. The project must interact with a range of urban utilities, including electricity, water, sewage lines, and more.

A construction or architectural firm must submit designs to the local authority to ensure that the new building integrates with these existing infrastructural elements. To achieve this, the firm can—assuming it is operating within the bounds of a modern municipality—access infrastructure data through a GIS application and overlay its design onto existing water and sewage lines using what is essentially a (very) capable digital map.

Since both the firm and the municipality are operating within a GIS environment, the design can be shared either through a common GIS platform or by submitting the design data in a GIS-compatible format. The difference is largely practical and doesn’t change the nature of the interaction.

In the next step, the local authority can use GIS tools to analyze whether the new construction is truly compatible with the existing urban fabric and underlying infrastructure. It’s easy to imagine how a similar collaborative setup could also support revisions, site checks, and more.

If we stay within our hypothetical scenario (which, fortunately, is becoming more common), the most natural interface for both stakeholders is a model of the project site and its surroundings—whether a digital vector map or a satellite image. On this interface, the school blueprints can be overlaid in their final position, the sewage, electricity, and water lines can be brought in, and both the designers and municipal experts can work together to find the best way to bring everything into alignment.

In fact, the same system remains relevant long after construction is complete. For example, a technician sent out to inspect a telecom junction point can pull up a GIS application on a mobile device and access the same geospatial data layers.

A Common Operating Picture is Very Uncommon

As intuitive as this may seem, in my experience there's still a strong tendency for domain experts to stick to their own specialized tools rather than adopt a shared “common operating picture” (a term originally coined in the military to describe a real-time, shared understanding of a situation). You might be surprised to discover that even highly spatially relevant information—such as access points to sewage systems or electrical junctions—is often stored in tools that resemble Excel spreadsheets far more than the “location-first” interfaces of GIS outlined earlier.

Surprisingly, things don’t improve much when we move to smaller-scale operations such as manufacturing facilities or airports. Despite most relevant processes occurring in close physical proximity and falling under a shared administrative structure, the “common operating picture” principle is still rarely applied.

Take, for example, an electronic card assembly line. Multiple digital systems may be in play: ERP (Enterprise Resource Planning) for component procurement, MOM (Manufacturing Operations Management) for overseeing production, and a personnel management system for tracking the operators working on the line. Each of these systems typically has its own dedicated interface, and integrating them often requires a surprisingly high level of effort—even when they’re addressing different aspects of the same physical space.

If facility-based systems were built from the ground up using a GIS-based approach (a scenario that’s becoming increasingly realistic—covered in another section), one could imagine all stakeholders accessing a digital twin representation of the production line, with relevant information flowing seamlessly from the various supporting systems.

This is by no means trivial—but in my experience, there is a significant cost difference between building with integration in mind from the start, versus trying to force integration after separate systems have been allowed to mature in isolation.

The Next Frontier May Be Right Next Door

There are other features of GIS that promise valuable contributions to digital twin systems, which I cover in separate sections. But one of the most critical points to consider is that some of the potential inherent in the GIS-based “common operating picture” outlined here has not yet extended to broader audiences.

For example, the GIS-based collaboration described in the construction scenario is typically limited to professionals and officials. Yet similar applications and datasets hold great promise in non-professional contexts—such as neighborhoods—where residents could make shared decisions around renewable energy solutions across building clusters or collaborate on resource sharing. The challenges of grassroots-style digital twin applications will also be explored in another section, and I believe there is still important work to be done to unlock the full potential of this domain.

I hope this brief outline of GIS and its relevance to digital twins has helped convey why I believe this combination offers tremendous potential for benefit and discovery. Please join me as we explore additional features and examine practical ways to stake a claim in this promising new frontier.