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February 3rd, 2016
Are we in an era of infrastructure as the leading geospatial application?

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The geospatial technology industry rests on a number of different leading application areas that ebb and flow in terms of their level of investment. Some of the market surges in the past were driven by technological breakthroughs, others were due to federal spending, the emergence of a large market need or a combination of the above. At present, there isn’t a dominant market, but the whole industry is looking to the next in order to drive revenues and shareholder returns.

The market has moved (in no particular order) from forestry to utilities to municipal governance to security/intelligence and infrastructure. With the sequester in place, the security and intelligence market has lost momentum, although it will always be a dominant source of funds in an unstable world. Many different market indicators now point to infrastructure as the next major market for investment and geospatial innovation.

Backlog with Funding

Certainly, you’re aware of the American Society of Civil Engineers (ASCE)’s report card on infrastructure performance. With one of the developed world’s lowest infrastructure investment rates, the United States is well past due for major investments in transportation and water infrastructure. ASCE places a price tag of $3.6 trillion dollars on infrastructure improvements needed by 2020.

Transportation investments in particular have limped along from year to year and entered crisis proportions last summer when federal funding for the Highway Trust Fund was drying up and many states delayed projects for fear of not getting paid. After a few short-term funding bills, the FAST Act passed in early December with a commitment of $300 Billion over a five-year span.

While that figure doesn’t quite reach the ASCE price tag, these funds are significant and the first long-term funding in more than 10 years. A significant portion of the funding is going toward technology innovations such as autonomous technologies and intelligent transportation, both of which build upon a backbone of geospatial technology combinations.

Convergence and Capability

There is a significant amount of investment in the bill to accelerate technology innovations for highways with an aim at congestion management. There is also an investment in positive train control for our railways. Both of these initiatives will put a whole new level of instrumented networks online where sensor feeds and geospatial analysis will provide improved safety and efficiency.

The combination of sensors and systems for better understanding and performance builds on new model-based design tools and our ability to quickly and accurately capture a digital representation of our infrastructure. The growing capacity of LiDAR-based and other mobile mapping capabilities ensures that we have an accurate point of beginning for planning and design. This unprecedented ability to capture complex infrastructure ensures that fewer surprises occur during construction.

Geospatial and CAD/BIM modeling environments are converging in their ability to quickly model detailed infrastructure and to combine these models with real-time inputs and improved simulation and analysis for greater understanding. These are precisely the advancements that are needed for autonomous navigation and other congestion-alleviating tools, where an improved understanding will get us more quickly and cheaply toward the desired efficiency gains.

Coming Changes

Transportation in the United States is undergoing an era of innovation with high-speed rail finally getting funded, autonomous cars from Google sparking a rapid automotive change, and even the promise of the hyperloop spurring thoughts of a whole new transportation mode. This disruption and increasing investment also come at a time when climate change is forcing us to add resilience and adapt, particularly on our coasts.

With the need to change how we approach transportation and other infrastructure, we now have the ability to better design and construct infrastructure. The new model-based approach aids value engineering for the best possible outcome while assuring performance via sophisticated simulation. Knowing what we’ll get for what investment is a critical, if seemingly obvious, first step to unlocking more investments to tackle the backlog.

Geospatial technology, in all various forms and combinations, has a huge role to play in planning next-generation infrastructure. As our maps become more dynamic, with greater sensor inputs on what’s happening now, we’ll get a far better understanding of our infrastructure health to tune its longevity and adapt to coming challenges.

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