Why in 2024 is Geospatial 2.0 so Important

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At the heart of the new Blue Ocean opportunities I discussed is Geospatial 2.0. Credit goes to Josh Gilbert for originally coming up with this term back in 2019 in his article: Approaching Geospatial 2.0: Unlocking billions, across verticals, at scale. Since then I have been evolving the concept.

In this article I want to discuss how Geospatial 2.0 has moved from a technology/data conversation to a commercial discussion, and how it represents a huge geospatial shift.

But let's begin with a definition.

Geospatial 2.0 in 2024

Four years ago I realised we were in the midst of a technology/data revolution. Thanks to new sensors we had begun to collect a tsunami of new geospatial data: imagery, lidar, SAR, hyperspectral, real-time data; below ground, terrestrial and above ground. Terms like reality capture and digital reality were becoming popular. This was also the beginning of the popularization of artificial intelligence (AI). Ground breaking books like AI Superpowers were published shining a bright light on our AI future.

The combination of new multi-dimensional geospatial data (2D, 3D and 4D) and AI to process and analyse that data made me realise that geospatial was moving beyond an abstract representation of the real world (2D maps) to actually modelling the real world (geospatial digital twins).

But in 2020, we were still building out the jigsaw pieces, not all were in place. We are now in 2024, and much has changed. We now have all the Geospatial 2.0 puzzle pieces.

So what are the core elements of Geospatial 2.0 in 2024?

1) Data - There are still a multitude of geospatial data providers, but today we have Google and others who are providing a single access point to a plethora of geospatial application ready data.

2) Platforms - iTwin from Bentley and ArcGIS from Esri have seen incredible advances over the last 4 years. Bentley in particular have embraced Geospatial 2.0 with their acquisition of Cesium, and partnership with Google. But overall, we now have platforms which are making the dream of geospatial digital twins a reality.

3) Immersive Visualization - Immersion was not part of the original Geospatial 2.0 conversation. But the integration of Unreal Engine into geospatial platforms and the release of the Apple Vision Pro and smart glasses respectively have provided a new interface. That is potentially a game changer, as we immerse ourselves in a digital replica of the real world. Both augmented reality and virtual reality will soon be a key part of Geospatial 2.0.

4) Artificial Intelligence & Generative AI - In 2020 AI was the focal point of the Geospatial 2.0 conversation. Two years ago OpenAI announced ChatGPT, and almost overnight the world changed. Generative AI is now with us. The possibilities are endless, and we are only at the very beginning.

As I mentioned earlier, over the last 4 years Geospatial 2.0 has moved from a technology/data conversation to a commercial discussion. That means applying Geospatial 2.0 to solve real world problems.

To help illustrate the incredible possibilities presented by Geospatial 2.0 let's consider a potential use case.

Geospatial 2.0 Transportation Safety Use Case - Diagnosing Causes of Serious Injuries and Deaths at Intersections

1) The Opportunity:

• By utilizing real-time data, 2D maps, and 3D digital twins, authorities can better understand the underlying causes of severe accidents at intersections. This allows for data-driven redesigns and preventive interventions, reducing fatalities and serious injuries.

2) Google Data:

• Google Maps and Street View can provide detailed geospatial data, including traffic flow, pedestrian density, and driver behavior at intersections. By overlaying crash data on maps, transportation analysts can identify patterns, such as which directions or lanes tend to have more accidents.
• Google Earth Engine can also contribute environmental context, such as analyzing the impact of seasonal changes (e.g., snow, rain) on accident rates at specific intersections.

3) 3D Visualization:

• 3D visualization capabilities allow safety teams to build realistic 3D models of intersections and accident sites, including roads, traffic signals, and nearby infrastructure. By visualizing accidents in 3D, teams can analyze factors like visibility, road gradients, and infrastructure elements that may contribute to accidents.
• Integrate sensor data from vehicles and traffic lights, enabling real-time visualization of vehicle movements, signal timings, and pedestrian crossings at high-risk intersections.

4) Immersive Visualization:

• Immersive technologies using Unreal Engine or Unity can recreate accident scenarios in a photorealistic 3D environment, allowing investigators to simulate and explore potential causes of collisions. Traffic planners can visualize how changes—such as adjusting signal timings, adding crosswalks, or altering lane markings—impact safety in real time.
• Immersive simulations can model accidents under different conditions, such as during rush hour or at night, helping authorities design safer intersections.

5) AI & GenAI's Role:

• AI-driven analysis of intersection data can detect hidden patterns in accidents, such as how driver behavior changes with time of day or weather conditions. AI can also automate the processing of camera footage and sensor data to identify contributing factors like speeding, red-light violations, or improper pedestrian crossings.
• AI-powered systems can predict future accidents by analyzing historical accident data and vehicle movement patterns, then proposing preventive solutions such as intersection redesign or optimized traffic signal algorithms. AI can also assist in creating automated risk assessments for each intersection.
• Generative AI could generate design alternatives based on crash data to propose safer intersection designs automatically, while real-time AI analysis could alert authorities to potential risks before accidents happen.

Closing Thoughts

As we stand on the brink of fully realizing Geospatial 2.0, it's clear that this isn’t just a technological evolution—it’s a commercial revolution. From smarter, safer cities to predictive risk management, the ability to harness multi-dimensional data and AI-driven insights is transforming industries. The shift from abstract mapping to dynamic digital twins offers businesses unprecedented opportunities to enter new markets and solve real-world problems in ways never before possible. Whether it’s optimizing transportation safety or developing the next generation of immersive geospatial experiences, the future belongs to those who can capitalize on Blue Ocean opportunities.

Now is the time for businesses to embrace this transformation and position themselves at the forefront of a rapidly evolving geospatial landscape.

Matt Sheehan is a Strategic Growth Advisor helping companies discover and win multimillion-dollar Geospatial 2.0 Blue Ocean opportunities in this new age of dynamic geospatial Digital Twins and AI.