In an interview with Geospatial World, Esri’s Director of Global Business Development Richard Cooke talks about GIS innovations and applications across industries.
Esri leads the GIS technology and location intelligence market, especially with federal agencies, local governments, and Fortune 100 companies. Where does Esri go from here?
The simple answer is, everywhere. Everyone in every industry has something to learn by incorporating geography when making decisions. A geographic approach is no longer solely the domain of GIS departments or government analysts or academics who have long recognized the value of geospatial tools.
This framework for problem-solving capitalizes on what’s now an abundance of data, much of it location-based. We see GIS as a logical foundation for organizing, analyzing, and applying all this data.
The result? Situational awareness, fluid collaboration, predictive analytics, risk mitigation, transparency, the list goes on and on.
There’s a lot of talk about digital twins right now. How is Esri involved in this space, and what industries are you seeing the most interest from?
We believe, as do many of our customers, that you can’t possibly have a powerful digital twin without GIS at the foundation. Only then does everything represented virtually reflect what’s accurate in the real world.
All the assets, systems, operations, and their many interconnections—they all become tied to the one thing they have in common: their physical locations.
Geospatial digital twins are now popular for infrastructure projects. Engineers and planners use them to test a project against various climate scenarios, with an eye on weather extremes. They can model flood levels, for example, or iterate on structural solutions for wildfires or hurricanes. By simulating environmental circumstances, we see how to make adaptive changes in the real world.
How is imagery continuing to play a role in GIS innovations?
Every second, every minute, every day, we as a global society are capturing massive amounts of location-specific imagery from drones, aircraft, and satellites. We’re also collecting even more data from remote sensors. But this treasure trove of data is of little use if it can’t be organized and analyzed.
At Esri, we have engineered an end-to-end system for capturing and processing all types of imagery and remotely sensed data, visualizing and analyzing it.
With all that rich imagery, we can see more and know more than we ever have about our natural and built environments and how they interact. That means near-real-time awareness of what’s happening where, almost like a central nervous system for the planet, as well as how things have changed based on historical observations.
How is Esri building its technology to support sustainability initiatives?
Organizations are under tremendous pressure to be more sustainable. The first step is to determine how and where they can bring their activities into balance with the natural world.
As a technology, GIS is ideal for this work—managing, combining, analyzing, and sharing many layers of data. Take climate risk assessments, for example. No business or government will be successful without first understanding how they will be impacted by wildfires, floods, hurricanes, or extreme heat.
Many organizations are layering their own information on smart maps and dashboards with data from the ArcGIS Living Atlas of the World to pinpoint risks and vulnerabilities. Decision-makers can see, block-by-block, specific climate scenarios.
We are seeing governments and companies develop mitigation measures based on those assessments, like razing buildings or adding green roofs, rerouting resources, and protecting assets. They are also applying a geospatial analysis to investment decisions, carbon emissions reduction initiatives, and supply chain traceability.
What might surprise someone about Esri’s technology?
This wouldn’t surprise our core GIS users, but there are four things I think analysts and data scientists may not know about the spatial analytics capabilities of ArcGIS.
- One: Spatial analytics isn’t just taking spatial data and applying traditional techniques. The methods and algorithms themselves are spatial. This allows us to see how things are changing over time and where changes are most significant.
- Two: ArcGIS technology includes machine learning and deep learning tools to perform quicker analysis, especially as it relates to imagery. This means, object detection, image and pixel classification. A machine trained on what to look for can take in an immense amount of satellite and aerial imagery and give results far faster than any human.
- Three: GIS-powered analysis can be automated to extract insights from big data with unprecedented speed and accuracy, giving analysts more time to do their higher-level work.
- Four: Graph analytics is another new ArcGIS capability that can expose relationships that didn’t otherwise seem related.
And, analysis isn’t valuable until it’s presented in the best way. That’s where visualizations—like smart maps and dashboards—become essential. Together, these GIS capabilities result in real-time, real-world intelligence that can scale across departments, enterprise-wide.
