To many, including myself, the digital revolution is more profound — at least as profound — as the industrial revolution. Allen Carroll, program manager of storytelling at Esri, brought this up when I interviewed him on storytelling with maps. He says that digitization took maps from static to dynamic. This was a key theme at HxGN Live 2017 as well. Each keynote focused on how geospatial professionals can make data more dynamic than it already is. Attendees were encouraged to “think limitless.”
In the geospatial track keynote, Mladen Stojic, president of Hexagon Geospatial, used music as an analogy for geospatial data. Listening to music is a much more dynamic experience than simply reading notes on a sheet of paper. When music is played, layers, patterns and time come together to bring it to life from its static sheet form. “We want to go beyond the traditional static experiences,” Stojic said in the presentation appropriately titled “Escaping the Flatlands.”
Today in the geospatial world, a snapshot of reality is often recorded with a sensor of some sort — one moment in time to experience at a later time. An important focus of many geospatial solution providers is eliminating that delay. When I asked Ola Rollén, Hexagon CEO, what he thought the most significant geospatial challenge is right now, he said “real time.” Yes, it exists already, but a lot of kinks need to be worked out in order to make it seamless, particularly for the driverless car application, which he highlighted. The real world is dynamic and constantly changing; a road that has free-flowing traffic one second can become backed up the next.
Stojic talked about how reality is often broken apart into one layer (GIS, CAD, BIM, etc.). In order to escape the “flatlands,” comprehensive integration is necessary. An important use case for this is the smart city. For example, a city may want to understand the level of noise pollution when considering the building of a new apartment structure near train tracks. Noise pollution can be calculated with GIS layers today, but the approach is static and the information it uses was often collected years ago. Live GNSS feeds combined with analytics can help deliver a more dynamic experience. Bringing a 3D model into the picture is important too, because the noise pollution someone hears is a function of what floor in the apartment building they live on. Adding cinematic and animated features as layers goes even further in creating a model that people can understand.
What I took away from the overall message was: We live in a complex world, and that’s at any one point in time. Account for time and it’s all the more dynamic because it is never the same from one moment to the next. Thinking limitless means figuring out how to use geospatial technology to make models of the world that mirror reality; they can’t just account for one layer of data at one point in time, multiple layers of data at one point in time or one layer of data at multiple points in time. To help solve as many problems as possible, reality has to be essentially recreated. So not only will multiple layers need to come together in harmony, but various computers and sensors will need to communicate continuously to share information.
What macro level geospatial innovations do you think are necessary to help solve important world problems? Let me know!