In conversation with Geospatial World, Georg Gartner, a professor of cartography in Vienna, Austria and Abbas Rajabifard, a professor in spatial data infrastructure and modernization of the land information system, talk about the future of geospatial ecosystem and the role of artificial intelligence and big data for map making to improve citizen services.
“Everything happens somewhere, and this geo element, this location element is really in everything. We need to go one step further,” says Georg Gartner, a professor of cartography in Vienna, Austria. He is also a former president of the International Cartographic Association, and he was representing the Academic Network of UN-GGIM
“Location has been actually widely used in response to the pandemic that we all faced as society. And then it also helped all the sectors to better in terms of being prepared and also manage themselves and, in particular, helping the vulnerable society part,” said Abbas Rajabifard, a professor in spatial data infrastructure and modernization of the land information system.
He is the Director of Center for Spatial Data Infrastructure, SDI, and Land Administration in Melbourne University. He is also a former chair of the UN-GGIM Academic Network and currently a member of the advisory board of this network.
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What is the future of geospatial ecosystem?
Georg Gartner: We need to go one step further in terms of going away from technology driven and data driven. We need to become more user driven or use driven that means that we’re going into the knowledge infrastructure. We need to have intelligence about data, about information. The future of geospatial ecosystem is going into knowledge networks, into knowledge infrastructure.
We also need to go further in respect to the functions of what geo is allowing us to do. In which way does that allow us to do what, in respect to decision-making, to planning, to be aware, and so on.
To build a bridge between the technology and what it enables us humans or respectively with autonomous machines, because that might also be a use case or is a use case for geospatial domain as well.
Abbas Rajabifard: What I see as a future of next generation and also as an ecosystem, we will be all part of the same journey. To me, it is a very interesting journey because we are now bringing all the parties together.
We are also incorporating series of technology into this, automations and machine learning in particular, integrating all of those together to create a new series of capabilities which we are experiencing.
And then at the same time, the system keeps getting more mature as a result of our interactions with that. So therefore we are going to have a more exciting future for all of ourselves.
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What is the mission and vision of your organization?
Abbas Rajabifard: We established our organization with a view of how we can empower the societies and governments and, in fact, by leveraging off the location intelligence as an enabler and similar to the other type of infrastructure.
And we work very closely with wider industry definition, which also comprises of government and also private sectors, and of course academia into that mix, to work together to addressing the needs of the societies and addressing the challenges that we face as societies today
Now we are seeing the power of digitalization, which we never actually experienced in the past and in particular before the COVID. Location has been actually widely used in response to the pandemic that we all faced as society.
And then it also helped all the sectors to better in terms of being prepared and also manage themselves and, in particular, helping the vulnerable society part.
What is the evolution of cartography over the years?
Georg Gartner: That’s a success story. Humans have not been forced to make maps. At one point, they came up with the idea of making a map and, since then, it hasn’t gone away.
It’s a success story because a map allows us to holistically understand complex patterns, spatial patterns, and the main function of a map remains constant. So as long as human uses and now also machine uses, there will be a need for producing maps.
Now, what is changing is the way we do it, the technology behind it. What is changing is the easy access to data, so we can produce much more precise maps than ever. What is changing are the attributes, something like that maps are available ubiquitously in real time, that they are adequate to the medium I’m using, if it’s on a mobile phone or on a laptop machine, or if that is an augmented reality device. What is not changing, what remains is that maps are a most effective tool for communication of spatial information.
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How mapping can change digital twins?
Georg Gartner: A digital twin is the same thing as we discussed before, where does that lead us when I’m having a digital twin, so what is the function of it? What’s the benefit of it? So at one point I will need to include also the same procedures in a digital virtual environment.
When I’m trying to make decisions in a digital twin environment, I will also have the same procedures there, that I’m aggregating, I’m filtering, I’m selecting information in a sense that I can make reasoning about it, that I can make decisions about it. So I think it’s actually instrumental to have cartography and maps in the digital twin as well.
What we need to do in cartography when we are making maps, most of the things which we do when we make a map is based on the constraints of humans because I have to look at that map. I generalize, I aggregate, I symbolize, and I lie. Every map lies. It’s not the truth. I’m selecting, I’m generalizing. I make the street big enough that I can see it. Do I need to do the same thing for a machine? The computer can handle the coordinates, all of them.
The question is, “is a map which I’m preparing for a machine, does that have the same cartographic transformation processes, generalization, symbolization, projection?”
All those things, are we going through and in a way, we can learn that. I was very critical at the beginning. I said, “That’s not a map.” But now we can see machines need the same procedures. Not design.
Design is not needed for them, that it’s pleasing. A machine doesn’t need pleasing. It doesn’t need to be aesthetically pleasing. It’s not needed, but it needs to be generalized, it needs to be aggregated, it needs to be brought together to a meaningful set of information. And in that sense, we could argue yes, to answer your question, I would see a future in that respect as well, which I put under the umbrella of modern cartography.
What is the role of artificial intelligence and big data for map making to improve citizen services?
Abbas Rajabifard: It’s interesting what we can now do with all these new technological advancements is to bring in and integrate multi-source live data feed into the system, capture those information, apply in a series of analytics right at the beginning of collections, and then integrating those and bringing a series of new opportunities that we never had before.
Now the capacity of the system is becoming more and more advanced into that, so therefore we are getting better understanding. Also predictions, modeling, forecasting, and then providing a series of simulations that we can actually better experience before even perhaps taking that to action.
