The future is already here

The future is already here
By Sampo Savolainen and Anita Lankinen, originally published on Geo International Nov/Dec 2016 Issue

Sampo Savolainen and Anita Lankinen look at some of the latest technological advances and analyse how they use spatial data infrastructures, what else can and should be done, and explore what role they will play in our future

Transport agencies, cities and municipalities, environmental agencies, mapping and cadaster authorities – all of these public organisations have been collecting and storing spatial data for many years. However, often companies end up developing their own spatial data infrastructures (SDIs) and creating their core data by themselves instead of leveraging this publicly collected data.

Look at self-driving cars. Instead of relying on available information on road infrastructure, car manufacturer Tesla has mostly relied on sensors to guide its Autopilot system. The sensors are placed all around the car to help the car understand its environment, so that it can safely steer itself in most situations.

Every Tesla car, with or without Autopilot, is connected to the cloud. The company is constantly monitoring and collecting data from each car to create and update its maps. In short, the company acquires all its data through drivers of its cars. As a result, Tesla will have its very own map of the world, built from data collected from the hundreds of sensors embedded in each of its cars. Founder Elon Musk calls this a ‘fleet learning network’, where every car learns from the other. Musk referred to an example of a Californian highway, where the lines are badly marked, which, however, doesn’t affect Autopilot data, as the system uses information from Tesla drivers who have used this section of road. This means that the data Tesla is collecting goes far beyond two-dimensional road maps.

Why not use existing maps?

So why do Tesla and other private companies prefer building SDIs from scratch instead of using data governments were collecting for years? We have come across the following typical arguments for this choice.

Firstly, governmental data is often missing some particular information that is crucial for the private organisation. For instance, TomTom could not rely on base maps to contain information about allowed turns at intersections, so had to collect this crucial information by driving through every intersection in every country in which this information was missing.

Secondly, the update cycle of suitable public data might not match the needs of private enterprises. For example, it might be dangerous for autonomous cars to rely on old data.

Lastly, spatial data is often recorded differently across countries or administrative areas. This is one of major issues the European Inspire directive is aiming to address by developing easily accessible, harmonised data and interoperable infrastructure for spatial information that supports environmental policy-making. Similar goals are pursued by the member of the Arctic SDI – a collaboration between eight national mapping agencies (Canada, Finland, Iceland, Norway, Russia, Sweden, USA and Denmark) to provide politicians, governments, policy makers, scientists, private enterprises and citizens in the Arctic with access to harmonised data, digital maps and tools to assist in monitoring and decision-making in the region.

Moreover, in our experience, it looks like private companies often simply assume that the collaboration with public authorities would end up being too difficult.

But what if there was less friction, greater collaboration and data sharing between authorities and companies could work two ways? What if, say, Tesla shared some of the data it collected with public authorities? The data would be integrated into a common reliable data set and could be shared with more partners. One clear benefit of this would be for autonomous cars: cars from different manufacturers would be able to better coordinate and exchange information that would lead to even safer journeys.

This is just one example of how new technologies would evolve better and faster by sharing more data. It would not be the first time Tesla shared some of its innovations and hard work for the common good, either – back in 2014, it opened its patents for electric vehicle technology to advance the development of sustainable transport. This was not an act of charity either – having more electric cars and charging stations on the market was in their commercial interests.

This makes it even clearer that the quality of public spatial data should be constantly monitored, improved and recorded, and that it should be accessible using common standards across boundaries. Having reliable, good quality data readily available, our cities and countries will become smarter and more interconnected faster, while collaboration between governments and the private sector to build better services would become a natural step to help create more efficiencies. Data is the foundation of smart cities and our improved tomorrow, so we need to make sure it is available when it is required.

Artificial intelligence

In the past few years, artificial intelligence (AI) technology has been commoditized, and is now being used in applications as varied as autonomous cars, Google search and evaluating and categorising produce. This is largely due to advances in AI research such as recurrent neural networks, as well as large software companies opening the source code of the technology platforms necessary for massive data analysis.

Soon, we will reach the point where every building collects and analyses the data about its inhabitants to better serve their needs, every traffic light constantly analyses traffic and reacts accordingly, and waste management is monitored to allow for optimisation, just as well as any other system in a city. The amount of data collected will be so massive, its analysis so complex, the only way to truly process and make sense of all this data will be through AI. This will allow both lower costs due to automatisation of previously work-intensive tasks and new truly innovative products and services.

The cities would need to run several digital applications simultaneously, with SDIs serving as the base on top of which to merge all this data, as location is one of the most intuitive way to connect different characteristics of a specific place. It is interesting to see how companies are already enriching their maps with data from the Internet of Things (IoT). Smartphones are one of the most used sensors, collecting a wide palette of signals and data, and acting as an enormous distributed sensor network.

Google has used the location data of smartphone users to find out what are the most crowded areas in cities. Take a closer look at your city in Google Maps and you will notice that some areas are highlighted with darker shades of brown. This signifies which areas and buildings are hot spots – a tremendous resource for real estate agents and buyers, as well as for tourists who want to visit areas of interest.

Humankind has a great track record in innovation and disruption but historically we have not been able to fully understand the repercussions of our new inventions beforehand. During the early days of the commercial internet, most companies were unable to see the benefits it could offer them and reputable papers were publishing articles proclaiming that e-commerce will never happen.

In 1995, Newsweek said: ‘The truth is no online database will replace your daily newspaper.’ Looking at this quote today highlights not only the power of our inventions but also our nearsightedness in understanding their true value. Just as AI already has been, IoT is now being commoditised quickly; the combination of the two will bring unforeseen advancements and implementations. This is the right time for fearless innovators to take action and seize the moment.

Spatial Data is Never on Holidays

By Kari-Pekka Karlsson, The Secretary of the KMTK Project, National Land Survey of Finland. Originally published in Finnish on (Read the original version here)

Do we realize how widely spatial data is used in our society? Might it be that not even GIS experts know how often we refer to geographical data, although Google and other widely-used map and spatial data services and products have increased the understanding of the importance of spatial data, or maps at least.

Topographical data, often called reference data, is spatial data in its most basic form. This reference data, typically complemented with other datasets, is used as a basis for most of the operations that are based on spatial data.

Some years ago, I did a small survey on the applications the reference data of the National Land Survey of Finland is used on. I was also surprised by the results. It felt like it’s much easier to list the fields where the reference data is not used.

What Needs to Be Improved and Why?

When the data is used widely, it’s important to put constant effort on ensuring good usability of the data. Furthermore, currently the potential of reference data is not fully utilized – partly because of usability issues caused by incompatible datasets.

National Topographic Database Project Focuses on Development Needs

National Reference Database (KMTK) focuses on the following development need: easy-to-access and relevant basic spatial data is needed to make operations in many areas of the society more efficient. KMTK does not solve all the problems but its mission is to create a basis for a better, more efficient future of spatial data usage that the applications of the future can be based on.

Once I heard a thought-provoking comment from a police officer: “The police car does not start driving unless the navigator is working”. That makes perfect sense. In addition to the security sector, reference data is used 24/7/365 for important purposes in many other applications as well.

The mystery of Pokemon Go maps is solved and it’s not just about the street maps

There has been a lot of hype surrounding Pokémon Go lately and also speculation around the source of the map data they are using. It should be no surprise that we, map data geeks from Spatineo, just could not stay away from doing our own little investigation of the maps they’re using.

What is Pokémon Go?

Most of you probably have already heard what the game is about, so we’ll just summarize the idea behind the game: Pokémon Go is a mobile augmented reality game where players use their smartphones to catch virtual Pokémon creatures that can be found in real world places. In case you’ve been a little disconnected from the outside world lately and haven’t heard about the game, just check out their video to see how it works.The game relies heavily on maps to not only show the location of the user, but also to show where you can find Pokémon, Gyms, etc. This data covers most of the world and is quite a remarkable data collection in itself, that is why the source of this map data has become a topic of several recent media articles.

And their maps come from…

An article in The Atlantic was questioning whether the spatial data used in the game comes from the OpenStreetMap or Google Maps, and creators of the game from Niantic declined to disclose this information. So we thought, why wouldn’t we try to figure it out ourselves? We took screenshots of a particular location (in Espoo, Finland) in the game as well as in Google Maps and OpenStreetMap. (Yes, our fellow Finns, while the game isn’t released here yet, we were lucky enough to find a friend who had downloaded the game  from a foreign App Store).

Let’s take a look at this screenshot from the Pokemon Go interface:

Pokemon Go Screenshot 1

Just compare the path in Pokemon Go (circle 1)  with the screenshots from Google Maps and OpenStreetMap. The features in Google Maps and Pokemon Go are identical whereas the turn appearing on OpenStreetMap is missing from the game.

Google Map Pokemon Go

Google Map Screenshot

OpenStreetMap Pokemon Go

OpenStreetMap Screenshot

Now take a look at the building on this screenshot from the game (circle 2) and compare its’ shape on the Google Map and the OpenStreetMap. OpenStreetMap is clearly more detailed, but all this detail is missing from the game.

Pokemon Go Screenshot 2

These images strongly suggest that Pokémon Go uses Google maps as its basemap. On the other hand, Google Maps outsources most of their map data, which makes it at least theoretically possible that Niantic is just using the same original source instead of Google Maps. However, given the fact that Ingress, Niantic’s original map and location based augmented reality game, was developed under Google’s wing, and that Niantic was spun off only as recently as September 2015, it’s safe to assume they might still have a working relationship when it comes to maps.

Given all this information, we think we can call it: Pokémon Go uses Google Maps. Please let us know if you have information otherwise and we can continue our Pokémon hunt.. er.. investigation.

Why are we so excited about Pokémon Go?

Not only does the game encourage people to get active and explore their surroundings, but it also utilizes map data in a very innovative ways. There is much more to the game’s maps than just the the typical street maps we’re accustomed to. Pokémon Go is backed by a large amount of data gathered from different sources like geology, vegetation and hydrology.

Creators of Pokémon Go have put a lot of effort into using data to give context for the different scenarios the players will encounter. For instance you’ll meet water-type pokémons only next to the actual water features (lakes, ponds, fountains, etc). “That gets into more [geographic information system]-type of data … and we utilise that to map Pokémon species to appropriate habitats,” John Hanke, CEO and founder of Niantic, told Mashable. They might have even used Spatineo Directory as one of their sources, since the Directory has the most comprehensive listing of geographical data in the world and is open for all to browse.

What does a happy marriage between map data and gaming lead to?

Well, so far so good – shares of Nintendo, which owns 33% of the Pokémon company and has a stake in Niantic, rose 53% in the three trading days after the release. Meanwhile both traditional and Social Media is going crazy about the game, as well as most of your friends (probably).

To sum up, what Pokémon Go actually does, in addition to being a highly addictive game, is get people interested in maps and spatial data. This kind of game wouldn’t be possible without up-to-date and highly available public maps. With services like Uber and Tripadvisor, using real-time map data has become a part of our everyday lives without us even realizing it. Now GIS and maps are invading our games as well!

If you’re interested in how spatial data is used to ensure the quality of services  – Learn more about Spatineo Monitor


Laura playing

Edit: In December 2017, Niantic finally made the change that all map data in the game would be coming from OpenStreetMap, not Google Maps. Read more about it here!