GeoTrends 2017 - Full report

GEO TRENDS
REPORT
The new year symbolises the beginning of new start and
an arbitrary point in time where the earth has completed
yet another lap in its marathon around the Sun. It always
evokes the feeling of a fresh start and change.
Speaking of new beginnings, we at Geoawesomeness have
always loved talking to other GeoGeeks and listening to
their thoughts on where the industry is heading. Instead
of letting these conversations just reside in our private
spheres, we invited them to share their thoughts and vi-
sions with the entire Geoawesomeness community.
We are thankful to each and every one of our guests who
took the time to pen their thoughts and agreeing to be
part of the #GeoTrends idea!
We hope you enjoy reading these thoughts and visions, just
as much as we have. Happy reading!
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TABLE OF CONTENT
What were the 4 key trends in 2016? ..................................................................................................................... 3
Key industry milestones in 2016 ............................................................................................................................... 4
2017 Predictions ............................................................................................................................................................. 7
The Five GIS Trends Changing the World ............................................................................................................. 8
Geo in 2017 ....................................................................................................................................................................... 10
3 trends that will shape Geo Industry in 2017 ..................................................................................................... 11
Next Generation of GIS is here! ................................................................................................................................. 12
What will happen across the Geo Industry in 2017 ........................................................................................... 13
8 Crazy Predictions for Geospatial in 2017 .......................................................................................................... 14
The Essential Element for Location-based Games in 2017 ............................................................................ 16
2017 – The Year Of Collaborative Mapping .......................................................................................................... 17
Geospatial Rising and Falling Stars for 2017 ....................................................................................................... 18
Geo behind every corner, even if you don’t expect it ...................................................................................... 21
Artificial Intelligence set to accelerate in 2017. Pieter Gillegot-Vergauwen, VP Product
Marketing, TomTom ....................................................................................................................................................... 24
The future of Earth Observation .............................................................................................................................. 25
6 location trends to watch out for in 2017 ........................................................................................................... 26
4 trends that will revolutionise the drone mapping industry in 2017, Aleks Buczkowski,
Editor-in-chief of Geoawesomeness ....................................................................................................................... 28

KEY INDUSTRY MILESTONES IN 2016
JAN 16, 2016
FEB 19, 2016
MAR 3, 2016
APR 20, 2016
MAY 13, 2016
Founder and CEO of Foursquare
Dennis Crowley steps down as the
company seeks to restart growth
According to FAA rule all hobby
drone owners in the US must be
registered.
PrecisionHawk raises $18M to bring
drone safety to the next level
Mapillary – the crowdsourced
Street View start-up raises $8M
Apple invested $1 billion
in Dixi Chung - Chinese Uber
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MAY 19, 2016
Apple opens Maps production
unit in Hyderabad, India with
4000 employees
Pokémon Go, the location-based
augmented reality game developed
is released and in a few month gets
500 million downloads.
Lenovo announced the first phone
with Google Tango
Uber quits China and sells business in
the country to its rival Didi Chuxing
PwC - one of the biggest
consulting companies in the
world goes live with its drone
mapping unit
MAY 24, 2016
JUN 8, 2016
JUL 6, 2016
AUG 1, 2016
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SEP 19, 2016
OCT 18, 2016
DEC 19, 2016
TripAdvisor – one of the largest
online hotel booking platforms,
acquired a popular mapping app
Citymaps
Google acquires Urban Engines to
better understand location-based
big data
After 17 years of development & delays
European GNSS - Galileo is finally live
(although not fully operational)
Alibaba invests in PlaceIQ – loca-
tion-based targeting start-up
AUG 24, 2016
06

THE FIVE GIS
TRENDS THAT
ARE CHANGING
THE WORLD
“The geospatial industry is quickly
evolving because the capabilities
of digital connectedness and
collaboration are moving ahead
exponentially. In fact, the five biggest
trends in the area of geographic
information system (GIS) technology
are centered on making data more
accessible and creating context to
visualize this data in an age when
fast, easy access to information is
taken for granted.”
JACK DANGERMOND
President, Esri Inc.
Maps are a simple and efficient way to understand and communicate
rapidly. Looking at a spreadsheet, we see rows and columns of data.
Using charts and graphs, that data can be seen as a pattern. But when
that same data is presented on a map, we suddenly have context for
the information. Because most of us are already familiar with
geography, when we see data as a map it is usually understood
much faster. We are now at a stage where we can display 3D imagery
and information on the web very easily. Web-based 3D visualizations
are everywhere, and maps are among the most common
manifestations of this.
At Esri, we are investing in things our users want at scale, while
still keeping abreast of the cutting edge. The geospatial industry is
quickly evolving because the capabilities of digital connectedness and
collaboration are moving ahead exponentially. In fact, the five biggest
trends in the area of geographic information system (GIS) technology
are centered on making data more accessible and creating context to
visualize this data in an age when fast, easy access to information is
taken for granted.
1. Location as a Service
There was a time when GIS use was limited to the niche market of
government, telecommunications, utilities, and oil and gas sectors.
That market has grown substantially, as large retailers and tech
startups have seen the benefits of understanding data geospatially.
The fundamentals of GIS and what it can do have also evolved
dramatically. We are entering an era of services-based GIS. This means
the GIS professional connects with consumers directly through
web-based applications that provide easy-to-access visualizations.
GIS also has huge implications for the enterprise user at a business or
a city organization, where departments have enormous amounts of
geographic data. Performing spatial analysis on the web and having
access to distributed servers where different layers of data exist allow
users to bring this data together, fuse it, and analyze it across the
network.
2. Advanced Analytics
Spatial analysis is important to any business that values location
as a variable to success. Site selection is a crucial function that is
dependent on geospatial analysis. A retailer that wants to set up new
stores needs to understand where there are existing successes for
similar ventures as well as hospitable demographics. All this data can
be overlaid onto a map to perform statistical analysis in order to make
a decision about the location of a new store. Maps communicate this
information well, and in a web services environment, professionals will
be able to make maps, graphs, and charts and perform analytics easily.
Accessible from an organization’s cloud, the power of GIS and
mapping is opened up across the enterprise.
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3. Big Data Analytics
The ability to access the vast amounts of data that provide us with insight into the environment and
human behavior has changed the way all organizations function. That capability has also evolved to
include the integration of big data operations into spatial analysis. Today, anyone in the enterprise can
access billions of environmental observations or tens of thousands of raster images from spacecraft
and analyze them easily. This will greatly expand what traditional GIS has done. Enterprise users can
now build their own imagery and raster analytics workflows for fast, multi-CPU, parallel processing of
massive imagery collections.
3. Real-Time GIS
The world of citizens and consumers is already interconnected digitally—people are connected with
each other and with their governments and businesses. Leveraging this vast network of devices and
sensors is perhaps the latest trend and the number one priority for organizations that want to remain
ahead in terms of having a comprehensive enterprise GIS for the future. Everything from smartphones
to crowdsourced social media feeds is being used to integrate real-time data from the Internet of
Things (IoT) directly into a GIS layer stack, where the data is analyzed, visualized, and reintegrated
into online applications for use by either professionals within the enterprise or by consumers and
citizens.
4. Mobility
Another way GIS is breaking out of its traditional space is by becoming more consumer-friendly.
Just as data from mobile devices is liberating professionals and consumers who’ve been accessing
GIS online and from the desktop, this same data is being used to power a new generation of easily
accessible applications that tap into the rich science and analytics that only GIS can deliver. A much
simpler user experience is now possible for GIS users with the creation of a suite of apps and app
builders. iPhones or Android devices can be used to collect geospatial data or explore it visually,
anywhere and at any time. Professionals in the field can use these apps for data collection or as
observational data, which they can then bring directly into an enterprise services environment in the
cloud. Field information is immediately input and analyzed.
Creating Big Understanding from Big Data
The last leap in computing was the shift from the server to the cloud. Software as a service (SaaS)
opened up a world of opportunities for GIS, as shared map services like the World Imagery Basemap
are no longer separate from the unique services offered to users. GIS users can share data,
collaborate, make mashup maps in the server, then connect to the cloud.
The next leap in GIS technology and computing is connecting to the vast network of devices provid-
ing data in real time. It is the most revolutionary change we have seen since Esri began and brings
great opportunity. The more accessible data is, the more important it will be to understand it. And
maps are the visual language for understanding the context of data.
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GEO IN 2017
“The next 1 Million users to start
using geospatial technology in
2017 will not even know what
GIS is. Location Intelligence will
be delivered seamlessly via their
apps, embedded in Data Analytics
space, as a new software segment,
or integrated on general purpose
tools and platforms.”
JAVIER DE LA TORRE
CEO, CARTO
The geospatial industry overall will continue growing strong in 2017.
Some big trends like IoT, Self-driving Cars, Location based Consumer
apps and space will keep pushing the industry to new areas.
The separation between different areas in the geospatial industry will
become more apparent. GIS will remain niche, but I expect strong
growth in the Data Analytics space and Location Based Services
(LBS). The usage of geospatial technology will increase very signifi-
cantly within enterprises as they continue to become more data-driv-
en; this will help solidify the Location Intelligence segment. The next 1
Million users to start using geospatial technology in 2017 will not even
know what GIS is. Location Intelligence will be delivered seamlessly
via their apps, embedded in Data Analytics space, as a new software
segment, or integrated on general purpose tools and platforms. This is
the segment where CARTO will be focused the most.
In terms of specific trends within the geospatial community, I believe
the following things will happen or continue happening on 2017.
• Commoditization of Location Based Services with value-added
services on top of traditional LBS.
• OSM and Open Data will keep getting space and will become the
inevitable 3rd option after Google Maps and Apple Maps.
• GIS will capitalize on IoT trends, but will be replaced often with
software capabilities on other products.
• More and more products will include geospatial technologies
taking it mainstream. Concepts of Spatial Analysis will be more
natural to a much larger audience.
• Predictive analytics on Spatial Data will start becoming much more
common and Machine Learning techniques will be much more
clearly applied to Location Data.
• Some core companies will continue absorbing incredible geospa-
tial talent (Uber, Google, Facebook…) and startups (like CARTO!)
will specialize in certain type of analysis and data.
• We will likely continue talking about counting cars in Walmart
parking lots from space.
• There will be more technology sector consolidation in 2017 than in
2016 as different platforms keep adding spatial capabilities and big
companies augment their pool of talent.
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3 TRENDS THAT
WILL SHAPE GEO
INDUSTRY IN 2017
“2017 might be the year where
we see more machine-generated
edits to maps than human edits.
With constant improvements in
deep learning technology, we may
soon get to a point where digital
editors are annotating maps more
efficiently than teams of humans
ever could.”
JAN ERIK SOLEM
CEO, MapillaryWhat we’re seeing now is that automotive companies are becom-
ing major players in the mapping ecosystem and are shaking up the
industry. It’s a time of rapid innovation, which will motivate some of the
predicted trends below.
1. Automotive mapping takes off
The automotive industry has huge momentum right now and will
continue to be a driving force behind the evolution of maps (pun in-
tended), motivated by the development of connected and self-driving
cars. Up to this point, digital maps have only been vitally important for
a few use cases, and have been simply convenient for the majority of
the population. But with self-driving cars, digital mapping will become
indispensable to a much larger population.
2. Deep learning and AI
2017 might be the year where we see more machine-generated edits
to maps than human edits. With constant improvements in deep learn-
ing technology, we may soon get to a point where digital editors are
annotating maps more efficiently than teams of humans ever could.
This will be especially important as we look to extract as much useful
data from digital photomaps as possible.
3. Lots of outsiders
In the GIS industry, you’re only as good as your data. The gap between
the big corporations that have data and the smaller ones that don’t
will grow over time, because good data collection requires substantial
resource allocation. The more their datasets become dwarfed by other
companies’, the more independents and small players may struggle in
2017.
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NEXT
GENERATION
OF GIS IS HERE!
“Integrating IoT data, mapping
drone information, analyzing
imagery from small sats – GIS is at
the root of these technology trends,
and we are only beginning to really
understand how these new sources
of information can help us make
better decisions.”
ANDY DEARING
CEO, Boundless
It’s no secret organizations today have access to more data than ever
before, and it only continues to grow at an astounding rate. Now the
problem is not gaining access to the data, it’s the ability to scale and
process such large amounts to help solve business problems. After all,
the data is meaningless if we cannot make sense of it. Location-based
data is no exception, of course.
There are many breakthroughs and success stories in the geospatial
industry right now that are propelling the science forward more rapidly
than ever before. Integrating IoT data, mapping drone information,
analyzing imagery from small sats – GIS is at the root of these
technology trends, and we are only beginning to really understand
how these new sources of information can help us make better
decisions.
Open source technologies, which continues to proliferate in modern
IT enterprises, have become an essential component for gathering,
organizing, and connecting the dots between vast amounts of the
spatial data at our fingertips. Open source enables organizations to
harness limitless scalability to understand and solve emerging business
challenges.
With the emergence of machine learning concepts, geoprocessing
techniques can be applied to make sense of data streams and “big
data” architectures. Organizations are not only understanding the
“what” behind location content, but now also understand the “why.”
The ability to gain deeper insights into change detection, trend
analysis, and predictive modeling will take hold in these open, elastic
infrastructures.
This is a great time to see the next generation GIS taking shape and
what it will become in the years ahead.
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WHAT WILL
HAPPEN
ACROSS THE
GEO INDUSTRY
IN 2017
“The value of the ‘where’ is fueling
innovation and entrepreneurialism.
Last year we saw the fusion of
augmented reality and geospatial
data creating the global
phenomenon that was Pokemon.
In 2017, we’ll continue to see an
explosion of augmented reality
apps based on location context.”
TIM BARBER
VP Software Solutions,
Pitney Bowes
The number of connected devices is skyrocketing, with Gartner
forecasting figures to reach 29.5 billion by 2020. The Internet of
Things or IoT – this intricate, hyperconnected web of integrated
devices – generates a wealth of geospatial insight thanks to powerful
sensors which transmit the devices’ locations. These sensors enable
the collating and tracking of in-depth, real-time location data: a
gold-mine for organisations wanting to get closer to their customers;
to deliver location-based customer engagement strategies; and to
make strategic decisions based on precise, accurate spatial analytics.
McKinsey forecasts the IoT has a total potential impact of 11% of the
world’s economy. As it snowballs, we’re likely to see an increase in the
application of location data, as the two are intertwined: every sensor
data point or mobile transaction happens somewhere. And social
media platforms place more emphasis on graphics and visuals, so
generating maps as visual representations of data becomes more
important and popular than ever.
The value of the ‘where’ is fueling innovation and entrepreneurialism.
Last year we saw the fusion of augmented reality and geospatial data
creating the global phenomenon that was Pokemon.
In 2017, we’ll continue to see an explosion of augmented reality
apps based on location context. We could also see more ‘asset-light’
organisations – driven by geospatial analytics – pop up to meet the
critical consumer objectives of speed, convenience, and value. These
organisations are appealing to consumers- with- a-conscience by
using geospatial data to formulate ethical, sustainable businesses, such
as FoodLoop, which connects consumers with short shelf-life products
and targeted real-time offers through its mobile app, so I anticipate
more of these over the next 12 months. Smart cities, too, are built on
sustainability, and the ability to extract geospatial analytics to drive
successful outcomes has a key part to play in their roll-out, more of
which we expect to see in 2017.
We expect to see more of location intelligence as an enabler unique to
different industries: enabling precise drone delivery to pinpoint spe-
cific addresses for Ecommerce deliveries, for example, and a real-time
location aware dimension in the financial services sector to improve
engagement and the customer experience. We could also see more
interest this year in geospatial data analytics from the telecoms and
mobile industries as 5G is tested and carriers perform terrain data
analysis and visualisation.
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8 CRAZY
PREDICTIONS
FOR GEOSPATIAL
IN 2017
“Let’s get crazy. None of your
safe boring predictions. No
going off into outer space either.
Reality. At least our sense of
reality.”
MATT SHEEHAN
Founder, WebMapSolutions
1. Continued hype around drones, augmented reali-
ty and anything shiny and new.
I yawn each time I see predictions talking up the new shiny geospatial
toys. Sure drones will help cut the cost of data collection, and 3D and
augmented reality will give us a more realistic view of our world. But
the ‘shiny and cool’ out-weighs significance in terms of use-age. That
hype will continue ad nauseam.
2. Mobile GIS is dead.
We’ve been surprised. Mobile GIS has been super slow to take off. We’ll
put our neck’s out and say mobile GIS is dead!
All device GIS will be our 2017 reality. What do we mean here? Web
apps: GIS applications which run on any platform, on any device. So
take the GIS app you are using on your office PC. Run that same app
on your laptop, smartphone, tablet. With GeoAppSmart for ArcGIS,
we’ve gone as far as to offline enable a Web Appbuilder for ArcGIS like
widget based web framework. Web GIS is truly about GIS anywhere,
anytime, on any device. We’ll see an increasing emphasis on all device
GIS web apps in 2017.
3. Greater demand and competition in the BI-GIS
space.
The release of Insights for ArcGIS moves Esri squarely into the BI
space. Sure its not a BI product, but is designed to be used in part by
BI professionals. We would have liked the first release to have been
part of ArcGIS Online to maximize the potential reach of the Web app.
We hope Insights is like Business Analyst: easy, simple, powerful. But
that said non-traditional, particularly commercial, organizations are
recognising their need to answer ‘where’ questions. In our ArcGIS Solu-
tions Pyramid, many of the questions being asked sit in tier 3 (calcu-
late and build map) and above.
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BI professionals are now learning GIS. We believe there will be more competition in the BI-GIS space
as demand increases for location analytics and location intelligence.
4. Dramatic increase in demand for GIS professionals.
Did you catch the comment in point 3 above?
“BI professionals are now learning GIS”.
That’s both a threat and an opportunity as we move into 2017. The demand for geospatial profession-
als will grow. But not for ‘map makers‘, for those who can think through complex business problems
and apply GIS and geographic methods to provide solutions. Geo-data scientists will be an emerging
group. Those of you working in the commercial sector will be particularly valuable, since you are al-
ready applying GIS to solve business problems. In 2017 we believe the value you bring to your organi-
zation will start to be better realised. From peripheral to the success of your organization, to central.
5. More focus on solving problems
There are many signs that the adoption of the newly emerging geospatial technologies has been
slower than hoped or expected by the main vendors. That is the reality of new tech. Organizations
cautiously move forward. With GIS we have 2 groups: existing users of GIS, and those new to the
technology. For both groups we saw 2016 as a Year of Geospatial Growing Pains.
What organizations want from GIS is solutions to problems. That means an emphasis on solving. We
think in 2017 sellers of GIS software will look to forge stronger relationships with service providers;
partners or those aligned closely with vendors. GIS is complex, client success is more than a simple
software sale. Partners are focused on solving client problems applying vendor software. Building
solutions, demonstrating value. The winners of the increasingly competitive GIS technology landscape
will be those with the most connected, incentivized partner communities.
6. From complex, and expensive to easy, affordable, does exactly what is
needed.
This prediction really focuses on choice. There are many large, focused GIS-centric solutions in the
marketplace today. As an example asset management. In the public sector, managing assets using GIS
is important. There are a number of big, complex, expensive solutions on the market. Great for large
organizations (with deep pockets). Not so good for medium to small. We will see in 2017 the release
of light-weight solutions which are easy to install, configure and use. Competitive pricing, flexibility
and extensibility will also be baked into these new releases.
7. Wider adoption of (new) Web GIS.
Let’s first define Web GIS:
ANY GIS THAT USES WEB TECHNOLOGY TO COMMUNICATE BETWEEN A SERVER AND A CLIENT.
Web GIS is in essence a move towards fully networked GIS. Sure server based GIS was a form of Web
GIS. But with the new GIS platforms being released, we now have everything connected via web tech-
nology. As an example, the desktop based ArcMap is now connected to ArcGIS Online. So you can
publish your maps directly to the cloud for all to see.
As we mentioned in our 2016 A Year of Geospatial Growing Pains those familiar with GIS still need
to grow their skills to take full advantage of Web GIS. They need to understand better the potential
impact Web GIS will have on their organization, and find the time, or get help, implementing new Web
GIS solutions. We think there will be wider adoption of Web GIS among traditional GIS sectors in 2017.
We have some concerns around those new to GIS. There has been much discussion that GIS is now
quite different; publish your data, map it, drop it in a COTS (commercial off the shelf) app and you
are good to go. In short that GIS has become easy. Nothing could be further from the truth. The GIS
users experience should be intuitive, that is (and always has been) true. But those responsible for the
GIS still require a geospatial background. See our blog post 4 ArcGIS Hits and Misses (and what we
learned) for more thoughts here.
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THE ESSENTIAL
ELEMENT FOR
LOCATION-BASED
GAMES IN 2017
“The future of location-based
games will be dominated by
those who take advantage of
the on-demand contextual data
available on each user’s device.
The mixing of each individual
user’s reality with the overall
fantasy of the game will not
only make for more engaging
games but far more personal
experiences.”
PETER WITTIG
Co-founder, Motive.io
Think about where you are right now. Are you at home, at work or out?
What are you near? Have you been there before? What time is it? Is it
sunny, snowing, raining? How much of that does your mobile device
already know? All of it and more. If your device knows it, your game
can know it too.
Context is the essential element for location-based games and
experiences. Having on-demand access to contextual information like
current location, location history, people or places closeby, weather,
date and time makes the mobile device unique compared to
other platforms. I would argue that it is context-aware games that will
succeed in the future. While location is a big part of context, location
alone is not enough. If you aren’t using location & context in your
mobile game, it might be better on a platform with a larger screen.
Let’s consider movies vs theatre as an analogy. Movies, like PC or
console games, have complete control over their environment. The
perfect scene, sound and dialogue can be arranged because of that
control. However, that means it is static and lacks the ability to be
spontaneous based upon what is happening in that moment for a
given viewer.
Now think about an improvised theatre performance in a public
square. It needs to be ready to deal with ambiguity and change.
Maybe it is a foggy day or maybe a construction project necessitated
a change in location. The actors have the ability to personalize the
experience for each new audience because they understand and share
their context. Location-based games have this ability as well.
The future of location-based games will be dominated by those who
take advantage of the on-demand contextual data available on each
user’s device. The mixing of each individual user’s reality with the
overall fantasy of the game will not only make for more engaging
games but far more personal experiences.
Future location-based game developers: Don’t design a PC or
console game and then decide it should be location-based. Build your
experience around being away from a computer. Get outside and test
early and often. Use the myriad of sensors on a mobile device to get
contextual data when you need it. Personalize your game to each user
based on their context. Embrace the ambiguity and change of the real
world in your game and you will succeed.
16

2017 – THE YEAR
OF COLLABORATIVE
MAPPING
“ It has never been easier to
take the idea of GIS and mobile
data collection to more people
in organizations, as so many
are educated by basemaps and
games like Pokémon Go!. The
key requirement is GIS that can
actually deliver such simple, easy
and high-quality user experience to
enterprise users.”
DINO RAVNIĆ
CEO, GIS Cloud
Throughout the years, maps have become a commodity. Simple
mapping services providing basemaps and simple API have enabled
thousands of lightweight location-based applications. Many of them
are consumer oriented e.g. Uber, Foursquare, Google Maps, etc. In es-
sence these are all GIS applications and many users are actually doing
GIS even though they don’t know what GIS is or what it stands for, and
how it can help them in their professional lives.
The latest geo phenomenon of how simple mapping can be brought to
the masses is one of the most viral apps of all time: Pokémon Go! This
game demonstrated endless opportunities for utilizing geo technol-
ogy and bringing it closer to end-users. Millions of people are using
their phones to play this game, but actually they are also surveying the
world and doing data collection. It has never been easier to take the
idea of GIS and mobile data collection to more people in organizations,
as so many are educated by basemaps and games like Pokémon Go!.
The key requirement is GIS that can actually deliver such simple, easy
and high-quality user experience to enterprise users.
At the same time, we have so many legacy GIS installations and silos
across so many organizations. Data is still being locked on many work-
stations and closed networks. More of these systems will be extended
with new GIS platforms that integrate, but also unlock and extend data
to more seats. Field workers require a real-time system to do their
work and they want to use their mobile phones. Various departments
have a need to access and share data. Decision makers require instant
access to maps from their phones or tablet devices. Not to mention
the community that can also be included in the process, not just to
view maps, but also to contribute. We need GIS to scale.
We at GIS Cloud are focusing on the next generation of GIS where
such technology will be available to more users, so that data could be
better organized, shared, built and accessed by those that need it, at
any point in time from any place. We are building real-time mapping
platform for the entire workflow of your organization.
These are our predictions for 2017:
True Collaboration
OpenStreetMap, as the biggest real-time collaborative mapping proj-
ect, showed what’s possible when a map is being built in a collabora-
tive way. More than 3 million registered users are contributing to this
cloud project and making real-time updates to the map at a speed no
proprietary map vendor can match. In the long run, the only sustain-
able way to map the ever-changing world is to collaborate and include
as many people as possible.
The same notion and workflow is being transferred into GIS. Maps must be
collaborative by default, they shouldn’t be built and maintained just by the
GIS department or locked on a certain workstation. Instead, the whole orga-
nization internally, or even externally, should be included. These users will
not just access a map, but also contribute in building it. The only way to map
the ever-changing life cycles of organizations is to include as many people
as possible.
17

GEOSPATIAL
RISING AND
FALLING STARS
FOR 2017
“In a world with self driving
cars, artificially intelligent home
assistants, and popularity of games
like Pokemon Go, the world of GIS
and Location Based services is on
a convergence path with macro-
technology trends.”
RYAN GOODMAN
CEO, CMaps Analytics
In 2017, we will see continued growth in geospatial technology in all
forms. The technological advancements we are experiencing on a day
to day basis is helping advance new waves of clever innovations for
enterprise. In a world with self driving cars, artificially intelligent home
assistants, and popularity of games like Pokemon Go, the world of GIS
and Location Based services is on a convergence path with mac-
ro-technology trends.
Rising Solutions for Enterprise
Indoor and micro-location intelligence
Leading up to 2017, we have seen a huge emphasis on geospatial /
mobile engagement for retail and mobile marketing. However, there
are less visible successes in the world of automation and optimization
for manufacturing, logistics, and healthcare. Real-time fencing and
large scale asset engagement will mature as asset and traffic dense
spaces foster new innovations beyond the one-way communication
mechanisms that sparked the location based services market.
As I mentioned in the introduction, this is a key area where I see geo-
spatial data and technology converging with machine learning, IOT,
and big data analytics. One company that has publicly demonstrated
its mastery of this is Amazon within their warehouse operations.
Expansion of Location Analytics Scenarios Beyond
Full Stack GIS Platforms
Location Intelligence and was once relegated to a finite number indus-
tries and scenarios where it made sense to invest in GIS technology
and skills. In 2017, those skills are critical, but will require professionals
to broaden their horizons into new areas. One of my favorite champi-
ons for this revolution for GIS is Matt Sheehan who also contributed his
2017 predictions. In 2017 lines of business like sales, marketing and HR
18

(not traditional GIS users) will ask more sophisticated “where” questions as they pertain to their jobs,
requiring modern breed of business user and analyst friendly solutions. Most enterprise analytics tools
will continue to commoditize a broad set of geospatial analysis and visualization capabilities. Howev-
er, there is still a need for more advanced, customized solutions and there is no shortage of commer-
cially available geo-analytics platforms like Carto and the embedded geo-analysis APIs work we do at
CMaps Analytics.
(not traditional GIS users) will ask more sophisticated “where” questions as they pertain to their jobs,
requiring modern breed of business user and analyst friendly solutions. Most enterprise analytics tools
will continue to commoditize a broad set of geospatial analysis and visualization capabilities. Howev-
er, there is still a need for more advanced, customized solutions and there is no shortage of commer-
cially available geo-analytics platforms like Carto and the embedded geo-analysis APIs work we do at
CMaps Analytics.
New Gold is Big Geo-Data Products
For example, high resolution aerial photography and the machine generated data (sensor and image
post processing based) will create a new wave of interesting business and analytics driven solutions
for construction, mining, utilities and other industries. While these techniques and technologies have
been around for a while, the expanding commercial drone industry and platforms forming around
these solutions will allow organizations that operate at massive scale are creating powerful derivative
data products. Both community and commercial initiatives will form and we are already have success
stories to bench mark. The first example of 2017 already dropped from Uber, who released Movement,
a data product which demonstrates what is possible from mining massive volumes of data to provide
derivative information/data products.
Lead Distribution Analysis with CMaps Analytics
19

Losing Steam in the Enterprise
While these new trends picking up steam some past year’s trends will flatten or slow down, pending
any new innovations that come up this year.
GIS on BI
The first wave of embedded GIS in BI solutions were either too complex for IT stakeholders to
maintain or resulted in simple integrations that lacked important geospatial data and functions
that makes GIS so useful. As GIS on BI lost steam, some GIS vendors like ESRI took the bull by the
horns to develop their own analytical tools which looks quite promising. It’s still too early to tell
if they have a hit on their hands, but we will should have an idea the deeper we get into 2017.
Google Maps Losing Steam in Enterprise
Google is a force in consumer apps and mobile, but has lost ground in enterprise to open-source
and commercial platforms. From MapBox, ESRI and IBM, to a recent announcement with Microsoft,
HERE, and TomTom, Google Maps is the one missing mapping provider from a lot of recent enterprise
partnerships. Google Maps provides an exceptional cost/value proposition and has mountains of data
that it can mine for geospatial services. It will be interesting to see if there is a resurgence in Google’s
marketing and release cadence for enterprise class geo-services in 2017.
“Location Intelligence” Tag
While the term “Location Intelligence” is popular among industry pros, a large portion of enterprise
stakeholders are not actively searching for “Location Intelligence”. Looking at recent Google trends
Twitter activity I was surprised that this term is not a blip on the relative geospatial social-sphere.
With that said, as the pervasiveness and importance trends mentioned above grow, we could see
higher awareness of related terms.
20

GEO IS
BEHIND EVERY
CORNER, EVEN
IF YOU DON’T
EXPECT IT
“Is “GIS is everywhere” a redundant
statement? Aside from the rather
poor (though literal) pun, I argue
that it is redundant. I propose that
GIS is currently going through a
renaissance period of explosive
growth, though perhaps not in the
most obvious of ways.”
ERNEST EARON
Founder & CTO, PrecisionHawk
Is “GIS is everywhere” a redundant statement? Aside from the rath-
er poor (though literal) pun, I argue that it is redundant. I propose
that GIS is currently going through a renaissance period of explosive
growth, though perhaps not in the most obvious of ways.
To the greater public, at least those who are aware of what ‘GIS’ is, the
field often seems to be highly specialized, complex, and niche. It is the
domain of highly skilled technical people using sophisticated tools to
track, catalog, and (ideally) understand the world as it unfolds in space
and time. While that is definitely a big piece of what is happening, we
are also in a transformative period where ‘GIS’ is being incorporated in
a myriad of often subtle ways that are changing both what and how
we know. What is happening is that applications and use cases for
spatial and temporal information and analysis are appearing in great
numbers at a faster rate than ever before. As such, core techniques
and technologies are being isolated and applied everywhere.
This is being driven by several factors:
1. Consumer Demand
This is likely both the biggest, and the most subtle, driver for the wide-
spread use of GIS technology. It’s also where the general public might
look and say “That’s GIS? Cool.”
This is very much akin to how computational vision processing went
from being the rarified, specialized domain of PhD’s in university labs
(and a tremendous mouthful to start a conversation at a party with),
to something that is virtually taken for granted now. Look at how your
camera or smart phone can automatically detect faces in a scene,
maximize the number of faces in that field of focus, and even trigger
the shutter when people smile. The same holds true for how those de-
vices attach metadata to those images. Cameras (whether in a phone
or stand-alone) now commonly contain a GPS device to tag photos so
that they can be more readily cataloged and queried later. While you
might say that that’s hardly high-grade GIS technology, it is applying
spatial and temporal information to other data to improve the end use
or workflow. This might be a somewhat trivial example, but is hardly
the only case where consumer applications is driving this technology.
Aerial imagery and drones are another great example. GIS for process-
ing, analyzing and storing this information are a critical requirement.
While a live-streamed video of a snowboarder going down a half-pipe
might not immediately strike one as needing this technology, being
able to effectively replicate the route or reconstruct a 3D model of the
course does.
21

Certainly when using drones to collect aerial imagery GIS techniques are paramount. Anyone who
has looked at 750 sequential aerial images of a corn field knows that that is not a useful format for
the data. It is not just critical to be able to properly create a rectified, accurately referenced mosaic,
but something needs to be done to process and extra useful information from that data set. Anything
from hydrology models to timber inventory estimates.
2. Technology (COLLECTING AND COMPUTING)
Drones are not just a key piece of the puzzle because they enable a new data collection method.
They are also a great indicator of a larger trend: that of rapidly improving technology at an
increasingly reduced price. This not only puts aerial imagery capabilities in the hands of anyone
from pre-high school kids all the way through to large existing manned aerial servicing outfits; it
also is increasing the number of sensor modalities those people have at their disposal. 5 or 6 years
ago Tetracam was pretty much it for low cost multispectral imaging. Now there are easily a dozen
options on the market, and more are coming. Alongside this, the performance and cost keep
improving. This driving even more applications and more data collection to be undertaken.
Computer resources are also continuing to improve. The Internet of Things movement has seen
tremendous growth in embedded controllers and signal processing capabilities. This allows
processing solutions to be embedded, speeding up the time-to-use of the data, and enabling more
and innovative use cases.
Indeed, the commoditization of all of the technologies involved is opening a great many more
opportunities and applications.
Lead Distribution Analysis with CMaps Analytics
22

3. Commercial and Industrial Applications
Another key feature driving the growth of GIS, is the expansion of commercial and industrial
applications for the data (for the record, this is hardly an exhaustive list of the thing making GIS
technology a must-have for the remainder of the 21st century and beyond. It’s really just a few
examples).
The examples above have really enabled and demonstrated the disruptive power of knowing more
about the right place at the right time, and companies are rapidly focusing efforts to harness that to
improve their business. Drones are a great example here, too. While 10 years ago using a small robotic
aircraft to do routine automated storm damage assessments would have seemed ludicrous, it is not
accepted as critical to best-practices going forward. Companies large and small are rapidly standing
up and heavily investing in groups to make this a part of business as usual.
Making remotely sensed data a standard part of your operating model is simply accepted.
Of course, right alongside this is a huge need to build the techniques and implement the tools
to make use of that data. Algorithm development is now moving at a pace we haven’t seen since
satellites came on the scene. In fact, it’s unprecedented and is dwarfing the to date. Now that
everyone can collect the data, and everyone needs it, it’s clear that GIS and remote sensing is
in a bit of a golden age. Albeit a tremendously busy one.
The other feature that is consistent through all of this, and what is making this truly a standout
period, is that all of issues are reinforcing each other. People are simply expecting better performance
and results that require GIS analysis; the tools to collect more data that needs to be analysed are
cheaper than ever; the applications for the data are exploding; and businesses are demanding more
of it.
While it is difficult to predict what this will look like in 10 years, it is clear that the widespread
solutions will not be driven by analysts in front of workstations. Instead, it will be tools and
techniques developed by those analysts being embedded in everyday technology seamlessly
integrated in our daily lives.
That’ll be handy when your self-driving Uber is monitoring tree growth to predict pollen intensity and
adding that to the antihistamine global logistics chain. And reminding you that the pharmacy at the
next corner still has some…
I’m thinking of going on a theme of “GIS is everywhere.” It’s not niche at all. Much like image process-
ing technology used to be niche, now it’s on every camera, every phone, Facebook, Instagram, etc.
finding faces (to focus the camera on) and identifying people. It’s a capability that we now take for
granted. GIS is like that. Then, with companies like PH driving applications and lower cost adoption,
it’s going to get bigger. I see the idea of a dominant GIS player giving way to smaller actors
embedding the tech and capability into everything.
PrecisionHawk’s Lancaster
23

ARTIFICIAL
INTELLIGENCE SET TO
ACCELERATE IN 2017
“Maps have existed for thousands
of years and are still evolving to
continue meeting users’ diverse
and changing needs. Part of this
evolution is the level of details
included in the maps; geometry
and street names alone are no
longer sufficient, and in recent
years, additional attribution has
been added to maps to enhance
the user experience. To facilitate
this attribution, TomTom is
developing new, innovative tools,
such as Artificial Intelligence to
speed up the process of map
development and updates.”
PIETER GILLEGOT-
VERGAUWEN
VP Product Marketing, TomTom
Maps have existed for thousands of years and are still evolving to
continue meeting users’ diverse and changing needs. Part of this
evolution is the level of details included in the maps; geometry and
street names alone are no longer sufficient, and in recent years,
additional attribution has been added to maps to enhance the user
experience. To facilitate this attribution, TomTom is developing new,
innovative tools, such as Artificial Intelligence to speed up the process
of map development and updates.
At TomTom, we have already started this with Traffic signs. They
provide critical information to drivers and vehicles, from warning them
that they are going above the speed limit or approaching a dangerous
curve to providing an environmental context for autonomous cars to
plan their next manoeuvre. Capturing and maintaining these traffic
signs to include them in our digital map database used to be done
almost entirely manually, with operators browsing through thousands
of hours of mobile mapping imagery to find and identify relevant signs.
With the introduction of laser radars in our mobile mapping fleet a few
years ago, TomTom took the first step towards automating the
detection of traffic signs. Indeed, sign reflectivity now allowed us to
easily filter out images containing relevant sign content. Once the
relevant sign content was singled out, sign classification, the complex
process of identifying the category and type of sign, would occur. The
human brain in naturally attuned for this complex visual process – but
machines had to be taught.
Over time, our operators have classified almost 100 million signs
across more than 100 traffic sign categories, creating a huge traffic
sign evidence database. Taking it all a step further and through the
supervised learning of deep neural networks on this traffic sign
evidence database, TomTom developed its own Traffic Sign
Classifier Artificial Intelligence. This AI tool allows TomTom to classify
detected signs in an automated way with very high accuracy levels.
Where needed, unclassified signs are revised by human operators,
further improving the learning and competence of the Traffic Sign
Classifier AI.
Once traffic signs are classified by the AI, TomTom’s map fusion
processes kick in, adding the correct signage data to the appropriate
TomTom map layers, including our navigation and HD maps.
With the explosion of sensor equipped vehicles, traffic signs will no
longer only be detected by TomTom’s mobile mapping fleet but also,
increasingly, by regular cars continuously driving the roads.
AI is set to play a crucial role in the quick and efficient processing of
data, therefore enabling TomTom to bring the most up-to-date maps
to its users for a safer and more comfortable driving experience and
also, one day, for autonomous cars to make their own decisions.
24

THE FUTURE
OF EARTH
OBSERVATION
“Earth Observation is now
heading towards a revolutionary
model where all data is
immediately available, all analysis
is performed in near real-time
as the data is acquired, and
the distribution of the imagery
analysis results are streamlined
straight into users hands through
apps and other channels, ready
to be put to work.”
DR. KEITH BECKETT
Chief Scientist, UrtheCast
To date, the model for geoanalytics has tended to be very
transactional: request imagery, analyze imagery, deliver imagery
analysis results. Earth Observation is now heading towards a
revolutionary model where all data is immediately available, all analysis
is performed in near real-time as the data is acquired, and the
distribution of the imagery analysis results are streamlined straight into
users hands through apps and other channels, ready to be put to work.
In the same way that the integration of many unrelated technologies
were integrated together into the creation of today’s smartphones, the
future of Earth Observation and geoanalytics will involve the seamless
integration of a wide range of technologies, sensing modalities and
unconventional data sources. We can already see how the Internet Of
Things (IOT) and remote sensing are converging, with each technology
combining in ways that we could only dream of a few years ago.
The explosion in the demand, largely attributable to the
compounding effects of global population growth and climate
change, to serve the rapidly expanding markets such as agriculture,
forestry, energy, water management and insurance, is forcing these
markets to look to Big Data to supply better, faster, higher-quality
and cheaper access to actionable information. Consequently, as
computing power grows according to Moore’s Law, the technological
leaps needed to operate on Big Data will, without a doubt, be pushed
far harder than Gordon ever envisioned.
25

“As artificial intelligence
becomes increasingly
humanized, humans become
increasingly digitalized, and it
will be up to us to find the right
balance between the two.”
HERE’S
Design Forward Team
6 LOCATION TRENDS
TO WATCH OUT FOR IN
2017
The Design Forward team at HERE have once again been looking into
a variety of industries and identified patterns to predict location trends
for 2017. The team focuses on cross-industry research, including mar-
kets outside of HERE’s current business areas. By attending relevant
trade shows, conferences, and events first-hand, they look at changes
affecting people’s lives and make speculative guesses about the future
as well as the role location could play in these scenarios. The goal is
to trigger innovative ideas for location technology development. This
year, six have made the list:
1. Location Intelligence (L.I.) for an autonomous
world
Thanks to highly automated and accurate analyses of large sets of
data, we are better equipped than ever to simulate and predict situ-
ations to determine a favorable outcome. In Reykjavik, for example,
traffic lights now automatically turn green for emergency and public
transportation vehicles, and Rob van der Burg is developing cybernetic
plants called “Nova Eden” that have the power to move to a sunnier
spot at will—without the help of humans. Pretty cool, but without L.I.,
most autonomous innovations wouldn’t get very far.
2. Digital and physical merge
Imagine a world in which robots and humans aren’t distinguishable by
looks, speech, or even intelligence. Cyberpunk would become reality.
We’re not quite there yet, but it’s clear that it’s the future we’re work-
ing towards. As artificial intelligence becomes increasingly humanized,
humans become increasingly digitalized, and it will be up to us to find
the right balance between the two. With location technology being
at the core of this merge, HERE will play a key role in making sure we
won’t wake up in our own Matrix one day.
26

3. The era of holistic experiences
It’s been five years since The Atlantic’s article “The Cheapest Generation: Why Millennials aren’t buy-
ing cars or houses, and what that means for the economy,” but the trend of sharing things has only
continued to grow. We no longer buy cars or stay loyal to brands, we buy and consume experiences.
More and more touchpoints emerge between sectors that have traditionally been separate, bringing
a new set of opportunities—all powered by location: autonomous cars as offices on-the-move, ma-
chines in charge of agricultural fields, and drones as mail carriers delivering to previously inaccessible
areas.
4. Hyper-mobile society
Maybe one of the reasons we no longer aim to own but to share is our everlasting thirst for adventure.
We’re never somewhere and always everywhere—we’re hyper-mobile. Digitalization has created a
world in which physical borders play less and less of a role, inspiring products, services, and institu-
tions to follow suit by offering mobile features: backpacks that power digital devices, beds that can
be built anywhere, and governments that don’t require residents to stay within physical borders.
5. (Re-)Distribution of resources
It’s no secret that the world’s need for resources will continue to grow in the years to come. A highly
flexible and autonomous society requires massive amounts of energy to function. These resources
will need to be less centralized to ensure a consistent supply everywhere and at any time. Using the
power of location, we can help build smarter cities and environments that will better (re-)distribute
resources.
6. Aspirations in algorithms
In many aspects of life, sophisticated algorithms have changed things for the better. We now have
safer roads through analyzing and rewarding good road behavior and more efficient healthcare soft-
ware that can create highly personalized diagnoses and treatments. But these advancements come
at a price: We pay them with massive amounts of data and potentially risk loss of privacy. Ethics and
social responsibility will thus play an even greater role in the future.
To get more details about the findings of HERE’s Design Forward team, check out the full disclosure
of this year’s location trends on HERE 360.
27

4 TRENDS THAT WILL
REVOLUTIONISE THE
DRONE MAPPING
“‘Machine Learning’ is one of the
buzzwords that you can hear
and read as often as ‘drone.’
So how about combining these
technologies? Recent years
showed that Machine Learning
is particularly useful for image
recognition and could be applied
to drone-powered digital
photogrammetry.”
ALEKS BUCZKOWSKI
Editor-in-chief of Geoawesomeness
Drone mapping tech is developing so fast that it’s hard to follow all the
industry news. UAVs are getting smarter, faster and overall more com-
plex but there are a couple of trends that are about to move the drone
photogrammetry revolution to the next level.
1. Miniaturization = Size vs. battery life
The launch of DJI Mavic Pro showed that hardware providers are
working on making smaller and lighter devices. Besides the portability,
the reason for that is the battery life. The more you save on size and
weight, the longer your drone can last on a single charge and today
the flight time is the biggest limitation of the technology.
There is a linear relation between the size of the area you can map
during a single flight and the battery life. Normally, fixed wing drones
can survey up to several square miles and rotary drones below 0.1 mi2
during a single flight. Extending the battery life could enable plenty
of new applications or significantly improve currently offered drone
mapping services.
2. Advanced Sensors
Most of the drone mapping use cases today are based on a regular
RGB visual sensors. The price decrease of advanced sensor technolo-
gies now allows using them with UAV platforms. Companies like Preci-
sionHawk already offers a whole range of mapping sensors including
multispectral, hyperspectral and thermal cameras as well as LiDAR.
Such sensors allow applying complex remote sensing algorithms to
drone imagery with a millimeter resolution. It brings domains like pre-
cision farming to a new level. It allows assessing the condition of crops
per plant rather than per acre. It’s a level of detail that was not avail-
able ever before, and it will require some time for the industry to learn
how to use it, but the data are there.
3. Automated drone fleets
Today, UAVs are typically controlled by human operators, that have
to plan the flight (or use software to do that), go to the field, launch a
drone, complete the survey in single or multiple rounds. The scope of
the project is limited by a range of the drone and the required
resolution.
28

So if you have a large object to survey, you need multiple drones with multiple operators or one oper-
ator that gradually collects data for the whole project area. It complicates the operations in the field,
increases the cost and compromises the available temporal resolution (refresh of a given area over
time). For some objects like long power lines or pipelines, large-scale drone inspection might not be
an option at all.
The developments in drone control technologies will soon solve the problem. Imagine that an oper-
ator controls not a single UAV but a whole fleet of dozens of autonomous flying robots. The central
system divides the survey area between them. Real-time flight path tracking and dynamic flight
recomputation allow the fleet to autonomously correct their route depending on the location of other
devices.
Such solutions are currently used by Intel in the entertainment industry but applying it to drone map-
ping will be a real disruption.
4. Machine Learning in Digital Photogrammetry
‘Machine Learning’ is one of the buzzwords that you can hear and read as often as ‘drone.’ So how
about combining these technologies? Recent years showed that Machine Learning is particularly use-
ful for image recognition and could be applied to drone-powered digital photogrammetry.
PwC is one of the pioneers in the field. The company’s drone mapping unit has trained neural
networks to recognize multiple object classes and is now applying it to construction inspections.
It allows tracking objects, applying safety measures to human behavior and automatically
monitoring progress but the possibilities of Machine Learning for drone mapping are endless.
29

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