United Maps

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United Maps
United Maps
United Maps:
Maps on a human scale.
• Professional Maps for the Geoweb.
• United Maps GmbH  2009
1
Maps leave the car.
in-dash OEM
in-car AM
PDA
PND
United Maps
smartphones
mobile phones
• Cell phones know where we are.
Maps become personal.
Maps made for cars
don‘t make too much sense
for mobile humans.
original picture: http://flickr.com/photos/greenspartan/2548517094/ - by greenspartan
Vehicle Maps don‘t make too much
sense on personal mobile devices
United Maps
Conventional maps focus on
vehicle traffic and streets:
» no detail on pedestrian level
» no multimodal navigation
» random house footprints
» few relevant POIs
Mobile devices have different
usecases.
Users expect better maps.
United Maps fills gaps in maps.
United Maps
» large scale = deep zoom
» public transport
» seamless multimodal
navigation
» pathes, walkways and trails
» precise house footprints
» exact addresses
» comprehensive content
Better maps = better apps.
Better Maps = Better Apps
Yahoo! Maps
Maps make the difference.
United Maps
UM-DE (pre-release 04.09)
United Maps
Better Maps.
» cities: up to 50% density
» rural: up to 300% more
streets, pathways and trails
» attributes conserved
» fully navigable
» professional topology
• White lines are basedata sets - red lines is United Maps better
maps with dramatically enhanced streets and pedestrian features.
Mobile multimodal navigation
on a human scale
indoor
hyperlocal
local
streets
municipial
regional
national
continental
United Maps
» algorithmic merging and
matching of vector data sets
» licenced data from Navteq
or Tele Atlas (no mashup)
» addition and completion of
missing features and layers
» perpetual, dynamic updates
» unique content
Conventional field research and
processing is expensive
Conventional field research
requires reasonable perpetual
effort and resources.
In 2007, Navteq alone spent
$336m for map updates.
2006: 275$m
2005: 236$m
2004: 197$m
Turner, A. and Forrest, B., (2008) Where 2.0 - The state of the Geospatial
Web. page 6. http://cachefly.oreilly.com/radar/research/
Where2.0_excerpt.pdf
United Maps
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We use smart software instead of
driving roads.
United Maps
Primary maps from Navteq or
Tele Atlas are matched,
merged and extended with
supplemental data.
The result are truely pedestrian
maps for mobile usecases in an
unseen map quality.
Highly detailed, hyperlocal maps.
Crowd Mapping produces results
United Maps
OpenStreetMap quickly generates
maps for populated areas.
Great Idea!
» professional quality?
» routable?
» comprehensive feature sets?
» commercial products?
» coverage?
» precision?
» reliability?
» Hype?
How we do it:
Algorithmic Conflation
UM licences vector data from market
leaders and deploys a proprietary
algorithm ...
» to automatically match vector data
sets, geometries and attributes
» with a precision of 95% correct
positive matches resulting in ...
» a fully navigable topological
network based on primary data
Original primary data is left
untouched. Nodes are expanded to
attach new, previously missing
pathways, conserving all attributes.
United Maps
What UM doesn‘t do:
» layering > original topology is
expanded, nodes and vertices are
added
» photogrammetry > pixel images
aren‘t vectorized: we licence original
and secondary vector data
» field research > we don‘t do field
checks
primary data + cadastral data
• United Maps
ATKIS is a set of official german cadastre data that is conflated with the street network data from
Navteq or Tele Atlas. Every country has cadastre data. Quality and/or availability varies.
primary + cadastre = United Maps United Maps
• Two vector data sets are conflated into a single, more precise and comprehensive dataset. All attributes are conserved,
the street networks becomes denser and remains fully navigable. A wealth of additional metadata is added.
Anyone can do that?
United Maps
The U.S. has a centralized, public
domain dataset maintained by the
US Census Bureau.
TIGER (Topologically
Integrated Geographic Encoding and
Referencing), the equivalent of
57.000 topographical maps is “out
of date, idiosyncratic and mostly
incompatible“*.
But at least there is something.
*) „Getting there“. The science of driving directions. Nick Paumgarten.
April 24, 2006; The New Yorker - http://tinyurl.com/czw3e9
Technology + Workflow
United Maps
The EU has neither
centralized nor free
data but thousands of
authorities and agencies.
European federalism, cultural
and language barriers and
completely heterogenous data
makes mapping a bit trickier.
We do maps since 30 years.
Rollout
United Maps
» DE ready in 2Q09
» 200 major European cities
» Trials for U.S. and Asia running
Where United Maps comes from
United Maps‘ staff produced european
and worldwide maps for more than 30
years.
Some of us made Carto Travel,
formerly Germany‘s mapping market
leader: cartography, GIS, editorial
processing and licencing is our
profession.
» Feb 2008: founded
» Sep 2008: (seed-)funded
» Nov 2008: started operations
United Maps
• We closely work with a german
university on academic projects and
currently employ 15 experts at 2
locations in Munich and Eisenach,
Germany.
• The first product, a hyperlocal and
fully navigable vector map of
Germany will be released as
UM-DE in April 2009.
much more
United Maps
United Maps
Contact
United Maps GmbH
Stefan Knecht – CIO
Agnes-Pockels-Bogen 1
80992 München
+49 89 4521 393 0
[email protected]
http://blog.unitedmaps.net
See Slideshare for more!
Automatic Conflation Results
Rural
United Maps
• A primary dataset is algorithmically
conflated and hence merged with a
secondary dataset.
• For practical reasons and sequential
processing, this is done by tiling an
area into 5x5 km segments.
• UM-DE consists of 15k technical
tiles.
primary dataset | secondary dataset | UM automated match
Automatic Conflation Results
Rural
• primary dataset | secondary dataset | UM automated match
United Maps
Automatic Conflation Results
Suburban
United Maps
• In rural areas, an up to 300% gain
in additional roads and pedestrian
pathes is achieved.
• In sub-/urban areas, the
enhancement varies up to 50%
depending on the timeliness of
primary and secondary data.
• Red is the fully automatically
matched vectors.
• Blue is defined as the primary base
vector set
primary dataset | secondary dataset | UM automated match
Automatic Conflation Results
Suburban
United Maps
• After a completely automated
first run, the majority of points and
lines are positively matched:
corresponding geometry is met.
• Despite its 95% precision, the
current release of the algorithm still
produces artefacts that
need to be
processed in a
second run.
primary dataset | secondary dataset | UM automated match | positive 1st run | QA 2nd run
Automatic Conflation Results
Urban
primary dataset | secondary dataset | UM automated match
United Maps
Automatic Conflation Results
Urban
United Maps
primary dataset | secondary dataset | UM automated match | positive 1st run | QA 2nd run

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