The document summarizes the role of geospatial information in a hyper-connected society. It discusses how the digital earth and geo big data/internet of things are generating massive amounts of geospatial data. It also describes how web geo services, participatory mapping, and geo crowdsourcing are making this data accessible and enabling new forms of interaction between people, places, and things on the internet.

1. The role of geospatial information
in a hyper-connected society
Maria Antonia Brovelli
Politecnico di Milano – Como Campus
Dept. of Civil and Environmental Engineering (DICA) - Italy
International Conference On
Geospatial Information Science
Seoul – September, 16th 2015
POLITECNICO DI MILANO
GEOlab - COMO Campus

2. 2Overview
●Modelling the Earth
●The Digital Earth
●The Geospatial Web
●Geo Big Data/ Internet of Things
●Web Geo Services/Viewers
●The Participatory Earth
●The Internet of Places and of Everything
●GeoForAll GeoCrowd

3. 3Modeling the Earth (1)
“ ... In that Empire, the Art
of Cartography attained
such Perfection that the
map of a single Province
occupied the entirety of a
City, and the map of the
Empire, the entirety of a
Province. In time, those
Unconscionable Maps no
longer satisfied, and the
Cartographers Guilds
struck a Map of the
Empire whose size was
that of the Empire, and
which coincided point for
point with it.
The following Generations, who
were not so fond of the Study of
Cartography as their Forebears
had been, saw that that vast
map was Useless, and not
without some Pitilessness was
it, that they delivered it up to the
Inclemencies of Sun and
Winters.“
Jorge Luis Borges, On Exactitude in Science from
A Universal History of Infamy (1960)

4. 4
●
Clearly, the map is not a
miniaturised reproduction of a
portion or of the entire Earth's
surface, but rather an abstraction,
a MODEL. What we see is
strongly influenced by the choices
made by the map author.
● Some of the limitations were
surpassed by the new technology
and by the transition from paper to
digital maps. Some of them linger
on and/or cannot be eliminated so
they pose new challenges.
Modeling the Earth (2)

5. 5
The Digital Earth (DE) was introduced in 1998
by Al Gore, as a tri-dimensional and multi-
resolution model of the planet which make it
possible to visually put in place the huge
amount of geo-referenced information about the
physical and social environment.
This system allows the user to navigate not only
in space but also in time, by having access to
historical data sets and to future prevision based
on social and environmental models.
Gore, A., 1998 The Digital Earth: underdstanding our planet in
the 21st
century,
http://portal.opengeospatial.org/files/?artifact_id=6210.
The Digital Earth (1)

6. 6
There isn't a single Digital Earth.
The Digital Earth is a mix of shared, multi-
thematic, multi-resolution and multi-
perspective archives of geo-referenced
knowledge, which meet the requirements of
different parties, like scientist, decision
makers, cummunity and citizens.
All these archives, which are updated in real-
time thanks to sensor observations and
information, are interconnected.
The Digital Earth (2)

7. 7
The Digital Earth is based on open access and
on the users participation through multiple
technological platforms.
According to this paradigm it's possible to
access data, information, services, models,
scenarios and predictions, ranging from simple
inquiries to complex analyses that refer to
environmental and social fields.
The Digital Earth (3)

8. 8
Users
Catalogues
Data/Objects
Processing
Internet
Geospatial Web

9. 9Geo Big Data
●
Every day we create 2.5 trillion (1018
) bytes of
data. 80 % of these are already georeferenced
or can be.
●
It's a huge dataset, equal to a DVD tower that
goes from the Earth to the Moon every day.
384.400 km

10. 10Geo Big Data: Satellites
Active satellites Inactive satellites Space debris Rocket parts
●Since 1957 there have been at least 26,000 space
objects orbiting Earth.
●There are currently more than 12,000 man-made
orbiting objects, the rest have re-entered Earth's
atmosphere and disintegrated, or survived re-
entry and impacted the Earth.
●These orbiting space objects range from satellites
weighing several tons to pieces of spent rocket
bodies weighing under 10 pounds.
●About 3,000 space objects are operational
satellites, the rest are space debris, retired
satellites and rocket bodies left over from
launches.

11. 11Geo Big Data: Satellites

12. 12
Sensors are everywhere and they are the
electronic skin of the Earth
Geo Big Data: Sensors
Citizens as
sensors

13. 13Example 1: EarthServer
 Agile Analytics on 1+ Petabyte space/time
datacubes
• Earth Science (3D sat image timeseries, 4D weather);
Planetary Science
 Open standards, open source
• OGC WCS + WCPS, integrated data/
metadata search
• rasdaman + NASA WorldWind
+ more
 Intercontinental initiative:
EU+US+AUS
 www.earthserver.eu
EarthServer: Datacubes at Your Fingertips
Peter Baumann & al, Jacobs Univ. Bremen -Germany

14. 14Example 2: support for massive datasets in GRASS
Moderate-resolution Imaging
Spectroradiometer (MODIS)
Land Surface Temperature:
Data from 2000-today
4 Earth coverages per day
Processing of 17,000 maps of 415
million pixels each (250 m size)
●
In total 300 nodes with 600 Gb RAM
●
132 TB of raw disk space, XFS,
GlusterFS
●
Scientific Linux operating system,
blades headless
●
Queue system for job management
(Grid Engine), used for GRASS jobs
●
Computational time for all data:
1 month with LST-algorithm V2.0
●
Computational time for one LST day:
3 hours on 2 nodes
Markus Neteler & al,
FEM-Italy
http://gis.cri.fmach.it/eurolst/

15. 15Internet of Things (IoT)
By 2020 there will be 26
billions of connected
devices.
The Internet of things is a
possible evolution of the
use of the Internet.
The objects become
recognisable thanks to the
ability to communicate data
about themselves and to
access information
provided by others.

16. 16Geo Big Data: social media
http://www.internetlivestats.com/
9,890 Tweets sent in 1 second
2,528 Instagram photos uploaded in 1 second
2,153 Tumblr posts in 1 second
1,843 Skype calls in 1 second
29,290 GB of Internet traffic in 1 second
50,232 Google searches in 1 second
106,299 YouTube videos viewed in 1 second
2,420,172 Emails sent in 1 second

17. 17
Geo Big Data:
location-based social network
http://onemilliontweetmap.com/
http://www.flickr.com/map

18. 18Geo Big Data: Milano GRID
●
Two months of data, with a temporal step of 10
minutes
●
Grid of 100 x 100 cells with size = 235 m
https://dandelion.eu/datamine/open-big-data/

19. 19
●
Received SMS: a Call Detail Record (CDR) is generated each
time a user receives an SMS
●
Sent SMS: a CDR is generated each time a user sends an SMS
●
Incoming Calls: a CDR is generated each time a user receives a
call
●
Outgoing Calls: CDR is generated each time a user issues a call
●
Internet: a CDR is generate each time
– a user starts an internet connection
– a user ends an internet connection
– during the same connection one of the following limits
is reached:​
• 15 minutes from the last generated CDR
• 5 MB from the last generated CDR
●
Geolocalized Twetts (Anonymized twitter users)
Geo Big Data: Milano GRID

20. 20Sensing the City - 1

21. 21Sensing the City - 1
Students: Emanuele Mariani, Jacopo Mossina;
Supervisors: Giorgio Zamboni, Maria A Brovelli
http://landcover.como.polimi.it/BGDV/

22. 22Sensing the City - 2
Student: Anna Trofimova
Supervisors: Carolina Arias, Maria A Brovelli

23. 23Sensing the City - 2
Filtering with date and land coverage classes

24. 24Sensing the City - 2
Student: Anna Trofimova
Supervisors: Carolina Arias, Maria A Brovelli
http://landcover.como.polimi.it/socialmedia_rasdaman/

25. 25Sensing the City - 3
Carolina Arias, Maria A Brovelli,
Simone Corti
http://landcover.como.polimi.it/BigNetCDF/

26. 26Sensing the City - 3
Filtering
Interactive
multidimensional
web visualisation -
ESTWA
Maria A Brovelli, Giorgio Zamboni

27. 27
Web Service
“... a software system designed to support the
interoperability between network machines ”
NETWORK
NETWORK
Web Geospatial Service
“...specific web services for geospatial data and information”
Web Geospatial Services

28. 28
CataloguesData
RASTER DATA
GRID DATA
VECTOR DATA
Other geospatial data
(e.g. sensors)
Processing
INPUT data
PROCESSED
DATA
Geo Services Types

29. 29
Data
INTERNET
COVERAGE
DATA
VECTOR DATA
RASTER
DATA
Geodata Services

30. 30
Server Client
INTERNET
DIGITAL TERRAIN MODEL
BASIC MAP
THEMATIC MAP
Cartographic Mashup

31. 31
INTERNET
CATALOGUE A
CATALOGUE B
CATALOGUE C (Metadata)
CATALOGUE
A
CATALOGUE
B
CATALOGUE
C
Geo-Catalogue Service

32. 32
INTERNET
TIN
Triangulated
Irregular Network
Scattered points
height measures
Scattered
points
height
measures
TIN
Processing:
Delaunay Triangulation
Processing Service

33. 33Multiframe and multidimensional viewers

34. 34
Images, Videos,
Positions, Sounds, …
images, videos,
sounds, positions
INTERNET
The Participatory Earth

35. 35Apps for collecting data
Architectural barriersArchitectural barriers
Cultural elementsCultural elements
Street furnitureStreet furniture BiodiversityBiodiversity

36. 362D Viewer architecture
SERVER CLIENT
template form
GeoJSON
AGGREGATE COLLECT
compiled form
DATA
STORAGE
DATA ACQUISITION
DATA WEB PUBLICATION
DATA WEB
VISUALIZATION

37. 37Policrowd2.0 (virtual globe) architecture

38. 38Collaborative Platform

39. 39The Internet of Places and of Everything
Although much of the hype has been around things
becoming part of the Internet, the additive power of the
Internet comes into play when things, people, places and
systems work together. This describes a concept Gartner
calls the "Internet of Everything”.
The Internet of Things is just one piece of this concept
alongside
● the Internet of People (such as social networks or IM
presence),
● the Internet of Places (such as Foursquare or any location
that can broadcast information about itself),
● the Internet of Information (for example, the World Wide
Web, or systems that can share information through APIs
or Web services).
Kristian Steenstrup (Vice President and Gartner Fellow in Gartner's Office of the CIO Research team)

40. 40GeoForAll Geocrowd
Geocrowdsourcing CitizenScience FOSS4G
Peter Mooney & Maria A Brovelli

41. 41
Thanks for your attention!
Thanks to all people of my team contributing on these
topics: Carolina Arias, Simone Corti, Eylul Candan
Kilsedar, Marco Minghini, Monia Molinari, Giorgio
Zamboni
Thanks to Peter Baumann, Peter Mooney and Markus
Neteler
Politecnico di Milano
GEOlab Como Campus
Via Valleggio 11, 22100 Como (Italy)
maria.brovelli@polimi.it