Cartographic visualisation of Time
prof Menno-Jan Kraak
<[email protected]>
Barend Köbben
<[email protected]>
INTERNATIONAL INSTITUTE FOR GEO-INFORMATION SCIENCE AND EARTH OBSERVATION
Contents
ƒChanging Cartography
ƒ from making maps to Spatial data dissemination
ƒTime in Cartography
ƒ Dynamic Visualization Variables
ƒ Case: Overijssel Municipal changes
ƒAdapting to Time & Place
ƒ Location Based Services
ƒPractical application
ƒ Using MapViewSVG to put Place & Time on the Web
© ITC Department of GeoInformation Processing – Barend Köbben
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Changing Cartography:
From making maps
to
Spatial data dissemination
Barend Köbben
<[email protected]>
INTERNATIONAL INSTITUTE FOR GEO-INFORMATION SCIENCE AND EARTH OBSERVATION
Overview
ƒWhy use maps?
ƒChanging Cartography
ƒWhy use the Web?
ƒWebCartography
© ITC Department of GeoInformation Processing – Barend Köbben
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Why use graphics?
Graphics are international:
uitgang, exit, Ausgang, sortie, uscita,
salida, etc...
=
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Why use graphics?
Graphics are holistic:
“a picture says more than a thousand words...”
“First road left, then
cross the railroad and
continue until you
cross the river, then
the first right and right
again on the
crossroads...”
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Why use maps?
rainfall
12, 13, 14 september
dirksland
de bilt
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apeldoorn
7
Why use maps?
apeldoorn
de bilt
dirksland
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Maps depict spatial data:
When? = time
Where?
= location
What? = attribute
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The Cartographic Communication
Process
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Changing cartography
conventio
nal
digital
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CHANGING CARTOGRAPHY
Î new kinds of maps
ƒInteractive maps
ƒRealism & false realism: Virtual worlds
ƒDepiction of movement & change:
Animated maps
ƒCombining maps with other graphics,
sound and moving images: Multimedia
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The Cartographic
Communication Process
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DLM - DCM model
from reality to maps
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DLM - DCM model
from reality to maps
Digital Landscape Model (DLM):
ƒ selection from real world
ƒ stores geometry (points, lines, areas, raster)
ƒ stores attributes (linked to geometry)
Digital Cartographic Model (DCM)
ƒ visualisation of DLM
ƒ dependent on scale, purpose, output medium,
reader skill, etc..
ƒ stores graphic attributes (linetype, colour, etc)
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DLM - DCM model:
example of road network
Reality: various roads with different widths, surface, status, etc.
geographic modelling
DLM: centre lines of roads stored as vectors with attributes such as road class, surface, amount
of traffic, etc.
visualisation
DCM: traffic loads (for WWW)
Map: lines with widths
proportional to amount of traffic
(at 72 dpi, WWW colours)
visualisation
DCM: topographic map (offset printed)
Map: lines with linetypes &
colours according to road class
(at 1240 dpi, printing colours)
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CHANGING CARTOGRAPHY
Î new (digital) data dissemination
ƒOn CD–ROM
ƒOn the World Wide Web
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Why use the Web?
ƒ WWW information is virtually platformindependent
ƒ unrivalled in its capacity to reach many
users at minimal costs
ƒ easy to update frequently
ƒ the WWW allows for a dynamic and
interactive dissemination of spatial
data:
Î New map types
© ITC Department of GeoInformation Processing – Barend Köbben
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Disadvantages
ƒPotential user group is limited (though
growing fast) and skewed (computerliterate and connected people)
ƒDifficult to charge for use
ƒFast-moving:
ƒInformation is time-sensitive
ƒInteractivity is a must
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WebCartography
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Static maps – view only
Existing maps
(scanned)
ƒ
mainly interesting for
Historical maps
Specially designed
web-maps
ƒ
eg. cartography
students at ITC
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Traditional vs. interactive maps
traditional map = view only map
ƒbitmaps (scanned images)
interactive map (map as interface)
ƒclickable map: leads to other (web)
information; map as menu;
interactive map (user–defined contents)
ƒmaps on demand; user defines contents
and/or symbolisation
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Interactive maps
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Static maps – interactive interface
Map is entrance to other (map)
information: ‘clickable maps’
ƒHTML clickable maps (Netherlands in provinces)
ƒFlash maps of Overijssel (data, magnify)
User can change map content &
visualisation:
ƒfrom simple layers on/off… map of Overijssel
(Flash)
ƒ…to fully interactive Tuerlersee topographic map
(SVG)
© ITC Department of GeoInformation Processing – Barend Köbben
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Virtual worlds
The world mapped “as it is”
ƒPerspective view (instead of orthogonal)
ƒComplete (not generalised)
ƒRealistic (not symbolised)
Photo–realism (or pseudo–
realism)
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Virtual Worlds
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Multimedia definition
“The combination of various media
parts into a coherent whole”
Media parts:
ƒmaps, graphics, text, moving images, sound,
text, etc...
Coherent whole:
ƒThe whole is more than the sum of the parts
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WebCartography
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Animated maps
For showing dynamic phenomena
ƒ
ƒ
As animated maps (“movies”)
As dynamic real-time images
(dynamic webpages)
For moving through Virtual Worlds
ƒ
ƒ
As animations (eg. animatedGIF, Quicktime movies)
With interactive contents (modelled worlds, eg. games, VRML)
© ITC Department of GeoInformation Processing – Barend Köbben
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Dynamic web maps
For showing dynamic phenomena
ƒ
ƒ
As animated maps (‘movies’) (eg. gondwana)
As dynamic real-time images (ANWB)
© ITC Department of GeoInformation Processing – Barend Köbben
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Dynamic web maps
For moving through Virtual Worlds
ƒAs a view-only animation
(eg. animated GIF)
ƒWith an interactive interface (“movie”)
(eg. quicktime)
ƒWith interactive contents (modelled)
(eg. games, VRML)
© ITC Department of GeoInformation Processing – Barend Köbben
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http://kartoweb.itc.nl/public_examples
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Dynamic visualization
variables
Connie Blok, Barend Köbben
{blok;kobben}@itc.nl
INTERNATIONAL INSTITUTE FOR GEO-INFORMATION SCIENCE AND EARTH OBSERVATION
Graphic variables
Known already: Bertin’s 7 graphic (visual)
variables
ƒ position
for locational aspects of geospatial data
ƒ form, orientation, colour, texture, value and size:
for the thematic attributes
Others have distinguished additional graphic
variables for thematic attributes, e.g.:
ƒ
ƒ
ƒ
ƒ
saturation (in addition to hue & value)
crispness / resolution
transparency
…
© ITC Department of GeoInformation Processing – Barend Köbben
More variables
to represent geospatial data
Visual variables (can be perceived visually):
ƒ Graphic variables
used in the spatial dimensions of static and dynamic
(animated maps)
ƒ Dynamic visualization variables
used in the temporal dimension of dynamic maps:
display time
Other variables
(need other modes of perception)
eg. sound, smell, touch…?
© ITC Department of GeoInformation Processing – Barend Köbben
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Representation of change
Based on graphic variables only:
ƒ Single static map
ƒ Multiple static
maps (snap shots
in time)
Based on graphic + dynamic
visualization variables:
ƒ Animated
(dynamic) map
© ITC Department of GeoInformation Processing – Barend Köbben
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Single static maps
Dynamics can suggested by symbols that give
an impression of movement or order,
order like:
ƒ value,
value e.g. to show the successive stages of
urban growth
ƒ arrows,
arrows e.g. for the paths of wildfires, hurricanes…
ƒ flow lines,
lines e.g. to show troop movements
ƒ etc…
Dynamics can also be shown by change /
temporal difference maps, e.g.:
ƒ change in land use between 2 moments in time
ƒ population growth in a given time period
© ITC Department of GeoInformation Processing – Barend Köbben
Single static maps
value
arrows
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Single static map:flowlines
Napoleon’s 1812 Russian campaign
Minard’s map,
1869
Kraak’s space-time cube, 2003
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Single static map
change map: deforested area in ‘95
forest in ’92,
deforested in ‘95
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Multiple static maps
Spatial dynamics have to be mentally
extracted by the user through map
comparison,
comparison e.g.:
ƒ land cover / use 1992
ƒ land cover / use 1995
Difficult if:
ƒ information is complex
ƒ more than a few maps have to be compared
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Multiple static maps:
1992 and 1995 land cover/use maps
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Multiple static maps:
growth of Enschede
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Animated (dynamic) map
Quick succession of slightly different images
-usually frames – showing change in display time
the temporal dimension: the time a viewer sees an animation
frames
interaction
controls
© ITC Department of GeoInformation Processing – Barend Köbben
Again… representation variables
in an animation
Graphic variables
ƒ represent characteristics of geodata in the
spatial dimensions of the images
ƒ their appearance may change in successive stages,
but the temporal characteristics of the changes
can only be viewed in display time
Dynamic visualization variables
ƒ can only be viewed in display time
ƒ at least one graphic variable (position) is required
to be able to see a dynamic variable, e.g.
ƒ the frequency of a blinking point symbol;
ƒ the order of locations hit by a hurricane …
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Questions that can be asked
to an animation of geodata
when?
in what order?
how long?
how fast?
how often?
states (periods not affected by change)
Those questions are difficult to answer with static maps !
© ITC Department of GeoInformation Processing – Barend Köbben
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Dynamic visualization variables
DiBiase et al. (1992)& MacEachren (1995): 6 variables
Blok (2005): 4 variables, the other 2 are effects
ƒ
ƒ
ƒ
ƒ
ƒ
ƒ
Moment of display (display date)
Order
Duration
Frequency
Rate of change
Synchronization
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Relationships between the
dynamic visualization variables
(Blok, 2005)
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Moment of display (or display date)
Position of a change / state in the representation in
display time
Moments of display that are ‘marked’ by a change enable
the perception of other dynamic visualization variables
T1
Tn
T=1837
I
T=1838
II
T=1839
III
T=1840
IV
T=1841
V
display date
‘marked’ moment of
display
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Moment of display
ITC building : in every frame there are changes; these are
‘marked’ moments of display
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Order
Structured sequence of states / changes in
the representation in display time
T1=1600
T2=1700
T3=1800
T4=1900
order
here,
chronological order is applied,
e.g.: 1600, 1700, 1800, 1900, 2000
… February, March, April, …
© ITC Department of GeoInformation Processing – Barend Köbben
T5=2000
Duration
Length in display time of a change/state in the
representation
1 unit of time
T=76-80
T=80-84
T=84-88
T=88-92
duration
3 units of time
© ITC Department of GeoInformation Processing – Barend Köbben
T=92-96
Frequency
Repetition or the number of identical states /changes
in the representation per unit of display time
every 10 minutes
T=
10.05
T=
10.15
T=
10.25
T=
10.35
high
low
frequency
every 30 minutes
© ITC Department of GeoInformation Processing – Barend Köbben
T=
10.45
Rate of change
variable … or effect?
The magnitude of change per unit of display time
Effect, influenced:
not only of animation design decisions, underlying data
also of any interaction with (the dyn. vis. variables in) the
animation
T1=12.00
T1=15.00
slow
T1=12.00
T1=15.00
quick
rate of change
© ITC Department of GeoInformation Processing – Barend Köbben
Rate of change
Population growth
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Synchronisation
(phase correspondence)
Refers to the possibility to run several temporal
animations simultaneously and manipulate (‘tune’)
their starting points in display time to discover
similarities in patterns
T = 3 months
T1
T2
T3
rain
vegetation
(f) synchronization
© ITC Department of GeoInformation Processing – Barend Köbben
T4
Synchronization (effect of tuning)
Tuning is
interacting with
moment of
display in two
animations to
synchronize
the animations
The ‘tuning
mode’ in
aNimVis
enables
synchronization
© ITC Department of GeoInformation Processing – Barend Köbben
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Application of the variables
The dynamic vis. variables can be used to represent:
ƒ the temporal component of geodata:
this results in temporal animations,
animations
in which e.g. moment, order, duration
and frequency of changes /states in reality are
mimicked.
mimicked
ƒ non-temporal aspects of geodata:
this results in non-temporal animations,
animations
in which the dynamic variables are used for the
sequential representation of:
ƒ other data components (location/them. attributes)
ƒ different graphic representations/views of the data
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Example: temporal animation
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Examples of non-temporal animation:
fly-by
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Examples of use of dyn. variables
in non-temporal animations
Suppose: variables are linked to attributes:
attributes
ƒ Moment of display:
a complex map builds-up gradually
(thematic objects are gradually added)
ƒ Order:
Order
data are represented in class order, e.g. from the
lowest to the highest class
ƒ Duration:
Duration
extreme attributes values are displayed longer
than normal values
ƒ Frequency:
Frequency
can be used to let a symbol blink (e.g. to attract
attention)
© ITC Department of GeoInformation Processing – Barend Köbben
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CASE:
Overijssel population
through time
http://www.itc.nl/personal/kraak/overijssel/index.htm
Menno-Jan Kraak
[email protected]
INTERNATIONAL INSTITUTE FOR GEO-INFORMATION SCIENCE AND EARTH OBSERVATION
visualize overijssel's past
interactive animation's on the www
the problem
the data
options
solutions
conclusion
© ITC Department of GeoInformation Processing – Barend Köbben
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the problem
to visualize the changes in municipal
population in the province of overijssel
during the last 200 years
conditions
ƒidentify municipality and number of
inhabitants at any time
(interactive and dynamic display)
ƒmedium: the www
© ITC Department of GeoInformation Processing – Barend Köbben
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what is changing?
municipal boundaries
population numbers
municipal boundaries:
time
now and then
time
population numbers:
© ITC Department of GeoInformation Processing – Barend Köbben
every year
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data sources
boundaries
ƒ(old) maps
ƒpublications
population
ƒcensus
ƒpublications
ƒgeographic dictionaries
archives - libraries – www
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from relevant publications
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non-map publications
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census
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nature of the changes
merge
split
annex
changes are registered when:
yarea involved is larger then 5km2 ,
yarea involved is smaller then 5km2, but more
than 500 inhabitants are involved
ycumulative effects
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what has been collected?
1818
1914
1955
1996
sample years
with changes
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what has been collected?
© ITC Department of GeoInformation Processing – Barend Köbben
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enschede
160000
140000
120000
annexactie
1935
full
annexation
Lonnerker
lonneker
1935
100000
80000
60000
uitbreiding
tkv
small
annexation
Lonneker
1885
from
lonneker
40000
error 1978
1978
error
20000
© ITC Department of GeoInformation Processing – Barend Köbben
1979
1965
1954
1943
1932
1921
1910
1899
1888
1877
1866
1855
1844
1833
1822
1811
0
73
blokzijl
2000
1800
1600
1400
1200
1000
departure of
fishermen
population due
to new polder
800
600
400
annexation
200
© ITC Department of GeoInformation Processing – Barend Köbben
1963
1955
1947
1939
1931
1923
1915
1907
1899
1891
1883
1875
1867
1859
1851
1843
1835
1827
1819
1811
0
74
mapping options
(single moment in time)
proportional point symbol
cartogram
prism
…
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mapping options
(multiple moments in time)
small multiples
animation
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smallest units
a
h
d b
i
2.
c
f
g
z
e
1972
1.
c
x
create lookup table
which holds for each
unit, per year, the
municipality it
belonged to
1971
1973
1
overlay of all
municipal divisions
between 1811 and
2001 resulting in
set of smallest units
5
2
4
3
6
7
8 11
12
10
9
13
1972
1973
1974
1
a
a
x
x
2
b
b
x
x
3
c
c
c
c
4
d
d
x
x
5
h
h
c
c
6
h
h
x
x
7
g
g
x
x
88
i
i
ii
xx
xx
9
f
f
z
z
10
g
g
z
z
11
g
g
z
z
12
g
g
z
z
13
e
e
z
z
© ITC Department of GeoInformation Processing – Barend Köbben
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resulting geographic units
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preparing the data
1971
1972
1973
create final
table population
per year per
smallest unit
1974
1971
1972
1973
1974
1
a
a
x
x
a
934
920
-
-
b
2750
2713
-
-
2
b
b
x
x
c
12600
12738
20499
20799
3
c
c
c
c
d
398
401
-
-
4
d
d
x
x
e
1788
1811
-
-
5
h
h
c
c
f
2722
1227
-
-
6
h
h
x
x
g
5504
5459
-
-
7
g
g
x
x
h
8096
8158
-
-
8
i
i
x
x
i
1344
1334
-
-
9
f
f
z
z
x
-
-
4874
4828
g
g
z
z
z
-
-
11102
11147
1
0
1
1
g
g
z
z
1
2
g
g
z
z
1
3
e
attributes
population data
1971
1972
1973
1974
1
934
920
4874
4828
2
2750
2713
4874
4828
3
12600
12738
20499
20799
4
398
401
4874
4828
5
8096
8158
20499
20799
6
8096
8158
4874
4828
7
5504
5459
4874
4828
8
1344
1334
4874
4828
9
2722
1227
11102
11147
10
5504
5459
11102
11147
11
5504
5459
11102
11147
12
5504
5459
11102
11147
13
1788
1811
11102
11147
© ITC Department of GeoInformation Processing – Barend Köbben
geometry
e
z
smallest
units
z
79
resulting user interfaces
prism map in 3d web
environment - VRML
Animation
© ITC Department of GeoInformation Processing – Barend Köbben
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considerations
depending on nature of
data sets the view can be
chaotic
need for options to
emphasize changes in
geo-units, attributes or
time only or a selection of
one of those
© ITC Department of GeoInformation Processing – Barend Köbben
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