What we do in CASA UCL

Centre for Advanced Spatial Analysis, University College LondonCentre for Advanced Spatial Analysis

What
We
Do
in
CASA

At
University
College
London

Vassilis
Zachariadis

h#p://www.casa.ucl.ac.uk/

v.zachariadis@ucl.ac.uk

Things
we
are
doing

•  The
Simula+on
Modelling
Projects:

for
the
FCC,
land
use
transport
forecas9ng
models

•  The
Mobility
Projects:
Insight
Project:
FP7

Review
of
Land
Use
Transport
Models
–
LUTI

•  The
Sensing
Projects:
Big
Data

Subway
and
Taxi
Data
Flows;
Matching
Demand
and
Supply

•  The
Science
of
Ci+es
Projects:
ERC
AdG
Mechanicity

Allometry
of
City
Sizes
–
Percola9on,
Ci9es
as
Networks

•  Other
Projects:
EPSRC
Global
Dynamics,
Urban
Flow
Engine,

ESRC
Talisman,
Several
Small
Projects
on
Visualising
3D
CiIes,

City
Engine,
VR,
Social
Media
Data
etc.

Amongst the first integrated urban models in
the UK were built for the Tyndall Centre for
Climate Change Cities program which
involved linking macro-economic and
demographic to land use, transport and
hydrological models dealing with flooding.
Here is the block diagram

The
Simula+on
Modelling
Projects:

for
the
FCC,
land
use
transport
forecas9ng
models
–
this
is
the

area
we
are
spinning
oﬀ
as
a
semi-‐commercial
opera9on
–
to

build
plaQorms
for
urban
land
use
transport
models

Demographic
Microsimulation
Model
LUTI Model

Demographic
Microsimulation
Model
LUTI Model
Leeds
Geography
Cambridge
Land
Economy
CASA -UCL
Leeds
Transport
Studies
Newcastle Civil Engineering
This Consortium was funded by NERC through RCUK
Led by Jim Hall (Oxford) who is involved in our platform

ENERGY - WATER
INTERMEDIATE INPUTS
FACTORS OF PRODUCTION
SERVICES
LAND
CAPITAL
LABOUR
generation of demand in each zone

DEMANDED
INPUT
emergence of prices and densities from constraints (mainly land and density)
PRODUCTION
LOCATION PRODUCTION
LOCATION
PRODUCTION
LOCATION
PRODUCTION
LOCATION
assignment of demand in production locations

The Structure of SIMULACRA

TesIng
the
Impact
of
Cross
Rail-‐1

SIMULACRA
A simplification and extension of one part of
SIMULACRA is being developed for the FCC
by CASA called the QUANT model that will
cover all areas of England and Wales in a
single model at the scale of middle layer
super output areas (average units of 7500
population, 7201 in total)

QUANT Outline
QUANT in one line:
Take n=7201 Census MSOA travel to work areas, compute n2=51,854,401
interactions and fit a mathematical model to the data based on distance.
Mean predicted O→D
flows

The
Mobility
Projects:
Insight
Project:
FP7

Land
Use
Transport
Models
–
LUTI
and
the
development
of
an

agent
based
model
of
London
and
the
Outer
Met
Area
–

simulates
some
400,000
households
trip
paVerns
using

acIvity
model

EvaluaIon
of
model
performance
–
focus
in

London

Transport
infrastructure
(supply)

–  Road
network

–  Public
transport
services:
tube,
bus,

–  overground,
DLR,
rail

~520k road links
https://vimeo.com/119354430

The
Sensing
Projects:
Big
Data

Subway
and
Taxi
Data
Flows;

Matching
Demand
and
Supply

Smart
Card
Data

Oyster
Card
Taps

Tap
at
start
and
end
of
train
journeys

Tap
at
start
only
on
buses

Accepted
at
695
Underground
and
rail

staIons,
and
on
thousands
of
buses

991
million
Oyster
Card
taps
over

Summer
2012
–
this
is
big
data

h?p://www.simulacra.info/

Oyster
Card
Data
–
interpreIng
urban
structure,
mulItrips,
etc.

We
can
examine
origins
volumes,
desInaIon
volumes
separately

and
we
are
doing
but
here
we
will
simply
add
these
together

as
total
volumes
–
in
this
sense
they
will
not
have
meaning

any
longer
as
trips

We
will
now
examine
the

proﬁles
of
behaviour
during

the
24
hour
day
to
provide

some
sense
of
the
problem

Entries
Leakage
Exits

ParIcular
Events:
Weekdays,
Saturdays
and
Sundays

2am 4am 6am 8am 10am 12pm 2pm 4pm 6pm 8pm 10pm 12am 2am 4am
−100
0
100
200
300
400
500
600
700
800
900
Time of Day
NumberofEvents
Entry at Arsenal (10 Mn. Intervals)
Weekday
Saturday
Sunday
−1000
−800
−600
−400
−200
0
200
400
600
800
1000
Time of Day
NumberofEvents
Entry at Bank (10 Mn. Intervals)
Weekday
Saturday
Sunday
−150
−100
−50
0
50
100
150
Time of Day
NumberofEvents
Entry at Bayswater (10 Mn. Intervals)
Weekday
Saturday
Sunday
−500
−400
−300
−200
−100
0
100
200
300
400
Time of Day
NumberofEvents
Entry at Camden Town (10 Mn. Intervals)
Weekday
Saturday
Sunday
Nightlife
Work
Tourism?
Events

Circle and District line
part closure
From Edgware Road to
Aldgate/Aldgate East
19th July 2012
07:49 to 12:04
1234022 Oyster Cards
with regular pattern
during disrupted time
period travelled

Increased Travel Time
Greater than 2SD above mean increase on usual
travel time for that Oyster Card
Size equal to proportion of users that regularly travel from station
during time period, and travelled that during disruption

Exemplar
4:
The
Public
Bike
Scheme:
Local
Rou9ng
and

Local
Models
of
Movement

Bikes Data – 4200 bikes, started Nov 2010, all the data–
everything – all trips, all times, all stations/docks

Geolocated Tweets and estimated activity patterns.
Colours reflect estimated activity (Red: Offices, Yellow: Retail, Green: Leisure, Cyan: Rail).
https://www.youtube.com/watch?v=seH0GkKb36I

New York London Paris Moscow

Modelling and Visualising Pedestrian Congestion in Neighbourhoods
and Large Building Complexes

Modelling and Visualising Pedestrian Congestion in Neighbourhoods and Large Building Complexes
https://www.youtube.com/watch?v=QWuHTXufElU

The
Science
of
Ci+es
Projects:
ERC
AdG
Mechanicity

Allometry
of
City
Sizes
–
Percola9on,
Ci9es
as
Networks

Shi`s
in
Traﬃc
Accessibility
if
all
Bridges
across
the
Thames
are
Inoperable

as
far
West
as
Hammersmith

Other
Projects:
Several
Small
Projects
on
Visualising
3D
CiIes,
City
Engine,
VR,

Social
Media
Data
etc.
EPSRC
Global
Dynamics,
Urban
Flow
Engine,
ESRC
Talisman,

SimulaIng
Crowds:
Fine
Scale
Modelling
and
Sensing

In
a
diﬀerent
tradiIon
but
one

which
is
rapidly
converging
with

our
interests
in
sensing
and

networks,
we
have
developed
a

number
of
pedestrian
models,
ﬁrst

for
the
Nofng
Hill
Carnival,
and

then
for
many
town
centres

We
are
now
working

on
ﬁne
scale
models

which
are
mirror

diﬀusion
and
spread
in

situaIons
ranging
from

epidemics
to

evacuaIon
and

shopping.

We
have
a
simple

model
of
epidemics
on

networks
in
London

and
we
are
looking
at

evacuaIons
of
major

shopping
centres
such

as
Covent
Garden

(right)

Thanks

h#p://blogs.casa.ucl.ac.uk/

h#p://www.casa.ucl.ac.uk/

Acknowledgements

Michael
Ba#y,
Andy
Hudson-‐Smith,
Richard
Milton,
Oliver
O’Brien,
Stephen
Gray,

Fabian
Neuhaus,
Pete
Ferguson,
Mar9n
Austwick,
Joan
Serras,
Camilo-‐Vargas-‐Ruiz,

Paul
Longley,
Jon
Reades,
Ed
Manley,
Anders
Johansson,
Elsa
Arcaute

What we do in CASA UCL

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