MOSES: A Synthetic Spatial Model of UK Cities and Regions - PowerPoint PPT Presentation

Loading...

PPT – MOSES: A Synthetic Spatial Model of UK Cities and Regions PowerPoint presentation | free to view - id: c3881-YmE4Y



Loading


The Adobe Flash plugin is needed to view this content

Get the plugin now

View by Category
About This Presentation
Title:

MOSES: A Synthetic Spatial Model of UK Cities and Regions

Description:

... M87: from top to bottom Chandra X-ray, HST optical, Gemini mid-IR, VLA radio. ... Picture credits: 'NASA / Chandra X-ray Observatory / Herman Marshall (MIT) ... – PowerPoint PPT presentation

Number of Views:55
Avg rating:3.0/5.0
Slides: 53
Provided by: johncl2
Category:

less

Write a Comment
User Comments (0)
Transcript and Presenter's Notes

Title: MOSES: A Synthetic Spatial Model of UK Cities and Regions


1
MOSES A Synthetic Spatial Model of UK Cities and
Regions
School of Geography FACULTY OF EARTH AND
ENVIRONMENT
  • Mark BirkinUniversity of Leeds

2
  • OVERVIEW
  • MoSeS
  • Modelling and Simulation for e-Social Science
  • Project funded under the ESRCs e-Social Science
    initiative
  • One of eight major projects in the National
    Centre for e-Social Science (NCeSS) (12 million
    programme)
  • Others include Geographic Visualisation of Urban
    Environments (GeoVUE)
  • And (arguably) a bunch of Computer Science

3
  • OVERVIEW
  • e-Science
  • Major research council initiative in the UK over
    the last 6/7 years
  • Matched by the US Cyberinfrastructure programme
  • Aims to address the Grand Challenges of
    scientific research
  • Suggestion is that new solutions are brought into
    view through a combination of
  • Data availability
  • Simulation and visualisation
  • Virtual collaboration
  • All supported through a new generation of
    computational infrastructure (Grid?)

4
Powering the Virtual Universehttp//www.astrog
rid.ac.uk(Edinburgh, Belfast, Cambridge,
Leicester, London, Manchester, RAL)
Multi-wavelength showing the jet in M87 from top
to bottom Chandra X-ray, HST optical, Gemini
mid-IR, VLA radio. AstroGrid will provide
advanced, Grid based, federation and data mining
tools to facilitate better and faster scientific
output.
Picture credits NASA / Chandra X-ray
Observatory / Herman Marshall (MIT),
NASA/HST/Eric Perlman (UMBC), Gemini
Observatory/OSCIR, VLA/NSF/Eric Perlman
(UMBC)/Fang Zhou, Biretta (STScI)/F Owen (NRA)


p4
Printed 09/11/2009
5
myGrid Project
Motivation In silico experiments necessitate the
virtual organization of people, data, tools and
machines. The scientific process also
necessitates an awareness of the experience base,
both of personal data as well as the wider
context of work. The management of all these data
and the co-ordination of resources to manage such
virtual organizations and the data surrounding
them needs significant computational
infra-structure support.
6
(No Transcript)
7
OVERVIEW
  • MoSeS
  • The Modelling and Simulation of e-Social Science.
  • MoSeS Objectives
  • To develop a complete representation of the UK
    population at a fine spatial scale
  • To produce rich, detailed and robust forecasts
    of the future population of the UK
  • To investigate scenarios which relate
    demographics to service provision - emphasis on
    policy applications within the health and
    transport policy sectors

8
  • MoSeS An Example
  • Leeds Social Services
  • Requirement to understand the future needs of the
    population (morbidity/ mortality)
  • Allocation of resources
  • Service delivery
  • Statutory targets e.g. reduction of (spatial)
    inequalities in life expectancy
  • Preparation of strategy demands a relatively long
    view 2027?

9
Population Projections
Source Office for National Statistics
Source Moses
10
Ethnic Projections
Source Moses
11
Growth in Elderly Population (85)2006-2031
12
Model of disability (1) of Disability (1)
Disabled in Leeds
Disabled in UK
Source BHPS
Source Moses
Estimate of the disabled in Leeds 51,599
13
Disabled in Leeds, 2006
Disabled in Leeds, 2031
Source Moses
Source Moses
Estimate of the disabled in Leeds 2031
93,698
Increase of 82!
14
(No Transcript)
15
Model of Disability (3)Scenario 5Plus1
Assume that a 65 year old in 2031 enjoys the
health of a 60 year old today
Disabled in Leeds, 2031
Disabled in Leeds, 2006
Baseline
Scenario
Source Moses
Source Moses
Revised estimate of the disabled in Leeds 2031
70,359
Increase of only 36!
16
Other Estimates of Need
17
  • Moses Methodology
  • What are the functional components of an applied
    urban simulation?
  • Recreation of a baseline population
  • A dynamic/ forecasting capability
  • A suite of service utilisation and activity
    models
  • A container (spatial decision support system?)

18
  • Moses Methodology
  • We create a synthetic representation of the UK
    population
  • Using data from the 2001 Census Small Area
    Statistics and the Sample of Anonymised Records
  • 24 million households and 60 million residents
    are individually represented
  • The synthetic population looks just like the
    actual population but no real citizens are
    included
  • The reconstructed population includes a wide
    range of social and demographic attributes age,
    ethnicity, housing, economic activity etc

19
Moses Population Reconstruction Model
20
(No Transcript)
21
Health Status (Optimised)
Actual
Model
22
Car ownership (Co-varying)
23
Moses Activity Model
24
Smoking
25
Carers
26
Diabetes
27
  • MoSeS Dynamic Model

28
Moses Dynamic Model
29
Migration Model
  • We combine two approaches
  • A person-specific general model, using
    probabilities of migration derived from the BHPS
    applied to cloned individuals in households
    derived from the 2001 Census SAR
  • Location specific information about migration
    intensities in small areas (2001 Census SMS),
    which are used to modify the results of the
    person-specific model
  • The model has a two stage procedure
  • Migrant generation protocol
  • Migrant distribution protocol

30
Migrant generation protocol
  • Assess migration probabilities from an analysis
    of BHPS data, 2000-2004 for
  • a) households
  • b) groups
  • c) individuals
  • Major drivers of migration identified using a
    stepwise chi-squared estimation procedure
  • Households age of head, household size, housing
    type
  • Individuals age, household size, marital status
  • Groups merged with individuals (small numbers)
  • National rates are locally adjusted by age using
    the Census Migration Statistics (SMS)

31
Migrant generation households
32
Migrant generation individuals
33
Migrant distribution protocol
  • The problem can be described as follows
  • Estimate migration rates by location, age,
    household size and housing type this process
    creates a stock of vacant housing
  • For each migrant, by location and household type
    (age, size) find a destination location by
    location and house type
  • Calibrate this process using data on known moves
    (by distance from the census SMS) and known
    assignments of household type to house type
    (BHPS)

34
Simulation Database
Update Location and Dwelling Characteristics
1
5
Migrant generation model
2
2
Aggregate To Migrant Population
Aggregate To Vacant Dwellings
Migration distribution protocol ( See Birkin and
Clarke 1987 Nakaya et al. 2006)
Spatial Interaction Model
3
Compute dwelling preference for each migrant
4
35
Migrant distribution model distribution model
Lambda Calibration
36
(No Transcript)
37
Model Results Aireborough
Observed
Predicted
38
Model Results Seacroft
Observed
Predicted
39
Model Results Headingley
Observed
Predicted
40
Agent-based simulation of student migrants
  • Agent-based simulation of student migrants
  • We recognise the following groups
  • First year undergraduates
  • Other undergraduates
  • Master students
  • Doctoral students
  • We apply the following rules
  • Each group is allowed set years to stay in an
    area
  • Students stay close to their university of study
  • They dont do marriage and fertility

41
(No Transcript)
42
(No Transcript)
43
(No Transcript)
44
  • Moses Methodology Architecture

45
Moses Selection Portlet
46
Moses Architecture
47
Moses Mapping Portlet 1 Google Maps
48
Moses Mapping Portlet 2 SeeGeo
49
  • Moses Discussion
  • 1. Moses is not the only work in this area in
    either an academic or a policy environment
  • But has some interesting and unique features!

50
  • Moses Discussion
  • 2. This work has both an intellectual and a
    practical value
  • Even though it is not critical
  • Sometimes it is necessary to be constructive as
    well

51
  • Moses Discussion
  • 3. This work is hard
  • Maybe too hard?
  • Scale back ambition?
  • Extend capability/ resourcing?

52
  • Moses Conclusions and Next Steps
  • There is still much work to be done to establish
    a convincing set of demonstrator applications for
    urban simulation
  • Enhanced visual representation of simulation
    outputs is one key ingredient
  • Collaboration with GeoVUE has important strategic
    value
  • Embedding this research more clearly within a
    paradigm of (generative) social simulation is a
    potential means to re-enter the mainstream
  • Genesis project?
About PowerShow.com