Crowds and Delegate – Emergent Behaviours

Crowd, transport and urban simulations are at their roots down to ‘Agents’ or ‘Objects’ that are assigned a set of rules as to how to moves in relation to both the environment and other agents around them. 3D Studio Max has a built in ‘Crowd and Delegate’ system which can be used to assign behaviour and therefore create realistic traffic of pedestrian systems in 3D space.

The movie below displays our first tentative steps to explore emergent behaviour via the introduction of simple rules. The movie starts out with a basic ‘wander’ behaviour where the agents only knowledge is the shape of the surface. Moving on we assign each of our ‘cubes’ (of which we have become quite fond of…) a level of vision so they can see ahead and therefore avoid each other and objects in their environment.

Crowd and Delegates – Emergent Behaviour from digitalurban on Vimeo.
Thirdly, the agents seek a ‘sphere’ which could be viewed as a source of food. While being aware of each other and tweaking the way the cubes move a swarm behaviour emerges. Finally, we introduce competing groups with two priorities, firstly to eat and secondly to stay as a group. The majority choose the group over the food but a couple stray off in search of sustenance and lose the other members.

All of these models are going into our exhibition space previewed below to allow a step by step guide to the principles of agent based modelling.

The virtual exhibition space should be online for Windows and Mac in the next few weeks.

Downloadable Preview – GENeSIS Exhibition Space

The following exhibition space is a proof of concept, looking at the ability to share and display city datasets and simulations within an interactive game engine. Available for download on both the PC and Mac (intel) platforms the space is the result of a few days work with the Unity Engine, it is intended to be viewed in the spirit of development rather than a completed product.

The room includes our first ‘crowd and delegate’ models direct from 3D Max, created as basic wander and avoid simulations they provide the building blocks of emergent behaviour within the cityscape.

City wide data sets can to be honest be very ‘dry’, the whole point of digital urban is to look at new ways to outreach, visualise and ultimately communicate urban data. The ability to include 3D models via ESRI ArcScene is a notable step forward, pictured below is the retail and office space in London measured on a 500m grid. We note some polygon issues here but these are known and we think we have a way to fix them – its to do with the way ArcScene exports, the model forms the centre of the exhibition space:

The room features various architectural models, including the Swiss Re building and the GLA in London, it also features a number of our latest output movies, the London LiDAR and Second Life Agents are of particular note.

The model is, as we mentioned, proof of concept, the next step is the addition of themed rooms and a more organised structure. We think the concept of virtual exhibition spaces is a strong one, so as ever any comments are most welcome…

Download the model for Windows XP/Visa (221 Mb zip file)

Unzip the file, open the folders and run the .exe file.

Download the model for Mac (222 Mb zip file)

Extract and simply run the .dmg file.

Use the mouse to look around, W/S move forwards/backwards, Space to jump.

GENeSIS Exhibition Space

We have spent the last few days giving the game engine Unity a spin. The pro version has various additions to the lower cost indie edition, most notably for our use the ability to import movies as textures and use dynamic shadows. Our movie below provides an update on progress:

Unity: Creating a City Exhibition Space – Update 2 from digitalurban on Vimeo.

The aim is to create an exhibition space exploring simulation and the city… more to follow.

Visualising City Datasets

The movie below is a visualisation of office and retail space in London. Using data kindly supplied by the Economics Unit at the Greater London Authority, Duncan Smith a PhD student here at CASA has calculated the amount of retail and office in London per 500 metre grid square:

Duncan carried out the analysis in ESRI’s ArcScene as part of his PhD. Intriguingly it is possible to export from ArcScene into Autodesk’s 3D Studio Max allowing a much higher level of visual fidelity. Of course once it is in max you can then export to a number of other platforms, such as Unity as our previous post on digital urban explained using the same data.

Here at CASA we have just completed the initial phase of our London database, as such we will be exploring more ways to visualise city based datasets in forthcoming posts.

ESRC Seminar Series: Microsimulation Modelling

Four seminars will be held over the spring and summer of 2009 which will provide an opportunity to evaluate the state of play and research opportunities in the field.  The first two seminars will be held in London on April 2nd and May 6th, and the others in Leeds (July 2nd) and Brighton (September 16th).  The full programme is shown below.�
The first seminar deals with the theme of ‘scaling up, scaling down’.  Major speakers include Neil Ferguson (Imperial College) and Holly Sutherland (University of Essex).  There will also be contributions on the MoSeS dynamic model, and on the GENeSIS e-infrastructure.  The second seminar on the theme of ‘adding behaviour’  looks of particular interest to the GENeSIS community.  The presenters include Edmund Chattoe-Brown (co-investigator of the SIMIAN project), Gary Polhill (Macauley Institute) and our own Alison Heppenstall.  Seminar 3 is concerned with land-use and transportation modelling, while the final seminar will adopt a more agenda-setting theme.
The series is organised by Dr Paul Williamson (University of Liverpool) .   Paul began his academic career at Leeds working with Phil Rees on problems relating to simulation and the delivery of social care.  His work on the development and evaluation of simulation algorithms is particularly well-regarded (Williamson et al, 1998; Voas and Williamson, 2001).  Paul has also written on the theme of geodemographics:  another  heavily cited paper with David Voas highlights the spatial diversity which is typically assumed away by  geodemographic classifications ).  Paul Williamson is editor of the International Journal of Microsimulation.







ESRC Seminar Series ‘Microsimulation modelling in the UK: bridging the gaps’



A short series of four closely-spaced seminars designed to:

Identify and agree common areas of challenge
Encourage greater/more



  • pooling of effort
  • sharing of existing solutions
  • collaborative research grant applications
Planned programme

Seminar 1 ‘Scaling up; scaling down’




Thursday 2nd April; London
Invited speaker / Team




Prof Neil Ferguson (Imperial)  

Large scale modelling of flu epidemics  

James Carpenter (LSHTM)  

Bootstrapping and multiple imputation  

Holly Sutherland / EUROMOD  

Flexing to add more countries/tax-benefit systems  

Mark Birkin / MOSES  

GRID/parallel computing  

Mark Birkin / MOSES  

Dealing with migration in sub-national dynamic msms  

Chris Drane / DWP  

Bigger vs. faster  

Paul Williamson (Liverpool)  

Creating synthetic sub-regional baseline populations  

Seminar 2 ‘Adding Behaviour’ 

Wednesday 6th May; London
Invited speaker / Team








Prof Alan Duncan (Nottingham)  

Economic behavioural response:state of the art  


Economic behavioural response: practical challenges  

Mike Murphy (MAP2030)  

Modelling kinship  

Ruth Hancock (MAP2030)  

Modelling demand for care  

Edmund Chattoe-Brown  

Agent-based modelling  

Alison Heppenstall  

Agent-based modelling  

Gary Polhill / FEARLUS  

Modelling evolving patterns of land-use  

Seminar 3 ‘Moving beyond tax-benefit and demographic modelling’




Thursday 2nd July; Leeds
Inivited speaker / team








Transport microsimulation  

Kai Nagel (Berlin)  

Transport microsimulation  

David Simmonds  

Transport microsimulation  

Ben Anderson / Chimera  

Retail / expenditure  

Dimitris Ballas (Sheffield)  


David Bell (Stirling)  

Demand for care  

Gary Polhill / FEARLUS  

Modelling evolving patterns of land-use  


Seminar 4 ‘Bridging the gaps’ / ‘Setting the agenda’



Friday 11th September; Brighton (as part of BSPS annual conference)
Invited speaker / team











How to build a coherent national msm effort



Statistics Canada



How to build a coherent national msm effort






What we are doing; what we can share; where next?

























































Crowdsourcing Spatial Surveys and Mapping

Below is a paper we will be presenting in March at GISRUK 2009. The full reference is:

Crooks, A. T., Hudson-Smith, A., M., Milton, R., and Batty, M. (2009), Crowdsourcing Spatial Surveys and Mapping, in Fairbairn, D. (ed.), Proceedings of the 17th Geographical Information Systems Research UK Conference, Durham University, England.

We thought we would put it on-line, to gauge peoples thoughts about it as it is the product of the crowd. Any comments and suggestions are most welcome.

Why blog about this work? It demonstrates the potential of crowdsourcing peoples opinions to specific questions over space and time both statistically and geographically, such work potentially allows one to crowdsource peoples perceptions on: fear of household burglary, quality of local schools, who would you vote for? etc. Additionally it is the ability to access real time information and use it for a purpose. For example, with the growth in mobile phones with built in GPS (such as the iPhone) if one had enough participants one could use the data for calibrating pedestrian or traffic simulations and therefore help potentially understand human behavoir. Such as peoples daily movement patterns (see urbanTick for such work).

Crowdsourcing Spatial Surveys and Mapping

1. Introduction

This paper presents the potential of linking the GMap Creator software and the MapTube web service to create near-real time spatial surveys. Three different surveys will be presented which map people’s perceptions about certain questions, including the current financial crisis, anti-social behaviour and peoples thoughts on road pricing. Basic results will be highlighted for each and the geodemographic profiles of respondents will be explored. However, before discussing this, the underlying technologies that we use for the creation of the surveys: GMap Creator and MapTube, will be introduced.

1.1. GMap Creator

GMap Creator is a free piece of software that takes a shapefile and enables the creation of thematic layers which can be quickly and easily integrated into Google Maps in a simple ‘point and click’ manner (see Hudson-Smith et al. (under review) for more details). Using GMap Creator, it is possible to overlay pre-rendered thematic tiles on top of street and satellite views of Google Maps, making it possible to show complex areal coverage’s. The purpose of such a tool is to build feature rich cartographic websites that may easily be used and interpreted by individuals who have limited experience of spatial data handling (e.g. Gibin et al., 2008) rather than for more formal exploratory spatial data analysis.

1.2. MapTube

MapTube ( combines the generic idea of YouTube where users can share information with the ability of GMap Creator to create thematic maps. MapTube provides a ‘place to put maps’ as we demonstrate in Figure 1, which highlights the most viewed maps currently on the MapTube site. MapTube acts as a portal for geographic data, data is not stored on the site. Every map hosted on MapTube is held on an outside server, and pulled in using the XML file which is automatically created when using GMap Creator. This allows data creators to maintain ownership of the data. MapTube allows one to view and compare different datasets as a series of layers (i.e. mashup) through the Google Map interface. However, we are currently working on an implementation for OpenLayers (see Milton, 2008).

Figure 1. MapTube home page showing the most popular maps.

2: Near Real-Time Spatial Surveys

Not only does MapTube allow people to share and view other people’s maps but it can also be used in more innovative ways. For example, as web surveys are often aspatial (e.g., the ability to combine GMap Creator and MapTube offers a simple solution to build spatial surveys for large areas. Figure 2 shows the process of creating the near real-time maps. Users are asked a series of questions and to enter their postcode so that the results can be geo-coded. This is then sent to a web server, time stamped and stored in a database. Every 30 minutes (however, this can be varied) a script is run to create a new shapefile, compiling all the results from a survey, aggregating them into a spatial units (in this case postcode districts). The shapefile is then passed to GMap Creator along with an XML file containing information including: settings for colour thresholds, maximum level of zoom and the field name of the shapefile for which the map is to be created on. GMap Creator runs creates a series of image tiles which updates the map on MapTube which can then be served back over the internet.
Figure 2. The process of gathering, storing and creation of maps.
What follows are three surveys which map people’s perceptions about certain issues done in association various BBC organisations. For each survey no personal information was collected and participants were reassured that actual locations could not be identified. This was ensured through the use of postcode districts rather than the postcode unit or building address therefore preserving data confidentiality. Used in conjunction with MapTube, it allowed participants and other users to take other information and lay the maps on top of one other.

2.1. Mapping the Credit Crunch

A pilot study was carried out as an experiment to create a mood map of the credit crunch within the United Kingdom in conjunction with BBC Radio 4 iPM show . Based on what is the “singly most significant factor hurting the person the most about the credit crunch”, participants were asked to enter the first part of their postcode (postcode district) so their responses could be geo-tagged along with one of six options to choose from: mortgage or rent, fuel, food prices, holidays, other, or the credit crunch is not affecting me.
Between 26th April and 29th June 2008 there were 23475 responses to the survey with 48.8% of response saying that fuel was most significant factor hurting the person the most about the credit crunch (Figure 3). However there was spatial variation around the country with more respondents within Greater London saying it was either mortgage or rent, or food as shown in Figure 4.
Figure 3. Overall percentages for the Credit Crunch Survey.
Figure 4. Results of the Credit Crunch Survey Focused Around London (Note: the Colour represents the Most Frequent Response in the Postcode District).

2.2. Anti-Social Behaviour in East Anglia

The Credit Crunch Map has since led to BBC Look East, using the system to map peoples perceptions of anti-social behaviour.

Anti-Social Behaviour in East Anglia.

Each respondent was asked “what problems do you face where you live?” Respondents had five options: drunken youths, noisy neighbours, boy racers, no problems, great community and no problems. The survey ran between 4th July 2008 and 12th September 2008. During this time 6902 responses were received. Figure 5 shows the overall percentages, with 33.7% saying drunken youths with the other categories broken down relatively evenly between 14 to 18%. Figure 6 maps the responses with drunken youths clustering around urban areas such as Norwich and Newmarket.

Figure 5. Overall Percentages for the Anti-Social Behaviour Survey.
Figure 6. Results of the Anti-Social Behaviour Survey Focused Around East Anglia (Note: the Colour represents the Most Frequent Response in the Postcode District, click here to see the map).

2.3. The Manchester Congestion Charge

There was a proposal for Manchester in introduce a congestion charge zone motorists pay to drive in and out of the city at peak times. The BBC North West Tonight program wanted people’s reaction to the proposed Greater Manchester congestion charge, from within the city but also people who drive in from outside the region. As these people don’t get a vote but may end up paying the charge (subsequently the people of Manchester said no).

The Manchester Congestion Charge.

People were asked the following question “If a congestion charge is introduced in Greater Manchester, along with significant investment in public transport, will you:” and then asked to select one of the following options: drive and pay the charge, drive at different times, use public transport/motorbike/bicycle, work or shop elsewhere, or I am not affected by these changes. The survey began on 14th October 2008. By the 10th December 2008, there were 14933 responses with 46.8% saying they would work or shop elsewhere (Figure 7). This online collaboration provided a unique picture of how well the proposal was going down across the north west of England as the map is updated every day (Click here to see the final map).

Figure 7. Overall percentages for the Manchester Congestion Survey.

3. Geodemographic Profiles of Respondents

While we only asked for respondents or their first part of their postcode, many entered their full postcode as can be seen in Table 1. We note that this in not a representative sample but it does provide an opportunity to further investigate who is responding to such surveys. To gain this understanding we use two geodemographic classification schemes. First, the Acorn classification from CACI which categorises neighbourhoods based on multidimensional socio-demographic attributes. The second being the e-Society geodemographic classification (Longley et al., 2008) which categorizes neighbourhoods based on their engagement with new information communication technologies.
For the analysis, index scores was calculated. An index score compares the over or under representation of a specific target variable against a base population (e.g. the national average). Where a score of 100 is the national average, 200 is double the national average and a score of 50 is 50% below the national average. From such analysis it is the middle and upper classes who are over-represented within the surveys as shown in Table 2, this potentially relates to demographics of the readers, listeners, and viewers Radio 4 and the BBC news. The over representation of E-business users in the E-society classification (Table 3) suggest many respondents are answering the questionnaire while at work. Furthermore the geodemographic profiles of responses to individual questions can also be explored as seen in Table 4. Across all demographic groups the biggest concern was fuel.
Table 1. Total Number of Respondents to Surveys and Number Who Entered Their Full Postcode.

Table 2. Index Scores of Respondents by Acorn Category Classification.

Table 3. Index Scores of Respondents by E-Society Group Classification.

Table 4. Percentage of Responses to the Credit Crunch Survey Broken Down by Acorn Category.

4. Discussion

This paper has demonstrated the potential of using GMap Creator and MapTube for near-real time spatial survey thus providing a resource to map the nations opinions to specific questions over space and time both statistically and geographically. The potential of this approach for gathering spatial information is enormous. For example, it could easily be used to gather other information such as fear of household burglary, the quality of primary school education and so on. We consider this in many senses this to be Web 2.0 and Neogeography in action.

However, the geodemographics of the respondents shows there is an inherit bias in who is answering the questions and there is the question to whether or not respondents are influenced by the maps before answering the questions. Further work is to explore how the maps evolve over time, as each response is time stamped and how this relates to news headlines. Additionally, we are currently exploring the geodemographic profiles of each survey in more detail. We have currently re-run the credit crunch with the BBC with slightly different options to the answer.

The question remains the same – “what single factor is hurting you most about the credit crunch?” But we decided to change the categories slightly:Mortgage or rent, Petrol, Food prices, Job security, Utility bills, or Not affected. This survey ran between 5th October 2008 and 3 February 2009 and has now closed. The final map can be viewed here. During this time we received 20,072 responses, which can be broken down as follows (Figure 8): Mortgage or Rent 11.05%, Petrol 4.7%, Food Prices 11.89%, Job Security 27.25%, Utility Bills 21.92%, and Not Affected 23.20%

The Return of the Credit Crunch on the BBC Site
Figure 8: Overall percentages for the Credit Crunch Survey

5. References

Gibin M, Singleton AD, Mateos P, and Longley PA. (2008) Exploratory cartographic visualisation of London using the Google Maps API Applied Spatial Analysis and Policy 1(2) pp85-97.

Hudson-Smith A, Crooks AT, Gibin M, Milton R, and Batty M (under review) Neogeography and Web 2.0: Concepts, Tools and Applications, Journal of Location Based Services.

Longley PA, Webber R, Li C, (2008) The UK geography of the e-society: a national classification Environment and Planning A 40(2) pp362-382.

Milton R (2008) GMap Creator, OpenLayers and OpenStreetMap CASA Blog. Available at .

The London Database

A quick update as we have been working on a number of projects. One is creating a simplified road network for London to explore the road structure in relation to network theory (see Masucci) but also for its use in accessibility measures. Our second project is building a detailed land use database for London (using SQL Server which we access through ArcSDE).

The purpose of the database is so our research group can use it for various applications (such as land use modelling, residential agent-based modelling, urban sprawl analysis, sustainability, rain water harvesting etc). The aim of the land use database is to tag all the buildings within London with various attributes such as use, whether it is a house, a flat or an office etc. The data sets we are using include; Ordnance Survey MasterMap and Address layer 2 , building heights via LIDAR data from InfoTerra. We are using Cities Revealed data for residential building types and age along with several other datasets. When combined it will allow for fine scale and extensive modelling of the of London’s housing market & built environment.

Below are some preliminary outputs, including a land use visualisation of the Isle of Dogs, the London Borough of Tower Hamlets broken down by residential property types and finally residential density within a section of the Isle of Dogs.

Isle of Dogs Land-use 3D Visualisation (Red is Residential, Dark blue is Office, Light blue is Office Mixed Use).

Housing Classification of Tower Hamlets, London (yellow is terraced housing, blue is flats and grey is non residential).

Residential Density within the Isle of Dogs (Dwellings per Hectare)

CASA & CSAP S4 Modelling Tour Workshop

CASA (with our partners in CSAP at Leeds) hosted a two day workshop on the 8th and 9th January 2009. The first day was designed to showcase our use of new Web 2.0 technologies for mapping and visualizing information about cities; the second day involved technical workshops on simulation. The workshop  was part of the of the S4 European Spatial Analysis network modelling tour.
Over 150 people both from the public and private sector came to the event from all across Europe. The first day of the event was designed to showcase CASA’s use of new technologies for mapping and visualizing information about cities and was entitled “Geographic Information in a Web-Based World.” Talks ranged from introducing GMapCreator and MapTube which enable web-based mapping for sharing and visualising geographic information, to public engagement via the London Profiler, Public Profiler and the E-Society Classification websites. The geography and ethnicity of people’s names was explored which introduced the WorldNames and Onomap websites.
Other talks on the first day explored the use of MapTube and GMapCreator for Crowdsourcing near-real time spatial surveys and understanding crowdsourced geographical information via the analysis of OpenStreetMap. On a more data oriented side, there were talks on exploring urban data collection and mapping, analysing and visualising fine scale urban form and socio-economic datasets. The day concluded with a talk by Andrew Hudson-Smith from Digital Urban on Web 2.0 and neogeography in real and virtual spaces: from geocaching through to Second Life.

The second day of the workshop was entitled “Developments in Urban Models, Simulation and Spatial Analysis” and talks ranged from: rank clocks and scaling in city sizes, geodemographics, retail modelling, the need to capture urban form patterns and processes in agent-based models, pedestrian modelling, consumer behaviour, microsimulation and 3D visualisation and communication of agent-based models.
Click here to see the full program and to download the presentations.

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GENeSIS History

This is a short history of our cooperation through the National Centre for e-Social Science


From 2005, two of the key research nodes of NCeSS were located in London at UCL – GeoVUE and at Leeds in the University of Leeds – MoSeS. GeoVUE ended on the 30th September 2008 and GENeSIS began on 1st October 2008. This is a convenient point to explain all these terms. GeoVUE stands for Geographic Virtual Urban Environments. It was a project which essentially developed web-based services for the visualisation of 2D maps producing in particular GMapCreator and MapTube amongst other software for map mashup and then moved on to consider importing 2D maps and related geospatial data into 3D environment, specifically games and virtual worlds but also 3D GIS, CAD and 3D virtual globes.


GENeSIS is a little different in that it stands for GENerative e-SocIal Science. The acronym like all good symbols for research projects can be unpacked in diverse ways which emphasise our focus on space and simulation but we consider the previous statements the baseline definition. It joins GeoVUE to MoSeS which is the project that the Leeds node has developed in the first phase of NCeSS funding. MoSeS is a microsimulation model of the UK economy developed using microsimulation logics and applied to subdivisions of the UK space at different spatial scales. It is used for policy analysis such as the impact of aging on public services. MoSeS stands for MOdelling and Simulation for e-Social Science.


GENeSIS (= GeoVUE + MoSeS) is to develop microsimulation models for social science and to link these to the emerging paradigm of agent-based models. The UCL node will develop ABMS and their visualisation while the Leeds node will link microsimulation to ABMs. Model development and visualisation will take place in both nodes and the programme of research will be integrated. A rudimentary web site has been set up ( but we consider that this blog will take over as our basic web presence, once we have experimented with formats.


Mike Batty, CASA, UCL