Simulacra

The Resources page contains information on useful presentations, articles, and other material of interest to researchers working with Land Use Transportation Models and wrestling with complex systems.

• Posts from Simulacra
• Articles in peer-reviewed journals
• Links to other resources

 

Posts

MapThing v1.0 Processing Library

One of the objectives of the COSMIC project is to "extend our current techniques of visualising complex spatial systems... [to] enable a wide range of stakeholders to be involved both in understanding such complexity and using it in policy analysis." Normally, this type of task would mean identifying a set of existing tools and producing some alternative visualisations of the same data to see what works and what doesn't; however, as seems to be common with this type of work, I soon found that there weren't any tools to do rapid visualisation and exploration of geodata (bar City's excellent, but not entirely relevant to what I was trying to do, giCentre Utilities).

So, without further ado: MapThing allows you to perform a range of useful mapping (in the geographical sense) functions within Processing and offers a collection of classes for reading ESRI-compliant Shape files (a.k.a. shapefiles) and CSV point data, and then displaying them as part of a sketch. My objective here was not to implement a full-fledged GIS system, but to make it as easy as possible to take a set of geographically coded files and do something with them inside Processing without needing to think about how to map the coordinate spaces or how to read a shape file and extract useful information from it.

There are four main classes with which you want to concern yourself:

You can also read in point data (tested) and line data (not tested) from CSV files and project this using the same mechanism.

The PDE sample file offers a working example of most of what is discussed above.

The library is available for download here: http://www.reades.com/MapThing.zip

Detailed feedback or suggestions are welcome.

jon
 

Running Spatial Interaction Models in JAVA

Overview

Recently we have been developing a Java based set of software components for the field of land use transportation modeling. The system has being designed for integrating various open source tools for the rapid assessment of urban futures. We have made use of extensive object oriented technologies to implement a general framework and data exchange environment, with the potential to embed common subsystems like GIS, simulation models, management tools, databases and other external data sources.

In this post, I am going to describe how to run spatial interaction models in Java platform using a basic library we have developed in the context SIMULACRA. The library defines a group of classes that represent a set of possible behaviors for spatial interaction models based on Wilson s (1972).

Probably one of the more interesting parts of this library from a design standpoint is the use of the Strategy pattern to implement the family of spatial interaction models. These behaviors should be flexible to be plugged into an application, changing the functionality on the fly. A UML class diagram is shown here:

Based on the UML class diagram, there are four ways to perform the running of a spatial interaction models (gravity, production constrained, attraction constrained and double constrained) and two ways to perform the generalization of the travel cost matrix (inverse power function and negative exponential function).

SpatialInteractionModel This is the class that will use different strategies to run the models. It keeps a reference to the ISpatialInterationModel instance. This class uses the setTypeOfSpatialInteractionModel method to replace the current strategy with another strategy. Also will use the different strategies to calculate the generalized travel cost using the method setTypeOfDistanceFunction.

ISpatialInteractionModel The interface defines all the methods available for the SpatialInteractionModel to use.

GravityModel, ProductionConstrainedModel, AttractionConstrainedModel and ProductionAttractionConstrainedModel These classes implement the ISpatialInteractionModel interface using the specific set of rules for each calculateInteractions method.

InversePowerFunction and NegativeExponentialFunction - These classes implement the IDistanceFunction interface using the specific set of rules for each calculateDistanceFuntion method.

Where to start?

This quick guide describes the usage of our spatial interaction model library in Eclipse as a Java IDE.

For the realization of this tutorial is necessary to be familiar with the basic concepts of spatial interaction models and object oriented programming with Java and the use of Eclipse IDE.

If you are not familiar with spatial interaction models I will advice you to first read this article by Professor Sir Alan Wilson.

If you are not familiar with Eclipse IDE I will advice you to first try this tutorial by Lars Vogel.

Used Libraries

For the development of the tutorial will need the following tools

• For the spatial interaction models we are going to use the latest jar file from our Google Code project home page casa-simulacra.

Step 1. Defining the problem

To explain how to run spatial interaction models with our library we will consider a problem of predicting flows shopping expenditure between a four-zones city.

Shopping expenditure data for the four-region city will be:

Weekly shopping expenditure (GBP)

Zonal Retail Floorspace (square metres)

Travel cost between zones

Step 2. Import project into Eclipse

First you will need to download an eclipse project we have prepared for this guide from here.

After start Eclipse, select from the menu File -> Import.

In the import wizard select "Existing Projects into Workspace" and click Next.

Select the "Select archive file" option and click on Browse to select the file that you just had downloaded.

After select the file click Finish to import the project into the workspace. A new project is created and displayed as a folder in the project explorer view. Open the corresponding folder to the "uk.ac.ucl.casa.simulacra.first" project.

Select the folder src, select the package "uk.ac.ucl.casa.simulacra.first" and then open the class MyFirstSpatialInteractionModel. The class should be something like:

package uk.ac.ucl.casa.simulacra.first;
public class MyFirstSpatialInteractionModel  


	/  


	   @param args


	  /


	public static void main(String[] args)  


		// TODO Auto-generated method stub


		double[] shoppingExpenditure =  355,455,255,570 ;


		double[] retailFloorspace =  720,376,930,321 ;


		double[][] travelCost =   3,11,18,22 , 12,3,13,19 , 15,13,5,7 , 24,18,8,5  ;


	 


 

Note that the class has already declared the variables related with the definition of the problem in Step 1.

Step 3. Creating an Spatial Interaction model object

To create the spatial interaction model we just will need to add few lines after the following line

double[][] travelCost =   3,11,18,22 , 12,3,13,19 , 15,13,5,7 , 24,18,8,5  ;

The lines are

SpatialInteractionModel model = new SpatialInteractionModel(shoppingExpenditure, retailFloorspace);
model.setTypeSpatialInteractionModel(new AttractionConstrainedModel());


model.setTypeDistanceFunction(new NegativeExponentialFunction());

Step 4. Run the model and print the results

To obtain the predicted trip matrix for shopping expenditure flows for the four-zones city we just need to run the model with the following line of code

double[][] tripMatrix = model.calculateInteractions(travelCost, 0.1);

Note that to run the model, the calculateInteractions() method needs to parameters, travelCost which has already been defined and the frictionParameter. For the purpose of this tutorial we will use a naive approach to assign a value of the friction parameter, we will simple guess the value. In following posts we will discuss the implementation of different methods to calculate a better estimation of the friction parameter.

Now, we just need to print the predicted trip matrix for shopping expenditure flows adding the following lines

System.out.println("Origin   "   "Destination   "   "Flow");
for (int i = 0; i < shoppingExpenditure.length; i  )  


	for (int j = 0; j < retailFloorspace.length; j  )  


		System.out.println(i   "        "    j   "             "   tripMatrix[i][j]);


	 


 

Finally, to see the results you just need to run the application by right click on the MyFirstSpatialInteractionModel.java editor -> Run as -> Java Applciation

At the end your class should look like:

package uk.ac.ucl.casa.simulacra.first;
import uk.ac.ucl.casa.scale.spatialinteraction.exception.SpatialUnitsException;


import uk.ac.ucl.casa.scale.spatialinteraction.model.AttractionConstrainedModel;


import uk.ac.ucl.casa.scale.spatialinteraction.model.NegativeExponentialFunction;


import uk.ac.ucl.casa.scale.spatialinteraction.model.SpatialInteractionModel;


public class MyFirstSpatialInteractionModel  


	/  


	   @param args


	   @throws SpatialUnitsException


	  /


	public static void main(String[] args) throws SpatialUnitsException  


		// TODO Auto-generated method stub


		double[] shoppingExpenditure =  355,455,255,570 ;


		double[] retailFloorspace =  720,376,930,321 ;


		double[][] travelCost =   3,11,18,22 , 12,3,13,19 , 15,13,5,7 , 24,18,8,5  ;


		SpatialInteractionModel model = new SpatialInteractionModel(shoppingExpenditure, retailFloorspace);


		model.setTypeSpatialInteractionModel(new AttractionConstrainedModel());


		model.setTypeDistanceFunction(new NegativeExponentialFunction());


		double[][] tripMatrix = model.calculateInteractions(travelCost, 0.1);


		System.out.println("Origin   "   "Destination   "   "Flow");


		for (int i = 0; i < shoppingExpenditure.length; i  )  


			for (int j = 0; j < retailFloorspace.length; j  )  


				System.out.println(i   "        "    j   "             "   tripMatrix[i][j]);


			 


		 


	 


 

And, the results should look like

Final Comments

This library has been the based for the implementation of one of the first models of Simulacra dealing with residential, retail and employment location. Here you can see a sample of what the application looks like

 

Articles

Metropolis or Region: On the Development and Structure of London

MOGRIDGE M. and PARR J. B. (1997) Metropolis or region: on the development and structure of London, Regional Studies 31, 97—115.

Drawing on a disparate range of sources and viewing the question from several perspectives, an attempt is made to trace the development of London over the period since 1800. An account of the physical expansion and population growth is outlined, with London de ned at a number of distinct scales. Attention is first focused on London as a metropolis, and various modelling techniques are used to illustrate the nature of metropolitan expansion. Consideration is given to the possibility that the changing spatial distribution of population through migration may be likened to a well-known process in physics. This is followed by an analysis of London at the broader scale of a region, with similar modelling techniques being employed. Finally, the question is raised as to whether London can still be meaningfully viewed as a metropolitan entity or whether a regional perspective is now more appropriate.

The Time Scale of Urban Change

WEGENER, M. and GNAD, F. and VANNAHME, M. (1986) The Time Scale of Urban Change, Advances in Urban Systems Modelling(Hutchison, B. and Batty, M. eds.)

Human settlements evolve over a long time span by the cumulative efforts of many generations. The resulting physical structure of cities displays a remarkable stability, changing only in small increments in normal times. However, underneath this major current of urban change there are more rapid fluctuations or cycles affecting the way the physical structure is utilized. Most existing urban models do not pay the requisite attention to the different time scales of urban change. An outline of an urban model being multilevel in its temporal dimension is sketched.

 

Changing travel to work patterns in South East England

TITHERIDGE, H. and HALL, P. (2006) Changing travel to work patterns in South East England, Journal of Transport Geography14, 60—75.

The Greater South East England region of the UK constitutes a "global mega-city region". The UK Government's 2003 Sustainable Communities strategy proposes major new growth centres in South East England at Ashford, Milton Keynes, Stansted, Cambridge and Thames Gateway. These, along with the upgrade of the West Coast Main Line in 2004 and the completion of the Channel Tunnel Rail Link in 2007, could have major impacts on commuting patterns. To understand the effect of these changes on commute distance and mode choice, the relationships between travel-to-work patterns and socio-economic and land-use characteristics are examined. The analysis suggests that the creation of the new growth centres may result in increased car use but is unlikely to result in longer journeys to work.

 

Exploratory mapping of commuter flows in England and Wales

NIELSEN, T.A.S. and HOVGESEN, H.H. (2008) Exploratory mapping of commuter flows in England and Wales, Journal of Transport Geography 16, 90—99

The paper uses the origin destination commute data published from the 1991 and 2001 Census to explore the developments in commuting and interaction patterns within England and Wales. Focus is on the geographical variations and a map of commuter flows is presented. Commuting is stretched out along a national corridor from London to Manchester. An important change between 1991 and 2001 is a widening of the corridor that can be explained as the result of the deconcentration of population and jobs in combination with increasing commute distances allowing rural areas to be connected with the jobs and services of the centres in the corridor.

 

A Study of Alternative Land Use Forecasting Models

ZHAO, F. and CHUNG, S. (2006) A Study of Alternative Land Use Forecasting Models, Final Report to the Florida DOT Systems Planning Office

FSUTMS requires future land use forecasts as input data to predict future travel demand and transportation needs. Given that the performance of the FSUTMS models relies heavily on the accuracy of land use forecast, there is a strong desire by planners to improve model input, especially for future forecast years. The purpose of this study is to survey the state-of-the-art and the state-of-the-practice, as well as to investigate the potential of UrbanSim as a land use model for Florida Applications. UrbanSim is a promising model for its spatial disaggregation (use of parcels to model land development), temporal disaggregation (one-year time steps), dynamics (disequilibrium model); detailed disaggregations of households and firms, and support to activity-based travel models. In this project, UrbanSim is applied to Volusia County, Florida, based on five scenarios of growth and transportation improvements. The model was validated by comparing the simulation results to the socioeconomic and demographic data adopted in the 2020 LRTP and the 2005 InfoUSA employment data. This report describes the implementation process of the land use simulation, including data collection and processing, model estimation and validation, and scenario building and testing. The most significant efforts in this project are related to data imputation and quality control, and model parameter estimation. The UrbanSim model produced reasonable results in a reasonable amount of time. It will be important to develop tools to support data imputation and processing. The modeling results also suggest that the existing consensus building processes adopted by many local governments may need improvements to allow community visions to be better reflected through the model.

 

 

Links

Open Data & Visualisation

 

In one of the more unusual invitations that I've received over the past few years, I was asked to speak about visualisation and open data at Transport Ticketing 2012, currently happening down in South Ken. Interestingly, in spite of my various posts on visualisation and work with a variety of companies on the spatial aspects of their 'big data', I'd not really thought a great deal about the open aspect.

So I've taken the opportunity to try to pull together my thoughts not only on the relationship between the two, but also on why companies should be actively exploring whether and how to make available to others aspects of their operational data. I've grouped the talk into four areas: why should companies open up their data in the first place? to whom should they open it up once the business case exists? what data should be made accessible? how should they go about opening it up? and, finally, by way of a wrap-up, what are the potential costs and benefits that could be realised?

Although this talk is focussed on transportation visualisations, I think that many of the same ideas apply to other domains as well and hope that you find the PDF thought-provoking no matter what your line of work.

MapThing v1.0 Processing Library

One of the objectives of the COSMIC project is to "extend our current techniques of visualising complex spatial systems... [to] enable a wide range of stakeholders to be involved both in understanding such complexity and using it in policy analysis." Normally, this type of task would mean identifying a set of existing tools and producing some alternative visualisations of the same data to see what works and what doesn't; however, as seems to be common with this type of work, I soon found that there weren't any tools to do rapid visualisation and exploration of geodata (bar City's excellent, but not entirely relevant to what I was trying to do, giCentre Utilities).

So, without further ado: MapThing allows you to perform a range of useful mapping (in the geographical sense) functions within Processing and offers a collection of classes for reading ESRI-compliant Shape files (a.k.a. shapefiles) and CSV point data, and then displaying them as part of a sketch. My objective here was not to implement a full-fledged GIS system, but to make it as easy as possible to take a set of geographically coded files and do something with them inside Processing without needing to think about how to map the coordinate spaces or how to read a shape file and extract useful information from it.

There are four main classes with which you want to concern yourself:

You can also read in point data (tested) and line data (not tested) from CSV files and project this using the same mechanism.

The PDE sample file offers a working example of most of what is discussed above.

The library is available for download here: http://www.reades.com/MapThing.zip

Detailed feedback or suggestions are welcome.

jon
 

All I Want For Christmas ...

... is the biggest, fattest book I have ever contributed to, almost unknowingly. Imagine my surprise when the large parcel, almost too heavy for the postman to carry, arrived on my desk, containing a copy of the 1465 page Technical Report of the UK National Ecosystem Assessment. What had I done to deserve this? Well I appear to have contributed to Chapter 10: Urban 48 pages about the urban condition of the UK written by an assorted team of 25 authors for which it would appear I wrote something about population distribution in the UK and provided a couple of my own computer graphics yes done by me, not ArcGIS, from raw code or so I remember - well memory isn't what it was, but it's Christmas.

See for yourself. Click the link to download the chapter - sorry it isn't there yet. I will sort this soon. But if you want to read the entire thing which incidentally is the last word on Ecosystem Services, and also heavily influenced the White Paper on Building on the National Ecosystem Assessment then there is a handy web site where you can download the entire volume. In fact you can get chapter 10 if you scroll down this web page and then download it directly from the link.

Beautifully produced book I must say and actually extremely useful. Even for urbanists like me who only live in the country at weekends, I learned a lot. Quite good on urban boundaries and on land use in Chapter 10, not by me, I think Mechanicity team please note the work on boundaries.

If you want to see the book itself, it is outside my office between my mac and my smackmac. Come and marvel at the scale and size. In a time when people say the days of the physical book are numbered, they seem to be getting larger and presumably will reach infinity in 2026. In joke for those who know. Sorry. Happy Christmas.

Running Spatial Interaction Models in JAVA

Overview

Recently we have been developing a Java based set of software components for the field of land use transportation modeling. The system has being designed for integrating various open source tools for the rapid assessment of urban futures. We have made use of extensive object oriented technologies to implement a general framework and data exchange environment, with the potential to embed common subsystems like GIS, simulation models, management tools, databases and other external data sources.

In this post, I am going to describe how to run spatial interaction models in Java platform using a basic library we have developed in the context SIMULACRA. The library defines a group of classes that represent a set of possible behaviors for spatial interaction models based on Wilson s (1972).

Probably one of the more interesting parts of this library from a design standpoint is the use of the Strategy pattern to implement the family of spatial interaction models. These behaviors should be flexible to be plugged into an application, changing the functionality on the fly. A UML class diagram is shown here:

Based on the UML class diagram, there are four ways to perform the running of a spatial interaction models (gravity, production constrained, attraction constrained and double constrained) and two ways to perform the generalization of the travel cost matrix (inverse power function and negative exponential function).

SpatialInteractionModel This is the class that will use different strategies to run the models. It keeps a reference to the ISpatialInterationModel instance. This class uses the setTypeOfSpatialInteractionModel method to replace the current strategy with another strategy. Also will use the different strategies to calculate the generalized travel cost using the method setTypeOfDistanceFunction.

ISpatialInteractionModel The interface defines all the methods available for the SpatialInteractionModel to use.

GravityModel, ProductionConstrainedModel, AttractionConstrainedModel and ProductionAttractionConstrainedModel These classes implement the ISpatialInteractionModel interface using the specific set of rules for each calculateInteractions method.

InversePowerFunction and NegativeExponentialFunction - These classes implement the IDistanceFunction interface using the specific set of rules for each calculateDistanceFuntion method.

Where to start?

This quick guide describes the usage of our spatial interaction model library in Eclipse as a Java IDE.

For the realization of this tutorial is necessary to be familiar with the basic concepts of spatial interaction models and object oriented programming with Java and the use of Eclipse IDE.

If you are not familiar with spatial interaction models I will advice you to first read this article by Professor Sir Alan Wilson.

If you are not familiar with Eclipse IDE I will advice you to first try this tutorial by Lars Vogel.

Used Libraries

For the development of the tutorial will need the following tools

• For the spatial interaction models we are going to use the latest jar file from our Google Code project home page casa-simulacra.

Step 1. Defining the problem

To explain how to run spatial interaction models with our library we will consider a problem of predicting flows shopping expenditure between a four-zones city.

Shopping expenditure data for the four-region city will be:

Weekly shopping expenditure (GBP)

Zonal Retail Floorspace (square metres)

Travel cost between zones

Step 2. Import project into Eclipse

First you will need to download an eclipse project we have prepared for this guide from here.

After start Eclipse, select from the menu File -> Import.

In the import wizard select "Existing Projects into Workspace" and click Next.

Select the "Select archive file" option and click on Browse to select the file that you just had downloaded.

After select the file click Finish to import the project into the workspace. A new project is created and displayed as a folder in the project explorer view. Open the corresponding folder to the "uk.ac.ucl.casa.simulacra.first" project.

Select the folder src, select the package "uk.ac.ucl.casa.simulacra.first" and then open the class MyFirstSpatialInteractionModel. The class should be something like:

package uk.ac.ucl.casa.simulacra.first;
public class MyFirstSpatialInteractionModel  


	/  


	   @param args


	  /


	public static void main(String[] args)  


		// TODO Auto-generated method stub


		double[] shoppingExpenditure =  355,455,255,570 ;


		double[] retailFloorspace =  720,376,930,321 ;


		double[][] travelCost =   3,11,18,22 , 12,3,13,19 , 15,13,5,7 , 24,18,8,5  ;


	 


 

Note that the class has already declared the variables related with the definition of the problem in Step 1.

Step 3. Creating an Spatial Interaction model object

To create the spatial interaction model we just will need to add few lines after the following line

double[][] travelCost =   3,11,18,22 , 12,3,13,19 , 15,13,5,7 , 24,18,8,5  ;

The lines are

SpatialInteractionModel model = new SpatialInteractionModel(shoppingExpenditure, retailFloorspace);
model.setTypeSpatialInteractionModel(new AttractionConstrainedModel());


model.setTypeDistanceFunction(new NegativeExponentialFunction());

Step 4. Run the model and print the results

To obtain the predicted trip matrix for shopping expenditure flows for the four-zones city we just need to run the model with the following line of code

double[][] tripMatrix = model.calculateInteractions(travelCost, 0.1);

Note that to run the model, the calculateInteractions() method needs to parameters, travelCost which has already been defined and the frictionParameter. For the purpose of this tutorial we will use a naive approach to assign a value of the friction parameter, we will simple guess the value. In following posts we will discuss the implementation of different methods to calculate a better estimation of the friction parameter.

Now, we just need to print the predicted trip matrix for shopping expenditure flows adding the following lines

System.out.println("Origin   "   "Destination   "   "Flow");
for (int i = 0; i < shoppingExpenditure.length; i  )  


	for (int j = 0; j < retailFloorspace.length; j  )  


		System.out.println(i   "        "    j   "             "   tripMatrix[i][j]);


	 


 

Finally, to see the results you just need to run the application by right click on the MyFirstSpatialInteractionModel.java editor -> Run as -> Java Applciation

At the end your class should look like:

package uk.ac.ucl.casa.simulacra.first;
import uk.ac.ucl.casa.scale.spatialinteraction.exception.SpatialUnitsException;


import uk.ac.ucl.casa.scale.spatialinteraction.model.AttractionConstrainedModel;


import uk.ac.ucl.casa.scale.spatialinteraction.model.NegativeExponentialFunction;


import uk.ac.ucl.casa.scale.spatialinteraction.model.SpatialInteractionModel;


public class MyFirstSpatialInteractionModel  


	/  


	   @param args


	   @throws SpatialUnitsException


	  /


	public static void main(String[] args) throws SpatialUnitsException  


		// TODO Auto-generated method stub


		double[] shoppingExpenditure =  355,455,255,570 ;


		double[] retailFloorspace =  720,376,930,321 ;


		double[][] travelCost =   3,11,18,22 , 12,3,13,19 , 15,13,5,7 , 24,18,8,5  ;


		SpatialInteractionModel model = new SpatialInteractionModel(shoppingExpenditure, retailFloorspace);


		model.setTypeSpatialInteractionModel(new AttractionConstrainedModel());


		model.setTypeDistanceFunction(new NegativeExponentialFunction());


		double[][] tripMatrix = model.calculateInteractions(travelCost, 0.1);


		System.out.println("Origin   "   "Destination   "   "Flow");


		for (int i = 0; i < shoppingExpenditure.length; i  )  


			for (int j = 0; j < retailFloorspace.length; j  )  


				System.out.println(i   "        "    j   "             "   tripMatrix[i][j]);


			 


		 


	 


 

And, the results should look like

Final Comments

This library has been the based for the implementation of one of the first models of Simulacra dealing with residential, retail and employment location. Here you can see a sample of what the application looks like

Metropolis or Region: On the Development and Structure of London

MOGRIDGE M. and PARR J. B. (1997) Metropolis or region: on the development and structure of London, Regional Studies 31, 97—115.

Drawing on a disparate range of sources and viewing the question from several perspectives, an attempt is made to trace the development of London over the period since 1800. An account of the physical expansion and population growth is outlined, with London de ned at a number of distinct scales. Attention is first focused on London as a metropolis, and various modelling techniques are used to illustrate the nature of metropolitan expansion. Consideration is given to the possibility that the changing spatial distribution of population through migration may be likened to a well-known process in physics. This is followed by an analysis of London at the broader scale of a region, with similar modelling techniques being employed. Finally, the question is raised as to whether London can still be meaningfully viewed as a metropolitan entity or whether a regional perspective is now more appropriate.

The Time Scale of Urban Change

WEGENER, M. and GNAD, F. and VANNAHME, M. (1986) The Time Scale of Urban Change, Advances in Urban Systems Modelling(Hutchison, B. and Batty, M. eds.)

Human settlements evolve over a long time span by the cumulative efforts of many generations. The resulting physical structure of cities displays a remarkable stability, changing only in small increments in normal times. However, underneath this major current of urban change there are more rapid fluctuations or cycles affecting the way the physical structure is utilized. Most existing urban models do not pay the requisite attention to the different time scales of urban change. An outline of an urban model being multilevel in its temporal dimension is sketched.

 

Changing travel to work patterns in South East England

TITHERIDGE, H. and HALL, P. (2006) Changing travel to work patterns in South East England, Journal of Transport Geography14, 60—75.

The Greater South East England region of the UK constitutes a "global mega-city region". The UK Government's 2003 Sustainable Communities strategy proposes major new growth centres in South East England at Ashford, Milton Keynes, Stansted, Cambridge and Thames Gateway. These, along with the upgrade of the West Coast Main Line in 2004 and the completion of the Channel Tunnel Rail Link in 2007, could have major impacts on commuting patterns. To understand the effect of these changes on commute distance and mode choice, the relationships between travel-to-work patterns and socio-economic and land-use characteristics are examined. The analysis suggests that the creation of the new growth centres may result in increased car use but is unlikely to result in longer journeys to work.

 

Exploratory mapping of commuter flows in England and Wales

NIELSEN, T.A.S. and HOVGESEN, H.H. (2008) Exploratory mapping of commuter flows in England and Wales, Journal of Transport Geography 16, 90—99

The paper uses the origin destination commute data published from the 1991 and 2001 Census to explore the developments in commuting and interaction patterns within England and Wales. Focus is on the geographical variations and a map of commuter flows is presented. Commuting is stretched out along a national corridor from London to Manchester. An important change between 1991 and 2001 is a widening of the corridor that can be explained as the result of the deconcentration of population and jobs in combination with increasing commute distances allowing rural areas to be connected with the jobs and services of the centres in the corridor.

 

A Study of Alternative Land Use Forecasting Models

ZHAO, F. and CHUNG, S. (2006) A Study of Alternative Land Use Forecasting Models, Final Report to the Florida DOT Systems Planning Office

FSUTMS requires future land use forecasts as input data to predict future travel demand and transportation needs. Given that the performance of the FSUTMS models relies heavily on the accuracy of land use forecast, there is a strong desire by planners to improve model input, especially for future forecast years. The purpose of this study is to survey the state-of-the-art and the state-of-the-practice, as well as to investigate the potential of UrbanSim as a land use model for Florida Applications. UrbanSim is a promising model for its spatial disaggregation (use of parcels to model land development), temporal disaggregation (one-year time steps), dynamics (disequilibrium model); detailed disaggregations of households and firms, and support to activity-based travel models. In this project, UrbanSim is applied to Volusia County, Florida, based on five scenarios of growth and transportation improvements. The model was validated by comparing the simulation results to the socioeconomic and demographic data adopted in the 2020 LRTP and the 2005 InfoUSA employment data. This report describes the implementation process of the land use simulation, including data collection and processing, model estimation and validation, and scenario building and testing. The most significant efforts in this project are related to data imputation and quality control, and model parameter estimation. The UrbanSim model produced reasonable results in a reasonable amount of time. It will be important to develop tools to support data imputation and processing. The modeling results also suggest that the existing consensus building processes adopted by many local governments may need improvements to allow community visions to be better reflected through the model.