Spatial bias in LUTI models

Land use and transport interactions (LUTI) models are widely employed by planners, to forecast future urban patterns and to test the influence of land use or transport policies. This thesis examines their sensitivity to two types of spatial bias, the choice of the study area ("spatial extent") and of the areal units (“spatial... Read More

Land use and transport interactions (LUTI) models are widely employed by planners, to forecast future urban patterns and to test the influence of land use or transport policies. This thesis examines their sensitivity to two types of spatial bias, the choice of the study area ("spatial extent") and of the areal units (“spatial resolution”).
The first part of this thesis focuses on econometric components inside LUTI models. We propose two extensions to the literature on the Modifiable Areal Unit Problem (MAUP). First, the sensitivity of regression models to spatial extent is examined. Secondly, the influence of the spatial resolution on discrete choice models, used by most state-of-the-art LUTI models to forecast location choices of agents, is assessed. Significant variations are found in parameter estimates, leading to changes in the
behaviour of the model.
The second part of the thesis assesses the influence of these spatial biases on LUTI models' outputs. Two applications of the UrbanSim model are developed. We rely on a synthetic case study to examine the sensitivity of the final situation predicted by the model. Then, a model of the urban region of Brussels is used to explore the implications of this sensitivity for policy evaluation. The results show that variations induced by spatial bias on LUTI models’ outputs are larger than those due to transport
or land use scenarios, and that they affect the estimation of the sustainability of these scenarios.
The last chapter offers recommendations to reduce the sensitivity of LUTI models to these spatial biases, consisting in the adoption of “best spatial practices” and of potential technical development, together with alternative approach of increasing the applicability of LUTI models

Paperback - In English 31.06 €

InfoFor more information on VAT and other payment methods, see "Payment & VAT".


Presses universitaires de Louvain
Jonathan Jones,
Thèses de la Faculté des sciences
Supporting Website
Publisher’s website for a specified work
BISAC Subject Heading
ARC010000 ARCHITECTURE / Urban & Land Use Planning
Onix Audience Codes
06 Professional and scholarly
CLIL (Version 2013-2019)
3076 Architecture/Urbanisme
Title First Published
12 October 2016


Publication Date
12 October 2016
Main content page count : 296
Legal Copyright Date
423 Louvain-la-Neuve, Belgium
16 x 24 cm
475 grams
List Price
31.06 €
Version 2.1, Version 3

Google Book Preview

Write a commentary


I Introduction and state-of-the-art 1

1 General introduction 3

1.1 Research focus and motivations 3

1.2 Terminology 5

1.3 Methodological choices and outline of the thesis 7

2 Space in Land Use and Transport Interactions models 13

2.1 Introduction 13

2.2 An history of space within LUTI models 14

2.3 Representation of space within LUTI models 24

2.4 Spatial extent and resolution: a meta-analysis 29

2.5 Spatial bias and LUTI models 38

II Sensitivity of LUTI models' econometric components 45

3 Boundary effect on land price determinants 47

3.1 Introduction 47

3.2 The case study 48

3.3 Methodology 58

3.4 Results 59

3.5 Discussion 63

3.6 Summary and implications for LUTI models 65

4 Scale effect in a MNL model of employment’ location choices 67

4.1 Introduction 67

4.2 Case study 68

4.3 Econometric estimations and sensitivity analyses 72

4.4 Results 78

4.5 Discussion 83


4.6 Summary and implications for LUTI models 87

IIISensitivity of LUTI models’ outputs 91

5 Experiments on a synthetic case study 93

5.1 Introduction 93

5.2 The UrbanSim model 94

5.3 A simple, small-scale, synthetic city for UrbanSim 99

5.4 Mono centric configuration 104

5.5 Polycentric case study 120

5.6 Implications for real-world applications 130

6 The Brussels case study: lessons for policy evaluations 133

6.1 Introduction 133

6.2 Policy evaluation in LUTI models 134

6.3 Data and methodology 135

6.4 Results 144

6.5 Discussion 149

6.6 Conclusion 154

IVRecommendations and conclusion 155

7 Recommendations and conclusion 157

7.1 Executive summary 157

7.2 Best spatial practices in LUTI models 161

7.3 Toward an optimal spatial model 165

7.4 Another approach? 168

7.5 Concluding words 174

V Appendices 177

A Appendices of Chapter 2 179

A.1 The Lowrymodel 179

A.2 MEPLAN 180

A.3 IRPUD 180

A.4 TRANUS 182

A.5 DELTA 184

A.6 MUSSA 184

A.7 PECAS 185



A.8 Additional tables and figures 188

B Appendices of Chapter 3 195

B.1 Additional tables and figures 195

C Appendices of Chapter 4 203

C.1 Additional tables and Figures 203

D Appendices of Chapter 5 211

D.1 Database of a zone-version of UrbanSim 212

D.2 Sub models of a zone-version of UrbanSim 217

D.3 Additional tables and figures 224

E Appendices of Chapter 6 231

E.1 Additional tables and figures 231

F Appendices of Chapter 7 241

F.1 Additional tables and figures 241

Bibliography 245

List of Tables 277

List of Figures 279

Contents 281