Geographical Modeling Cities and Territories

Introduction ix
Denise PUMAIN

Chapter 1. Complexity in Geography 1
Denise PUMAIN

1.1. A first bifurcation in the epistemology of geographic modeling 3

1.1.1. “Vertical” explanations for the “science of places, not people” 4

1.1.2. “Horizontal” explanations for the science of the spatiality of societies 5

1.1.3. The discussed status of modeling 7

1.2. Modeled regularities 10

1.2.1. Proximity and distances 11

1.2.2. The scale 15

1.2.3. Concentration and accumulation: geographical inequalities and scaling laws 19

1.2.4. Spatial change and trajectory dependence 21

1.2.5. Territorial drifts, space-time compression, and globalization 25

1.3. Conclusion 29

Chapter 2. Choosing Models to Explain the Dynamics of Cities and Territories 31
Lena SANDERS

2.1. Introduction 31

2.2. Explaining by reasons or laws: choosing an epistemological framework 32

2.3. The modeling approach: diversity of models 36

2.4. Explaining through statistical relationships or mechanisms 38

2.5. Choosing the level of abstraction for the phenomenon to be explained: general versus particular 41

2.6. Choosing the level of abstraction for the model: stylized or realistic, KISS or KIDS 44

2.6.1. Modes of representation of space: from a stylized space to a realistic space 45

2.6.2. Formalizing spatial mechanisms: from stylized to realistic 48

2.7. Conclusion 50

Chapter 3. Effects of Distance and Scale Dependence in Geographical Models of Cities and Territories 53
Cécile TANNIER

3.1. Three fundamental principles for modeling cities and territories 55

3.1.1. Effects of distance 57

3.1.2. Effects of scale dependence 58

3.2. Role of distance in spatial simulation models 61

3.3. Modeling scale dependence 76

3.3.1. Scale dependence as a result of processes acting at different scales 77

3.3.2. Scale invariance for the description of geographical phenomena 83

3.3.3. Scale dependence as a generative mechanism for simulated spatial configurations 88

3.4. Conclusion 93

Chapter 4. Incremental Territorial Modeling 95
Clémentine COTTINEAU, Paul CHAPRON, Marion LE TEXIER and Sébastien REY-COYREHOURCQ

4.1. The map and the territory 96

4.1.1. Modeling as one map: selection and schematization 96

4.1.2. The representation of territory as an input of the model 100

4.1.3. The representation of territory as an output of the model 102

4.2. Generality and specificity: explaining by ways of geographical models 106

4.2.1. Historical contingency and non-ergodicity 106

4.2.2. General/specific/singular 109

4.3. Incremental territorial modeling 110

4.3.1. Identifying the object, scale, configuration, and stylized facts 111

4.3.2. Gathering the different theoretical explanations 112

4.3.3. Hierarchizing the interaction processes between agents 113

4.3.4. Hierarchizing the interaction processes between agents and their environment 114

4.3.5. Implementing mechanisms and their formal alternatives 115

4.3.6. Combining, simulating, and comparing 116

4.4. Challenges and limits of multi-modeling 117

4.4.1. The combinatorial curse 118

4.4.2. Human and technical costs 118

4.4.3. Subjectivity in the choice of building blocks 119

4.4.4. Comparing models of different structures 119

4.4.5. Sharing and accumulation of knowledge 121

4.5. Conclusion 121

Chapter 5. Methods for Exploring Simulation Models 125
Juste RAIMBAULT and Denise PUMAIN

5.1. Social sciences and experimentation 126

5.2. Geographical data and computer skills 127

5.3. New generation simulations 130

5.3.1. A virtual laboratory: the OpenMOLE platform 131

5.3.2. The SimpopLocal experiment: simulation of an emergence in geography 134

5.3.3. Implementation of SimpopLocal, from NetLogo to OpenMOLE 137

5.3.4. Calibration and validation 139

5.4. Other examples of OpenMOLE applications: network–territory interaction models 143

5.5. Perspectives 147

5.5.1. Methods 147

5.5.2. Tools 148

5.6. Conclusion 149

Chapter 6. Model Visualization 151
Robin CURA

6.1. Introduction 151

6.2. Visualization as modeling 153

6.2.1. Visualization as a tool for interdisciplinarity 155

6.2.2. Visualization and reproducibility 160

6.2.3. Visualizing a model means learning 162

6.3. Visualize to evaluate 163

6.3.1. Visualize before modeling 164

6.3.2. Visualize during the simulation 166

6.3.3. Visualizing after the simulation 169

6.4. Visualizing to compare 172

6.4.1. Which models should be compared? 172

6.4.2. How should visual comparison be done? 174

6.5. Visualizing to communicate 178

6.5.1. Visualizing to disseminate 179

6.6. Some obstacles inherent in model visualization 182

6.6.1. Producing and visualizing massive data 183

6.6.2. Visualization of aggregated data 187

6.7. Conclusion 191

References 193

List of Authors 221

Index 223

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