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<p>INTRODUCTION ix</p> <p><b>CHAPTER 1. BUILDING OBJECTS IN TIME 1</b></p> <p>1.1. Different points of view on ontology 4</p> <p>1.1.1. Defining ontology 4</p> <p>1.1.2. Qualification of the objects from an ontological perspective: “bona fide” versus “fiat” objects 8</p> <p>1.1.3. Specification of ontologies in the field of spatial analysis and geographical sciences: objects versus fields 10</p> <p>1.1.4. An example of empirical objects’ construction: the case of cities 13</p> <p>1.2. Locating spatial objects in time 16</p> <p>1.2.1. Objects’ formalization in time: “endurant” and “perdurant” entities of philosophers 17</p> <p>1.2.2. From change to objects’ life 21</p> <p>1.3. Conclusion 28</p> <p><b>CHAPTER 2. FROM EMPIRICAL QUESTIONING TO SPATIO-TEMPORAL MODELING 29</b></p> <p>2.1. From the conception of entities to their analysis of responding to thematic issues 30</p> <p>2.1.1. Building the spatio-temporal objects from the empirical observations (challenge 1) 32</p> <p>2.1.2. Representing and exploring change and movement (challenge 2) 35</p> <p>2.1.3. Analyzing the evolution of statistical and spatial relationships (challenge 3) 38</p> <p>2.1.4. Identifying the underlying processes of change: simulation and scenario testing (challenge 4)          41</p> <p>2.2. Challenges and models: the possible misunderstandings 44</p> <p>2.3. Application examples 46</p> <p>2.3.1. Cities’ dynamics: construction and follow-up of composite objects in time 47</p> <p>2.3.2. Distribution of urban functions in the intra-urban space: construction of spatio-temporal<br /> functional objects 53</p> <p>2.3.3. Evaluating the impact of mobile objects on a spatial support 56</p> <p>2.3.4. What factors are behind the emergence and/or the reinforcement of school segregation? Construction of multilevel and multidate information 60</p> <p>2.4. Conclusion 64</p> <p><b>CHAPTER 3. ANALYZING SPATIO-TEMPORAL DATA: EMPIRICAL AND STATISTICAL APPROACHES 65</b></p> <p>3.1. Statistical data and spatio-temporal analysis 66</p> <p>3.1.1. Spatial analysis evolution in a context influenced by statistics and computer science 66</p> <p>3.1.2. Different ways to take time and space into account to analyze spatio-temporal processes 70</p> <p>3.1.3. From entities’ dynamics to that of organizations: what is it that changes and relative to what frame of reference? 73</p> <p>3.2. Following the evolution of the structure of spatial systems 76</p> <p>3.2.1. Describing the evolution of space and hierarchical organizations 76</p> <p>3.2.2. Change, temporalities and statistical explanations 82</p> <p>3.3. Understanding the evolution of a spatial system’s entities 86</p> <p>3.3.1. Constructing, describing and categorizing trajectories of evolution 87</p> <p>3.3.2. Identifying a priori defined types of change to classify evolutions 91</p> <p>3.3.3. “Unfolded” time and forecast 93</p> <p>3.4. Conclusion 97</p> <p><b>Chapter 4. Exploring the Underlying Processes of Change: Simulation Models 99</b></p> <p>4.1. Computer simulation versus statistical approach: different points of view about explanation 99</p> <p>4.1.1. From covariation to interaction, from differentiation to emergence 102</p> <p>4.1.2. Different types of explanation: from the percentage of variance explained to the generation of mechanisms 104</p> <p>4.1.3. Different points of view on multilevel phenomena 105</p> <p>4.2. Microsimulation models107</p> <p>4.3. Computing models: simulation and emergence 112</p> <p>4.3.1. Modeling the diffusion of a migratory wave front 113</p> <p>4.3.2. Cellular automata approaches: the case of land use changes 115</p> <p>4.3.3. Agent-based models applied to simple entities 120</p> <p>4.3.4. Agent modeling on composite entities 124</p> <p>4.4. Conclusion 129</p> <p>CONCLUSION 133</p> <p>BIBLIOGRAPHY 139</p> <p>INDEX 155</p>

<p><strong>Hélène Mathian</strong> is a research engineer at CNRS in Lyon, France. Her main research interests include spatial analysis, particularly concepts and methods for studying change and movement in space. <p><strong>Lena Sanders</strong> is a senior researcher at CNRS in Paris, France. Her main research interests include modeling spatial systems' dynamics and studying conceptual transfers between disciplines.

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