Spatio-temporal Approaches

Hélène Mathian 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. Lena Sanders is a senior researcher at CNRS in Paris, France. Her main research interests include modeling spatial systems' dynamics and studying conceptual transfers between disciplines.

• INTRODUCTION ixCHAPTER 1. BUILDING OBJECTS IN TIME 11.1. Different points of view on ontology 41.1.1. Defining ontology 41.1.2. Qualification of the objects from an ontological perspective: “bona fide” versus “fiat” objects 81.1.3. Specification of ontologies in the field of spatial analysis and geographical sciences: objects versus fields 101.1.4. An example of empirical objects’ construction: the case of cities 131.2. Locating spatial objects in time 161.2.1. Objects’ formalization in time: “endurant” and “perdurant” entities of philosophers 171.2.2. From change to objects’ life 211.3. Conclusion 28CHAPTER 2. FROM EMPIRICAL QUESTIONING TO SPATIO-TEMPORAL MODELING 292.1. From the conception of entities to their analysis of responding to thematic issues 302.1.1. Building the spatio-temporal objects from the empirical observations (challenge 1) 322.1.2. Representing and exploring change and movement (challenge 2) 352.1.3. Analyzing the evolution of statistical and spatial relationships (challenge 3) 382.1.4. Identifying the underlying processes of change: simulation and scenario testing (challenge 4)          412.2. Challenges and models: the possible misunderstandings 442.3. Application examples 462.3.1. Cities’ dynamics: construction and follow-up of composite objects in time 472.3.2. Distribution of urban functions in the intra-urban space: construction of spatio-temporalfunctional objects 532.3.3. Evaluating the impact of mobile objects on a spatial support 562.3.4. What factors are behind the emergence and/or the reinforcement of school segregation? Construction of multilevel and multidate information 602.4. Conclusion 64CHAPTER 3. ANALYZING SPATIO-TEMPORAL DATA: EMPIRICAL AND STATISTICAL APPROACHES 653.1. Statistical data and spatio-temporal analysis 663.1.1. Spatial analysis evolution in a context influenced by statistics and computer science 663.1.2. Different ways to take time and space into account to analyze spatio-temporal processes 703.1.3. From entities’ dynamics to that of organizations: what is it that changes and relative to what frame of reference? 733.2. Following the evolution of the structure of spatial systems 763.2.1. Describing the evolution of space and hierarchical organizations 763.2.2. Change, temporalities and statistical explanations 823.3. Understanding the evolution of a spatial system’s entities 863.3.1. Constructing, describing and categorizing trajectories of evolution 873.3.2. Identifying a priori defined types of change to classify evolutions 913.3.3. “Unfolded” time and forecast 933.4. Conclusion 97Chapter 4. Exploring the Underlying Processes of Change: Simulation Models 994.1. Computer simulation versus statistical approach: different points of view about explanation 994.1.1. From covariation to interaction, from differentiation to emergence 1024.1.2. Different types of explanation: from the percentage of variance explained to the generation of mechanisms 1044.1.3. Different points of view on multilevel phenomena 1054.2. Microsimulation models1074.3. Computing models: simulation and emergence 1124.3.1. Modeling the diffusion of a migratory wave front 1134.3.2. Cellular automata approaches: the case of land use changes 1154.3.3. Agent-based models applied to simple entities 1204.3.4. Agent modeling on composite entities 1244.4. Conclusion 129CONCLUSION 133BIBLIOGRAPHY 139INDEX 155