Spatial simulation : exploring pattern and process /

• Κύριος συγγραφέας: O'Sullivan, David, 1966-
• Άλλοι συγγραφείς: Perry, George L. W.
• Μορφή: Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Chichester, West Sussex, UK : Wiley-Blackwell, 2013.
• Θέματα: Spatial data infrastructures > Mathematical models.; Spatial analysis (Statistics); SCIENCE > System Theory.; TECHNOLOGY & ENGINEERING > Operations Research.; Electronic books.

Πίνακας περιεχομένων:

• Chapter 1 Spatial Simulation Models: What? Why? How?; 1.1 What are simulation models?; 1.1.1 Conceptual models; 1.1.2 Physical models; 1.1.3 Mathematical models; 1.1.4 Empirical models; 1.1.5 Simulation models; 1.2 How do we use simulation models?; 1.2.1 Using models for prediction; 1.2.2 Models as guides to data collection; 1.2.3 Models as t̀ools to think with'; 1.3 Why do we use simulation models?; 1.3.1 When experimental science is difficult (or impossible).
• 1.3.2 Complexity and nonlinear dynamics 1.4 Why dynamic and spatial models?; 1.4.1 The strengths and weaknesses of highly general models; 1.4.2 From abstract to more realistic models: controlling the cost; Chapter 2 Pattern, Process and Scale; 2.1 Thinking about spatiotemporal patterns and processes; 2.1.1 What is a pattern?; 2.1.2 What is a process?; 2.1.3 Scale; 2.2 Using models to explore spatial patterns and processes; 2.2.1 Reciprocal links between pattern and process: a spatial model of forest structure; 2.2.2 Characterising patterns: first- and second-order structure.
• 2.2.3 Using null models to evaluate patterns 2.2.4.2.4 Density-based (first-order) null models; 2.2.5 Interaction-based (second-order) null models; 2.2.6 Inferring process from (spatio-temporal) pattern; 2.2.7 Making the virtual forest more realistic; 2.3 Conclusions; Chapter 3 Aggregation and Segregation; 3.1 Background and motivating examples; 3.1.1 Basics of (discrete spatial) model structure; 3.2 Local averaging; 3.2.1 Local averaging with noise; 3.3 Totalistic automata; 3.3.1 Majority rules; 3.3.2 Twisted majority annealing; 3.3.3 Life-like rules.
• 3.4 A more general framework: interacting particle systems3.4.1 The contact process; 3.4.2 Multiple contact processes; 3.4.3 Cyclic relationships between states: rock-scissors-paper; 3.4.4 Voter models; 3.4.5 Voter models with noise mutation; 3.5 Schelling models; 3.6 Spatial partitioning; 3.6.1 Iterative subdivision; 3.6.2 Voronoi tessellations; 3.7 Applying these ideas: more complicated models; 3.7.1 Pattern formation on animals' coats: reaction-diffusion models; 3.7.2 More complicated processes: spatial evolutionary game theory; 3.7.3 More realistic models: cellular urban models.
• Chapter 4 Random Walks and Mobile Entities4.1 Background and motivating examples; 4.2 The random walk; 4.2.1 Simple random walks; 4.2.2 Random walks with variable step lengths; 4.2.3 Correlated walks; 4.2.4 Bias and drift in random walks; 4.2.5 Ĺevy flights: walks with non-finite step length variance; 4.3 Walking for a reason: foraging and search; 4.3.1 Using clues: localised search; 4.3.2 The effect of the distribution of resources; 4.3.3 Foraging and random walks revisited; 4.4 Moving entities and landscape interaction; 4.5 Flocking: entity-entity interaction; 4.6 Applying the framework.