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Spatial simulation : exploring pattern and process /

A ground-up approach to explaining dynamic spatial modelling for an interdisciplinary audience. Across broad areas of the environmental and social sciences, simulation models are an important way to study systems inaccessible to scientific experimental and observational methods, and also an essentia...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: O'Sullivan, David, 1966-
Otros Autores: Perry, George L. W.
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Chichester, West Sussex, U.K. : John Wiley & Sons Inc., 2013.
Temas:
Acceso en línea:Texto completo

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037 |n Title subscribed to via ProQuest Academic Complete 
050 4 |a QA402  |b .O797 2013eb 
082 0 4 |a 003  |2 23 
049 |a UAMI 
100 1 |a O'Sullivan, David,  |d 1966-  |1 https://id.oclc.org/worldcat/entity/E39PCjxXBw74pJVMXykQd6CWWC 
245 1 0 |a Spatial simulation :  |b exploring pattern and process /  |c David O'Sullivan and George L.W. Perry. 
260 |a Chichester, West Sussex, U.K. :  |b John Wiley & Sons Inc.,  |c 2013. 
300 |a 1 online resource (xxiv, 305 pages, 8 unnumbered pages of plates) :  |b illustrations (some color) 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a data file 
504 |a Includes bibliographical references and index. 
505 0 |a Cover; Title Page; Copyright; Contents; Foreword; Preface; Acknowledgements; Introduction; About the Companion Website; 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 `tools to think with'; 1.3 Why do we use simulation models?; 1.3.1 When experimental science is difficult (or impossible) 
505 8 |a 1.3.2 Complexity and nonlinear dynamics1.4 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 
505 8 |a 2.2.3 Using null models to evaluate patterns2.2.4 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 
505 8 |a 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 
505 8 |a 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 L ́evy 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 
520 |a A ground-up approach to explaining dynamic spatial modelling for an interdisciplinary audience. Across broad areas of the environmental and social sciences, simulation models are an important way to study systems inaccessible to scientific experimental and observational methods, and also an essential complement to those more conventional approaches. The contemporary research literature is teeming with abstract simulation models whose presentation is mathematically demanding and requires a high level of knowledge of quantitative and computational methods and approaches. Furth. 
590 |a ProQuest Ebook Central  |b Ebook Central Academic Complete 
650 0 |a Spatial data infrastructures  |x Mathematical models. 
650 0 |a Spatial analysis (Statistics) 
650 6 |a Infrastructures de données géospatiales  |x Modèles mathématiques. 
650 6 |a Analyse spatiale (Statistique) 
650 7 |a spatial analysis.  |2 aat 
650 7 |a Spatial analysis (Statistics)  |2 fast 
700 1 |a Perry, George L. W. 
758 |i has work:  |a Spatial simulation (Text)  |1 https://id.oclc.org/worldcat/entity/E39PCG3VHQtxMPjhHXJbG983cP  |4 https://id.oclc.org/worldcat/ontology/hasWork 
776 0 8 |i Print version:  |a O'Sullivan, David, 1966-  |t Spatial simulation.  |d Chichester, West Sussex, U.K. : John Wiley & Sons Inc., 2013  |w (DLC) 2012043887 
856 4 0 |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=1434092  |z Texto completo 
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