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Produktbild: Simulating Pattern and Process

Simulating Pattern and Process

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

30.08.2013

Verlag

John Wiley & Sons Inc

Seitenzahl

336

Maße (L/B/H)

24,4/17/1,8 cm

Gewicht

588 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-1-119-97079-8

Beschreibung

Rezension

"The book by O'Sullivan and Perry thoroughly introduces basic theoretical work and offers not only a rich source of inspiration but also readily accessible examples from various applications that can be adopted and adapted in order to get started." (Frontiers of Biogeography, 2 June 2014)

"In summary, the book brings a comprehensiveness and structure that will aid any researcher in the development of a spatial simulation model, no matter their experience. In moving from simple "building blocks" to sophisticated extensions of fundamental processes, the book brings a new maturity to the field of spatial simulation. As Volker Grimm correctly points out in the foreword - "This book was badly needed.." (Journal of Artificial Societies and Social Simulation, 1 March 2014)

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

30.08.2013

Verlag

John Wiley & Sons Inc

Seitenzahl

336

Maße (L/B/H)

24,4/17/1,8 cm

Gewicht

588 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-1-119-97079-8

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: gpsr@libri.de

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  • Produktbild: Simulating Pattern and Process

  • Foreword xiii

    Preface xv

    Acknowledgements xix

    Introduction xxi

    About the Companion Website xxv

    1 Spatial Simulation Models: What? Why? How? 1

    1.1 What are simulation models? 2

    1.1.1 Conceptual models 4

    1.1.2 Physical models 7

    1.1.3 Mathematical models 7

    1.1.4 Empirical models 8

    1.1.5 Simulation models 9

    1.2 How do we use simulation models? 12

    1.2.1 Using models for prediction 13

    1.2.2 Models as guides to data collection 13

    1.2.3 Models as 'tools to think with' 14

    1.3 Why do we use simulation models? 15

    1.3.1 When experimental science is difficult (or impossible) 16

    1.3.2 Complexity and nonlinear dynamics 18

    1.4 Why dynamic and spatial models? 23

    1.4.1 The strengths and weaknesses of highly general models 23

    1.4.2 From abstract to more realistic models: controlling the cost 27

    2 Pattern, Process and Scale 29

    2.1 Thinking about spatiotemporal patterns and processes 30

    2.1.1 What is a pattern? 30

    2.1.2 What is a process? 31

    2.1.3 Scale 32

    2.2 Using models to explore spatial patterns and processes 38

    2.2.1 Reciprocal links between pattern and process: a spatial model of forest structure 39

    2.2.2 Characterising patterns: first- and second-order structure 40

    2.2.3 Using null models to evaluate patterns 43

    2.2.4 Density-based (first-order) null models 46

    2.2.5 Interaction-based (second-order) null models 48

    2.2.6 Inferring process from (spatio-temporal) pattern 49

    2.2.7 Making the virtual forest more realistic 53

    2.3 Conclusions 56

    3 Aggregation and Segregation 57

    3.1 Background and motivating examples 58

    3.1.1 Basics of (discrete spatial) model structure 59

    3.2 Local averaging 60

    3.2.1 Local averaging with noise 63

    3.3 Totalistic automata 64

    3.3.1 Majority rules 65

    3.3.2 Twisted majority annealing 68

    3.3.3 Life-like rules 69

    3.4 A more general framework: interacting particle systems 70

    3.4.1 The contact process 71

    3.4.2 Multiple contact processes 73

    3.4.3 Cyclic relationships between states: rock-scissors-paper 76

    3.4.4 Voter models 78

    3.4.5 Voter models with noise mutation 80

    3.5 Schelling models 83

    3.6 Spatial partitioning 86

    3.6.1 Iterative subdivision 86

    3.6.2 Voronoi tessellations 87

    3.7 Applying these ideas: more complicated models 88

    3.7.1 Pattern formation on animals' coats: reaction-diffusion models 89

    3.7.2 More complicated processes: spatial evolutionary game theory 91

    3.7.3 More realistic models: cellular urban models 93

    4 Random Walks and Mobile Entities 97

    4.1 Background and motivating examples 97

    4.2 The random walk 99

    4.2.1 Simple random walks 99

    4.2.2 Random walks with variable step lengths 102

    4.2.3 Correlated walks 103

    4.2.4 Bias and drift in random walks 108

    4.2.5 Lévy flights: walks with non-finite step length variance 109

    4.3 Walking for a reason: foraging and search 111

    4.3.1 Using clues: localised search 115

    4.3.2 The effect of the distribution of resources 116

    4.3.3 Foraging and random walks revisited 119

    4.4 Moving entities and landscape interaction 119

    4.5 Flocking: entity-entity interaction 121

    4.6 Applying the framework 125

    4.6.1 Animal foraging 126

    4.6.2 Human 'hunter-gatherers' 128

    4.6.3 The development of home ranges and path networks 129

    4.6.4 Constrained environments: pedestrians and evacuations 129

    4.6.5 Concluding remarks 131

    5 Percolation and Growth: Spread in Heterogeneous Spaces 133

    5.1 Motivating examples 133

    5.2 Percolation models 137

    5.2.1 What is percolation? 137

    5.2.2 Ordinary perc