Spatial Simulation

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.
Furthermore, simulation models designed to represent specific
systems and phenomena are often complicated, and, as a result,
difficult to reconstruct from their descriptions in the
literature. This book aims to provide a practical and
accessible account of dynamic spatial modelling, while also
equipping readers with a sound conceptual foundation in the
subject, and a useful introduction to the wide-ranging
literature.

Spatial Simulation: Exploring Pattern and Process is
organised around the idea that a small number of spatial processes
underlie the wide variety of dynamic spatial models. Its central
focus on three 'building-blocks' of dynamic spatial
models - forces of attraction and segregation, individual
mobile entities, and processes of spread - guides the reader
to an understanding of the basis of many of the complicated models
found in the research literature. The three building block models
are presented in their simplest form and are progressively
elaborated and related to real world process that can be
represented using them. Introductory chapters cover essential
background topics, particularly the relationships between pattern,
process and spatiotemporal scale. Additional chapters
consider how time and space can be represented in more complicated
models, and methods for the analysis and evaluation of models.
Finally, the three building block models are woven together in a
more elaborate example to show how a complicated model can be
assembled from relatively simple components.

To aid understanding, more than 50 specific models described in
the book are available online at patternandprocess.org for
exploration in the freely available Netlogo platform. This
book encourages readers to develop intuition for the abstract types
of model that are likely to be appropriate for application in any
specific context. Spatial Simulation: Exploring Pattern
and Process will be of interest to undergraduate and graduate
students taking courses in environmental, social, ecological and
geographical disciplines. Researchers and professionals who
require a non-specialist introduction will also find this book an
invaluable guide to dynamic spatial simulation.

Autorentext

DAVID O'SULLIVAN, PhD, is Assistant Professor of Geography at The Pennsylvania State University in University Park, Pennsylvania.

George L.W. Perry, University of Auckland, New Zealand.

Zusammenfassung

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. Furthermore, simulation models designed to represent specific systems and phenomena are often complicated, and, as a result, difficult to reconstruct from their descriptions in the literature. This book aims to provide a practical and accessible account of dynamic spatial modelling, while also equipping readers with a sound conceptual foundation in the subject, and a useful introduction to the wide-ranging literature.

Spatial Simulation: Exploring Pattern and Process is organised around the idea that a small number of spatial processes underlie the wide variety of dynamic spatial models. Its central focus on three 'building-blocks' of dynamic spatial models forces of attraction and segregation, individual mobile entities, and processes of spread guides the reader to an understanding of the basis of many of the complicated models found in the research literature. The three building block models are presented in their simplest form and are progressively elaborated and related to real world process that can be represented using them. Introductory chapters cover essential background topics, particularly the relationships between pattern, process and spatiotemporal scale. Additional chapters consider how time and space can be represented in more complicated models, and methods for the analysis and evaluation of models. Finally, the three building block models are woven together in a more elaborate example to show how a complicated model can be assembled from relatively simple components.

To aid understanding, more than 50 specific models described in the book are available online at patternandprocess.org for exploration in the freely available Netlogo platform. This book encourages readers to develop intuition for the abstract types of model that are likely to be appropriate for application in any specific context. Spatial Simulation: Exploring Pattern and Process will be of interest to undergraduate and graduate students taking courses in environmental, social, ecological and geographical disciplines. Researchers and professionals who require a non-specialist introduction will also find this book an invaluable guide to dynamic spatial simulation.

Inhalt

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 rel…