Fundamentals of Spatial Analysis and Modelling

Cover
Half Title
Title Page
Copyright Page
Dedication
Table of Contents
Preface
Author Biography
Acknowledgements
Chapter 1 Introduction
	1.1 What Is Spatial Analysis?
		1.1.1 Definition
		1.1.2 Spatial Statistics
		1.1.3 Geocomputation
		1.1.4 Geostatistics
	1.2 What Is So Special about Spatial Analysis?
		1.2.1 A Historic Event
		1.2.2 Value of the Spatial Perspective
		1.2.3 Ubiquitous Applications
		1.2.4 Ability to Predict and Explore Alternatives
	1.3 A Brief History
		1.3.1 Pre-digital and Early Digital Era
		1.3.2 Desktop Era
		1.3.3 GPS and GIS Era
		1.3.4 Big Data Era
	1.4 Relationship with Other Pertinent Disciplines
		1.4.1 GIS
		1.4.2 Remote Sensing
		1.4.3 GPS
		1.4.4 Computer Science
		1.4.5 Statistics
	1.5 Targets of Analysis
		1.5.1 Spatial Relationship
		1.5.2 Spatial Pattern and Structure
		1.5.3 Spatial Process
	1.6 Types of Spatial Analysis
		1.6.1 Descriptive Spatial Analysis
		1.6.2 Explanatory/Inferential Spatial Analysis
		1.6.3 Predictive Spatial Analysis
	1.7 Systems for Spatial Analysis
		1.7.1 ArcGIS Pro
		1.7.2 ERDAS Imagine
		1.7.3 RStudio
		1.7.4 MATLAB®
		1.7.5 NetLogo
	Review Questions
	References
Chapter 2 Space in Spatial Analysis
	2.1 Spatial Reference Systems
		2.1.1 Geoid and Datum
		2.1.2 Global Spherical System
		2.1.3 Global Plane System
		2.1.4 Conversion between 3D and 2D Coordinates
	2.2 Properties of Spatial Entities
		2.2.1 Components of Spatial Entities
		2.2.2 Object View of Spatial Entities
		2.2.3 Field View of Spatial Entities
		2.2.4 Dimension of Spatial Entities
		2.2.5 Spatial Adjacency and Connectivity
	2.3 Quantitative Measures of Space
		2.3.1 Distance
		2.3.2 Proximity
		2.3.3 Neighbourhood
		2.3.4 Dispersion and Clustering
		2.3.5 Direction
		2.3.6 Area
	2.4 Spatial Partitioning and Aggregation
		2.4.1 Spatial Partitioning
		2.4.2 Spatial Aggregation and the Modifiable Area Unit Problem
	2.5 Spatial Tessellation
		2.5.1 Regular Tessellations
		2.5.2 Irregular Tessellations
		2.5.3 Delaunay Triangulation
		2.5.4 Thiessen (Voronoi) Polygons
	2.6 Rudimentary Spatial Measures
		2.6.1 Mean
		2.6.2 Variance and Standard Deviation
		2.6.3 Correlation
		2.6.4 RMSE
	Review Questions
	References
Chapter 3 Spatial Data and Association
	3.1 Data and Their Sources
		3.1.1 Spatial Data
		3.1.2 Thematic Data
		3.1.3 Enumeration Scales of Thematic Data
	3.2 Spatial Sampling
		3.2.1 Sampling Considerations
		3.2.2 Strategies of Spatial Sampling
		3.2.3 Sampling Dimensionality
		3.2.4 Sample Size and Spacing
	3.3 Spatial Association and Pattern
		3.3.1 Spatial Continuity versus Spatial Pattern
		3.3.2 Scatterplot and H-scatterplot
		3.3.3 Correlogram
		3.3.4 Spatial Auto-correlation
		3.3.5 Cross-correlation
		3.3.6 Scale in Spatial Analysis
	3.4 Spatial Auto-correlation
		3.4.1 Geary’s Ratio
		3.4.2 Moranʹs I
		3.4.3 An example
		3.4.4 Local-scale Spatial Association
		3.4.5 Global Bivariate Spatial Auto-correlation
	3.5 Area Pattern and Joint Count Statistic
		3.5.1 Area Patterns and Joint Counts
		3.5.2 Joint Count Test
	Review Questions
	References
Chapter 4 Descriptive and Inferential Spatial Analysis
	4.1 Analysis of Point Data
		4.1.1 Point Data
		4.1.2 Fundamental Types of Point Patterns
		4.1.3 Poisson Process behind Random Patterns
		4.1.4 Formation of Clustered Patterns
		4.1.5 Measures of Point Dispersion
		4.1.6 Nearest Neighbour Analysis
		4.1.7 Hotspot Analysis
		4.1.8 Inferential Analysis of Point Patterns
		4.1.9 Kernel Density Analysis
		4.1.10 Second-order Analysis of Point Patterns
	4.2 Fractals and Spatial Analysis
		4.2.1 Line/Surface Complexity
		4.2.2 Fundamentals of Fractal Geometry
		4.2.3 Fractal Dimension and Its Determination
	4.3 Shape Analysis of Polygons
		4.3.1 Desirable Qualities of Shape Measures
		4.3.2 Outline-based Shape Analysis
		4.3.3 Compactness-based Measures
		4.3.4 Comparison to a Standard Shape
		4.3.5 Practical Applications
	4.4 Analysis of Areal Data and FRAGSTATS
		4.4.1 Objects of Study
		4.4.2 Representative Metrics
		4.4.3 FRAGSTATS
		4.4.4 Application in Quantifying Urban Sprawl
	4.5 Analysis of Directions
		4.5.1 Reference Systems of Directions
		4.5.2 Descriptive Measures
		4.5.3 Schematic Representation
	Review Questions
	References
Chapter 5 Geostatistics and Spatial Interpolation
	5.1 Introduction
		5.1.1 Spatial Interpolation and Geostatistics
		5.1.2 Regionalised Variables
		5.1.3 Variogram and Semi-variogram
		5.1.4 Structure of Semi-variogram
		5.1.5 Semi-variogram Models
	5.2 Trend Surface Interpolation
	5.3 Moving Averaging
	5.4 Minimum Curvature
	5.5 Kriging
		5.5.1 Ordinary (Punctual) Kriging
		5.5.2 A Comparative Evaluation
		5.5.3 Simple Kriging
		5.5.4 Universal Kriging
		5.5.5 Block Kriging and Co-kriging
	Review Questions
	References
Chapter 6 Spatial Modelling
	6.1 Fundamentals of Modelling
		6.1.1 Models and Types
		6.1.2 Static versus Dynamic Models
		6.1.3 Spatial Modelling
		6.1.4 Spatial Analysis or Spatial Modelling?
	6.2 Nature of Spatial Modelling
		6.2.1 Variables in Spatial Modelling
		6.2.2 Types of Spatial Modelling
		6.2.3 Cartographic Modelling
		6.2.4 Spatial Dynamic Modelling
	6.3 Model Development and Accuracy
		6.3.1 Feature Selection
		6.3.2 Multi-collinearity Test
		6.3.3 Model Validation
		6.3.4 Measures of Modelling Accuracy
	6.4 Issues in Spatial Modelling
		6.4.1 Assignment of Weights
			6.4.1.1 AHP
			6.4.1.2 Regression Analysis
			6.4.1.3 Weight of Evidence Model
			6.4.1.4 Delphi Technique
		6.4.2 Spatial Modelling and Data Structure
		6.4.3 Platforms for Spatial Modelling
			6.4.3.1 ArcGIS ModelBuilder
			6.4.3.2 Raster Calculator
			6.4.3.3 IDRISI TerrSet
			6.4.3.4 Scripting
	6.5 Spatial Modelling in GIS Packages
		6.5.1 Spatial modelling and GIS Packages
		6.5.2 Pros and Cons of GIS Modelling
		6.5.3 Coupling of Spatial Models with GIS Software
			6.5.3.1 Loose Coupling
			6.5.3.2 Tight Coupling
			6.5.3.3 Total Coupling
	6.6 Special Types of Modelling
		6.6.1 (Spatial) Logistic Regression
		6.6.2 Land Use Regression Modelling
		6.6.3 Hydrological Modelling
	6.7 Three Cases of Spatial Modelling
		6.7.1 Earthquake Damage Modelling
		6.7.2 Landslide Susceptibility Modelling
		6.7.3 Glacier Extent Modelling
	Review Questions
	References
Chapter 7 Spatial Simulation
	7.1 Introduction
		7.1.1 Spatial Simulation
		7.1.2 Spatiotemporal Dynamic Simulation
		7.1.3 Spatially Explicit Simulation Models
		7.1.4 Spatial Simulation and Machine Learning
	7.2 Cellular Automata Simulation
		7.2.1 Automata
		7.2.2 Environment
		7.2.3 Rules
		7.2.4 CA and Spatial Simulation
		7.2.5 Two Examples of CA Models
		7.2.6 Integration with Other Models
	7.3 Agent-based Simulation
		7.3.1 Agents and Geographic Agents
		7.3.2 Agent-based Modelling
		7.3.3 Rules
		7.3.4 CA or ABM?
		7.3.5 Designing and Developing ABMs
		7.3.6 Toolkits for Implementing ABM
	7.4 NetLogo for Dynamic Simulation
		7.4.1 General Features
		7.4.2 Anatomy of a NetLogo Model
		7.4.3 Sensitivity Analysis
		7.4.4 NetLogo versus Spatiotemporal Simulations
	7.5 Special Cases of Spatial Simulation
		7.5.1 Wildfire Simulation
			7.5.1.1 Wildfire Models
			7.5.1.2 Raster or Vector Simulation Models
			7.5.1.3 Common Wildfire Simulation Models
		7.5.2 Urban Expansion Simulation
			7.5.2.1 Modes of Urban Expansion
			7.5.2.2 Players in Urban Expansion
			7.5.2.3 Simulation Models of Urban Expansion
			7.5.2.4 A Case Study
		7.5.3 Simulation of Grassland Degradation
	Review Questions
	References
Chapter 8 Time-explicit Spatial Analysis and Modelling
	8.1 Time
		8.1.1 Nature of Time in Geography
		8.1.2 Space, Time, and Attribute
		8.1.3 Temporal Aggregation versus Discretisation
	8.2 Models of Spatiotemporal Representation
		8.2.1 Time-location Path Model
		8.2.2 Gazetteer Method of Representation
		8.2.3 Snapshot Model
		8.2.4 Space-time Composites Model
		8.2.5 Spatiotemporal Object Model
		8.2.6 Event-based Spatiotemporal Model
		8.2.7 Organisation and Storage of Spatiotemporal Data
	8.3 Spatiotemporal Data Analysis
		8.3.1 Time-explicit versus Time-implicit Analysis
		8.3.2 Spatiotemporal Association
		8.3.3 Time Slicing Overlay Analysis
	8.4 Time-explicit Spatiotemporal Modelling
		8.4.1 Extended Semi-variogram Model
		8.4.2 Diffusion Models
		8.4.3 State and Transition Model
		8.4.4 Modified SIR Model
		8.4.5 Packages for Spatiotemporal Analysis and Modelling
	8.5 Visualisation of Spatiotemporal Data and Processes
		8.5.1 Simple Map Display
		8.5.2 Animation
		8.5.3 Simulation
	Review Questions
	References
Index