Table of Contents 1 Vocabulary. 4 1.1 Geoprocessing Terms 4 1.2 Network Terms. 4 2 Course Breakdown 5 2.1 Assessments. 5 2.1.1 GIS Project Steps. 5 3 Geoprocessing with ModelBuilder. 6 3.1 Model Elements 6 3.2 Model States 7 3.3 Model Parameters. 7 3.4 Environmental Settings. .8 3.5 Model Saving. 9 3.6 Advanced Techniques. 9 4 Analytical Methodologies 10 5 Spatial Analysis as a Process. 13 6 Spatial Analysis and the PPDAC Model 13 6.1 Problem: Framing the question 14 6.2 Plan: Formulating the approach 15 6.3 Data: Data acquisition. 16 6.4 Analysis: Analytical methods and tools. 17 6.5 Conclusions: delivering the results 18 7 Geospatial Analysis and Model Building 18 8 Week 1 Readings. 19 9 Network Analysis. 20 9.1 Problems that can be solved using Network Analysis 20 9.1.1 Example Questions. 20 9.2 Undirected Networks 20 9.3 Directed Networks 20 9.4 Building up a Network 20 9.4.1 Network Data Models 21 9.5 Network Applications. 21 9.5.1 Optimal Routings. 21 9.5.2 Finding the closest facilities 21
9.5.3 Resource Allocation. 21 9.6 Network Analysis Workflow in ArcGIS 22 9.6.1 ArcGIS Pro Network Analyst. 22 9.6.2 Building a Network Dataset in ArcCatalog 22 9.6.3 Conducting Network Analyst in ArcGIS Pro. 22 10 Impedance. 22 10.1 Turn Impedance. 22 10.2 Link Impedance. 22 10.3 Modelling Impedance 23 10.3.1 Example Exam Questions 23 11 OD Cost Matrix 23 12 Spatial Accessibility Modelling. 24 13 Topology 24 13.1 Topological Data Models 24 13.2 Elements to Topology 24 13.2.1 Adjacency, Containment and Connectivity. 24 14 Week 2 Readings. 25 15 Spatial Accessibility Modelling. 25 15.1 Methods 25 15.2 Data Required. 29 15.2.1 Measuring Distance/ Travel Time 29 15.2.2 Application. 29 15.3 2SFCA Method and its limitations. 30 15.3.1 Modified 2SFCA Method. 30 15.3.2 Results 30 15.4 Measuring access to urban green space 32 15.4.1 Ipswich Case Study. 33 16 Describing Spatial Distributions. 33 16.1 Spatial Statistics. 33 16.1.1 Methods for Characterising Geographic Distribution. 33 16.1.2 Describing Geographical Distribution. 34 16.2 Describing Spatial Distribution. 34 16.2.1 Measure Central Tendency. 34 16.3 Measure Spatial (Variation) Spread. 37 16.3.1 Standard Distance. 37 16.3.2 Non-Symmetrical Distributions. 38 16.4 Non-parametric Estimators of Distribution 39 16.4.1 Probability of Normal Distribution. 39 16.5 Non-parametric Statistics. 40 16.5.1 Kernel Density Estimation (KDE) / Kernel Approximation. 40 16.6 Parametric vs non-Parametric 42 17 Analysing Geographic Patterns 43 17.1 Spatial Patterns vs Processes 43
17.2 Feature Locations Vs Feature Values. 43 17.3 Spatial Pattern Analysis 44 17.4 Hypothesis Tests for Spatial Analysis 17.4.1 HO (Null Hypothesis). 44 17.4.2 H1 (Alternative Hypothesis) 44 17.4.3 Methods used to identify patterns in Feature Locations and Feature Values 44 45 17.4.4 Quadrant Analysis. 45 18 Spatial Autocorrelation (Global/ Local Statistics and Hot Spot Analysis). 48 18.1 Spatial Patterns of feature locations/ values. 49 18.2 Methods used to identify patterns in Feature Locations and Feature Values 49 18.3 Global VS Local Measures of Patterns. 49 18.4 Global Statistics I (Global Moran's I) 49 18.4.1 Computing Global Moran's I. 50 18.4.2 Advantages and Limitations. 51 18.5 Global Statistics II: Getis-Ord General