1.2 John Snow’s map of cholera mortality and pump location in a London neighbourhood
1.3 Tree canopy distribution across neighbourhoods in Providence, Rhode Island, US
1.4 The vector versus the raster spatial data model
1.5 Vector representation of features in Providence, Rhode Island, US
1.6 The dynamic connection between vector features and their attribute table
2.1 Neighbourhood Statistics topics from the UK Office for National Statistics
2.3 The city of Sheffield, UK, electoral wards
2.5 Spatial distribution of professional and managerial occupations in Sheffield, UK, 2011
2.6 Population living more than 60 minutes from the nearest university in Europe
2.8 Distance to nearest grocery stores in Sheffield, UK, from each LSOA
2.9 Point, line and polygon features and buffers around these features
3.1 The six principal visual variables
3.2 A reference map of Golden Gate, California, US, created using ArcGIS
3.3 A reference map example: grocery stores in central London
3.4 A reference map example: charities and shelters in support of the homeless in central London
3.5 Choropleth map with nominal/ordinal data: geodemographic classifications
3.6 Choropleth map with nominal/ordinal data: social atlas of Europe rainbow
3.7 Choropleth map with nominal/ordinal data: Worldmapper regions
3.8 Choropleth map example for unemployment rate in Sheffield, UK, 2011 (natural breaks)
3.9 Choropleth map example for unemployment rate in Sheffield, UK, 2011 (quantiles)
3.10 Graduated symbol example: unemployment in Sheffield, UK
3.11 Dot density map example: population in Sheffield, UK
3.12 Pie chart map example: occupations in Sheffield, UK
3.13 Bar chart map example: occupations in Sheffield, UK
3.14 Stacked bar chart map example: occupations in Sheffield, UK
3.15 Pie chart (occupations) and choropleth map of unemployment rates in Sheffield, UK
3.16 A graduated symbol point map: groceries and floor-space in Sheffield, UK
3.17 A graduated symbol point map and choropleth map in Sheffield, UK
3.18 A line thematic map example combined with choropleth travel time mapping
3.19 Mapping flows example: British Coal exports in 1864
3.20 A map of government balance and gross debt in Europe
3.21 A circular (Dorling) cartogram example
3.22 Change 1971–2001 in percentage of households with access to two or more cars
3.23 A human cartogram map locator example
3.25 Standard versus cartogram mapping of US presidential election results, 2004
3.26 Bar chart of total population by Worldmapper region as a percentage of the global population
3.29 A gridded population cartogram of the world
3.30 A population cartogram of Europe using Gastner and Newman’s density-equalising method
3.31 Gridded population cartogram of Europe
3.33 Gridded population cartogram representation of the topography of Europe
4.1 Comparison of straight-line and network distances for identical origin and destination
4.2 A street network represented as combinations of junctions and edges
4.3 Converting streets to a street network
4.4 Impact of an areal barrier on route computation
4.6 Using network analysis to compute service areas around facilities
4.7 Finding the closest facility for a set of ‘incidents’
5.2 English Index of Multiple Deprivation, 2015
5.3 Poverty, wealth and place overview of methodology
5.4 Poverty, wealth and place in Britain
5.7 The BBC radio regions map and human cartogram
5.8 Spatial distribution of anomie index, 1971
5.9 Spatial distribution of anomie index, 2001
5.10 Spatial distribution of anomie index difference between 1971 and 2001
5.11 Dimensions of human development
5.12 The EU Human Development Index, 2007
5.14 The diversitydata.org project
5.15 The diversitydatakids.org project
5.16 Geodemographics is about ‘linking people to places’
5.17 Mosaic UK: City Prosperity ‘pen portrait’
5.18 A map showing ‘Patchwork Nation’
5.19 The Nielsen PRIZM geodemographic classification: segment details
5.20 Mapping the first UK output area classification, South and West Yorkshire, UK, 2001
5.22 Cluster radial plot for ‘Countryside’ supergroup
5.23 Distribution of high-income earners in Los Angeles, California, US, using geodemographics
5.24 Distribution of high-income earners in Sydney, Australia, using geodemographics
6.1 Geographical distribution of subjective happiness in Europe
6.2 Net adjusted disposable income of private households, 2007
6.3 Gross monthly employee earnings by occupation category in the UK, 2011
6.4 Regression in GIS as explained by ArcMap instruction manuals
6.5 Census rehearsal household income distribution
6.6 Income distribution of household representatives in different local neighbourhoods
6.7 Spatial microsimulation query results
6.10 Simulated percentage earning over £150,000, Edinburgh, UK: quintiles
6.11 Estimated geographical distribution of happiness in Wales, 2001
7.2 Crime Finder mobile phone application
7.3 The police forces in the UK and their funding
7.5 Crime rates vary spatially in Washington, DC
7.7 Activity space and crime opportunities
7.8 Plotting offender locations for crimes committed in Roundhay, Leeds, UK
7.9 Temporal variations in clusters of crime in Leeds, UK
7.10 A map of repeat victimisation for burglaries in Liverpool, UK
7.11 Mapping the impact of ‘Operation Anchorage’ in Canberra, Australia, 2001
7.12 Pinpointing the likely residence of Jack the Ripper
7.13 Creating ‘families’ for police comparison purposes using geodemographics
7.14 Spatial variations in malicious fires, South Wales
7.15 Various types of arson, Leeds, UK
8.1 Differences between postal geographies and administrative boundaries in Leeds, UK
8.2 Mapping census variables in a retail GIS for Montreal, Canada
8.3 Mapping immediate retail catchments in London, Ontario, Canada in 1961 and 2005
8.4 Drawing a buffer around a potential new store in New Haven, Connecticut, US
8.5 Interpolation procedure within GIS
8.6 The end result of ‘sieving’ data to find optimal or ideal zones
8.7 Deriving hot spots of demand for potential new pawnbrokers in Houston, Texas, US
8.8 A one-mile buffer demarcated for a retailer in a US city
8.9 Use of Thiessen polygons for trade area demarcation
8.10 Estimated market share for an individual Asda store in East Leeds, UK
8.12 Spatial distribution of supermarket accessibility in Montreal, Canada, 2001
8.14 Areas of concern regarding poor access to grocery retailing in Toledo, Ohio, US
8.15 Mapping food deserts in Cardiff, UK
9.1 Variations in life expectancy for males at birth by local authority district, UK, 2010–12
9.2 Variations in likely future patterns of male heart disease in the US
9.3 Spatial variations in life expectancy in London plotted against child poverty
9.4 Variations in hospitalisation rates for heart disease across Michigan, US
9.5 Hot and cold spot mapping of late-stage colorectal cancer in Iowa, US, 1998–2003
9.6 Locating the geography of poorer diets, Leeds, UK
9.7 Obesity in Seattle, Washington, US
9.8 Plotting hot spots of childhood leukaemia in the North of England
9.9 Variations in hospitalisation rates for asthma in New York, 1996–2000
9.10 Stages in the creation of a road travel time cost surface for hospital accessibility
9.11 Estimated travel time by car to nearest GP surgery
9.12 Access to adult specialist inpatient hospices in England and Wales based on travel time
9.14 Location-allocation results for smoking cessation services in Leeds, UK
10.1 A selection of hazards and hazard impacts as identified by the New York City government
10.2 An example of user-contributed information: Flu Near You
10.4 Map showing storm vulnerability and location of evacuation centres in New York City
10.5 Type of damage and flooding extent post-Hurricane Katrina in New Orleans, Louisiana, US
10.6 Snapshot of USGS’s pedestrian evacuation tool capability
10.7 Vulnerability and drowning deaths from Hurricane Katrina
11.1 Generation of catchment pupil forecasts in Norfolk, UK
11.2 School locations plotted against population decline in New Orleans, Louisiana, US
11.4 Weighted Thiessen polygon boundaries around schools in Lancashire, UK
11.5 Flows to the University of Manchester from the rest of England
12.1 Mapping long-distance commuting in Ireland
12.2 Rapid transit flow patterns in Brisbane, Australia, during the working day
12.4 Accident hot spot analysis for cyclists and other road users, West Yorkshire, UK
12.5 Top four hot spots for bike accidents in Regina, Canada
12.6 Accessibility surface for public transport in Singapore
12.7 Optimal route for new rapid transit system in Thane, India
12.8 Airport connectivity in the US
12.9 Spatial variations in the location of ambulance stations and fire stations in London, 2012
13.2 Collapsing polygon features to representative points, or centroids
13.4 Park size and distribution of the white, non-Hispanic population in Washington, DC
13.5 Assessing park accessibility via containment and distance
13.8 Distribution of the white, non-Hispanic population and hazardous waste and TRI locations