Socioeconomic conditions in the Liverpool City Region
My mapping work on the Liverpool City Region focused on social characteristics such as the population and education and economic conditions including deprivation, poverty and employment. I have generated a number of maps for my research into socioeconomic conditions in Liverpool through QGIS, ArcGIS and ArcGIS Pro. The spatial representations below include choropleth maps, graduated symbol maps and density equalizing cartograms.
The Liverpool City Region
I identified the dispersal of the population through a graduated symbol and a dot density map. The population data was sourced from the most recent national census and it shows that the city of Liverpool is the major population centre in the region with the most densely populated areas situated here.
For the graduated symbol map, I performed a centroid function to plot the mean point for each of the six boroughs and attached the population XLS file to the six points. The point was set as a graduated symbol to reflect the population data and shows that a larger circle represents a larger population.
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My goal was to highlight the economic conditions within each of the six boroughs, so I set the LSOA boundary shapefile to a 'hairline width' and widened the boundaries of the six boroughs. This shows how the economic conditions vary within a borough, for example the northeast of Wirral contains particularly deprived areas whereas the southwest shows areas containing less deprivation and higher employment.
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IMD Change A deeper look into deprivation was possible by comparing the most recent data with older indices. The IMD Decile data from 2010, 2015 and 2019 is presented as three choropleth maps below.  Below are my projections of how the IMD Decile and Rank of each LSOA has changed between 2015 and 2019. To achieve this, I joined both the 2015 and 2019 IMD .xls file to the LSOA polygon layer in QGIS. Following this, I exported the layer as an Excel readable file, as this contained the statistical data matched to the correct spatial boundary, and executed the formulas 'IMD Rank 2019 - IMD Rank 2015 = Rank Change' and 'IMD Decile 2019 - IMD Decile 2015 = Decile Change' to identify how each LSOA has changed in the four-year period.
  This equation would also have worked through the field calculator function in QGIS but I chose to complete it through Excel to explore some further statistics of change. Some of these figures are listed below and indicate that deprivation has increased across the Liverpool City Region.
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The city of Liverpool
The next few graphics present a ward-level analysis of the city of Liverpool. In the first chart below, the population change from 2000 and 2020 is detailed as an arrow series and below this, an area chart details the population change in five-year intervals. Both charts were made with Datawrapper.
Following on from this, I have included a Treemap of the 2011 population data which I made using Raw Graphs. This illustrates the data proportionally, although without a spatial reference. To depict the data spatially, I've generated a choropleth map with the population totals labelled for each ward and the density articulated through colour shading, with concentric circles added too. Also included is a density equalising cartogram to weight the spatial boundaries of each ward by population density.
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The initial map illustrates a breakdown of the qualification in each ward across Liverpool and was created in ArcGIS Pro. Following this, the density equalizing cartogram below was created on ArcGIS Pro to compare the total number of residents with Level 1 qualifications with the number of Level 4 for each ward in Liverpool. The Level 1 qualifications map (left) shows the north of Liverpool much larger than usual. Wards including Fazakarley, Anfield and Clubmoor have over 2000 residents with Level 1 qualifications as an individual’s highest form of education. The Level 4 qualifications map (right) shows this trend in reverse with wards including Central, Riverside, St Michael’s, Mossley Hill and Church containing over 5000 residents with Level 4 professional strata.
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I generated a choropleth map on unemployment and jobseeker’s claims to illustrate the economic activity of residents across Liverpool. The areas with the highest unemployment rate of 15% and above are Everton, Princess Park, Norris Green and Kensington and Fairfield. Wards with low unemployment rates in south Liverpool, including Mossley Hill, Church, Woolton and Childwall also show a lower number of jobseeker’s claimants.
The two choropleth maps show different colour schemes. Whilst the jobseeker’s claims map has a simple green-to-red scale, I chose to use a blue theme for the unemployment map. The unemployment data is shown in a different shade of blue and reflects the total, but the wards located outside of the Liverpool city boundary remain the same colour. The River Mersey has a gradient theme and is a deeper black in the southeast.
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The final representation in this section includes rail travel data which is discussed in further detail in another chapter of my page. The map details the employment score for each Lower Super Output Area in Liverpool with the ward boundaries included also. This builds on the previous choropleth maps by showing how spaces within the wards perform differently which is particularly useful for larger areas such as Speke-Garston and Fazakerly. The percentage of residents commuting to work by train was included as a graduated symbol and executed through the same function as the Liverpool City Region population map.
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