ISYS3438 Chap.10 Geographic Visualisation Choices
Geographic Visualisation Choices
Geographic visualisation is appropriate when location or spatial relationship contributes to the decision. This chapter starts with spatial units and measure type, then compares dot maps, density views, choropleths, hierarchical statistical maps and cartograms.
It explains why counts and rates answer different questions, why missing regions need a distinct style and how projection and boundary choices create analytical consequences. A companion sorted view often supplies precision that the map cannot.
What this chapter covers
- 01
spatial units
- 02
map projections
- 03
dot and density maps
- 04
choropleth rates
- 05
cartograms
- 06
classification and missing data
Worked example · free
Separate workload from comparative need
- +1Keep visit counts for service workload.
- +1Create a defensible rate for comparative need.
- +1Show clinic points, period, legend and missing regions.
- +1Pair the map with a sorted rate chart and test classification breaks.
Key terms
- Choropleth map
- A choropleth map fills regions according to a value attached to each region.
- Cartogram
- A cartogram resizes geographic regions according to a variable.
- Projection
- A projection transforms the curved Earth onto a flat surface with unavoidable distortion.
- Spatial unit
- A spatial unit is the point, grid or bounded region at which data is represented.
Geographic Visualisation Choices FAQ
Should a choropleth show counts or rates?
Rates are usually better for comparing regions with different exposure, while counts show workload or volume. Present both when the audience needs capacity and comparative risk.
Why do classification breaks matter?
Breakpoints determine which regions share a colour and can make a pattern look sharper or weaker. Test alternatives, disclose the rule and avoid a conclusion that depends on one convenient setting.
When is a map unnecessary?
If the task is simply to rank regions and neighbourhood relationships do not matter, a sorted bar may be more accurate. Use geography only when place contributes analytical meaning.
Assessment move
For every map, write five labels before styling: spatial unit, measure, denominator, period and projection or classification rule. Build a non-map companion that answers the same comparison. Any disagreement reveals whether area, grouping or missing data is changing the interpretation. Confirm that geography contributes to the decision before drawing a map.
If the task is only to rank regions, a sorted common-scale chart is usually more precise. Record the spatial unit, coordinate or boundary source, projection and geographic role assigned by the software. Check unmatched locations, ambiguous place names and points placed at administrative centroids. Never interpret mapping errors as data patterns. Choose the form according to the quantity.
Dot maps show locations or events, proportional symbols encode magnitude at points and density surfaces summarise concentration under stated parameters. Choropleths compare values attached to regions and usually require rates when populations or exposure differ. Counts can still matter for workload or capacity, so pair count and rate when both decisions are relevant.
Test classification boundaries and disclose whether missing regions are blank, zero or unavailable. Inspect the effect of area and projection. Large polygons dominate attention even when their value is unremarkable, while small urban regions can disappear. Use insets, labels or a companion ranked view to recover important comparisons.
A cartogram deliberately distorts area to encode another quantity and therefore needs an explanation and geographic reference. Avoid implying precision beyond the source: exact household points or smooth density can overstate certainty and create privacy risk. Validate the map with a table of region, numerator, denominator and rate, then reconcile totals.
Change a defensible classification or smoothing parameter and note whether the conclusion persists. Write an annotation that identifies the visible spatial pattern without treating proximity as cause. Consider boundary definitions, mobility and neighbouring exposure before recommending action.
The final justification should explain why location changes the decision, why the selected map preserves the needed structure and which non-spatial view helps the audience verify magnitude. Complete a spatial claim audit by selecting several regions with different area and population. Recalculate their mapped values from numerator and denominator, check boundary joins and compare their ranking in a non-spatial chart.
Inspect whether colour classification or symbol overlap changes the apparent priority. Where a region is absent, label the reason rather than allowing blank space to imply zero. Write the final claim with the spatial unit and period included, then add one plausible non-spatial explanation that the map cannot resolve. This audit protects against treating proximity, cluster or boundary shape as a mechanism.
It also demonstrates when the map supports allocation, investigation or communication better than a table alone. Create a map-versus-ranking comparison using identical region values. Ask two peers to identify the priority and explain their evidence. Differences reveal whether polygon area, classification or familiarity is dominating the intended measure.
Use the result to decide whether the map should lead, support or be replaced by the common-scale comparison.