Cartography Cheat Sheet for R Spatial Mapping
A Chinese R cartography reference for spatial layers, thematic symbols, classification, labels, legends, scale and map export review.
What this reference covers
This reference organizes R cartography around spatial objects, attribute fields and visual encoding. It helps a mapper choose between classified colors, proportional symbols and category symbols, then complete labels, legends, scale information and output checks without treating a map as decoration alone.
Start with geometry and coordinate reference
Record whether the data contains points, lines or polygons, which field carries the topic and which coordinate reference each object uses. Align the coordinate systems before comparing locations. A correct-looking extent does not repair a coordinate mismatch.
Make the visual encoding explainable
Use continuous values with a documented classification or proportional scale, and use categories with a deliberate palette or symbol set. Keep the legend, title, units and labels consistent with the variable. Add boundaries and annotations gradually so a dense layer can be diagnosed instead of hidden.
Maintenance note
Classification breaks, colors, projection choice and export resolution affect interpretation. This sheet is an operation index, not a spatial-quality or map-design guarantee. Content review date: 2026-08-23.
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R Cartography study guide
Confirm geometry and coordinate systems, choose one visual encoding for the main variable, add support layers gradually and review the final map at its actual output size.
Before you start
- Prepare a PDF reader and an R environment with a small spatial object.
- Record geometry type, coordinate reference and the attribute field to explain.
- Decide whether the output is for a report, web page, print or a narrow screen.
Quick start
- 01
Inspect geometry and projection
Check point, line or polygon geometry, coordinate reference, units and key attributes before plotting.
- 02
Select the main encoding
Use classified color or proportional symbols for continuous values and category symbols for discrete groups, keeping one clear meaning per channel.
- 03
Add labels and legend
Align title, units, scale, north indicator, legend and annotations with the variable, reducing fields when labels become crowded.
- 04
Review the export
Open the output at screen, print and thumbnail sizes, checking text, contrast, boundaries, labels and legend before preserving the script.
Usage tips
- Draw one thematic layer first, then add boundaries, labels and supporting context step by step.
- Record classification breaks, colors, symbol sizes and projection in the analysis notes.
- Recheck contrast and text size when the map is printed or reduced.
Troubleshooting and uninstall
Why are map layers misaligned?
Compare coordinate reference systems and units for every spatial object, transform them consistently and plot a minimal pair before adding styling.
Why do labels cover the legend or each other?
Reduce simultaneous fields, adjust label placement and legend layout, then inspect the map at the final display size.
Frequently asked questions
Which R cartography topics are covered?
The sheet covers spatial layers, coordinate systems, thematic symbols, classification, labels, legends, scale and export review.
How should a continuous variable be shown?
Use a documented classified color or proportional scale, explain units in the legend and keep breaks consistent across comparable maps.
What should be checked before publishing a map?
Check projection, data date, variable meaning, classification, legend, labels, contrast, source note and output resolution.
Does the sheet validate spatial data quality?
It is a mapping reference; geometry validity, projection suitability, source quality and analysis assumptions still require separate checks.