Resources for Map-making


There are MILLIONS of online learning resources regarding map making, and I also learn the best via online materials. This is a storage space for myself on materials / papers / books / websites / codes related to map making. If you find this place useful, I will be more than gratified.


Last Updated: 17 Aug 2021

Table of Contents

Cartography - Colour Selection

In most cases, Color Brewer would save your life in selecting colours. In general, think about if your color scheme is: 1. Colour-blind friendly; 2. Photocopy friendly and 3. For sequential, diverging or qualitative data

  • Color Brewer
    • a diagnostic tool for evaluating the robustness of individual color schemes

Cartography - Choosing classification method

Classification affects how you would interpret the results of chloropleth maps!

Types of Chloropleth Map Classification Methods, from Geospatial Analysis 6th Edition, 2020 update

Classification scheme Description/application
Unique values - Each value is treated separately
- Each value is mapped as a distinct color
Manual classification - Manually specifies the boundaries between classes required as a list, or specifies a lower bound and interval or lower and upper bound plus number of intervals required
Equal interval, Slice - The attribute values are divided into n classes with each interval having the same width=Range/n.
- For raster maps this operation is often called slice
Defined interval - A variant of manual and equal interval, in which the user defines each of the intervals required
Exponential interval - the number of observations in each successive interval increases (or decreases) exponentially
- Intervals are selected manually
Equal count or quantile - Intervals are selected so that the number of observations in each interval is the same.
- Ideally the procedure should indicate the exact numbers assigned to each class
Percentile - Standard version equal percentages (percentiles) are included in each class
- a variant of equal count or quantile plots. .
- Example: <=1%, 1% to <10%, 10% to <50%, 50% to <90%, 90% to <99% and >=99%
Natural breaks/Jenks - Widely used within GIS packages
- variance-minimization classification technique
- Breaks are typically uneven, and are selected to separate values where large changes in value occur.
- Could be significantly affected by the number of classes selected and tends to have unusual class boundaries.
- Unsuitable for map comparisons
Standard deviation - The mean and standard deviation of the attribute values are calculated, and values classified according to their deviation from the mean (z-transform)
- Usually at intervals of 1.0 or 0.5 standard deviations.
- often results in no central class, only classes either side of the mean and the number of classes is then even.
- central class (defined as the mean value +/-0.5SD)
Box - A variant of quartile classification designed to highlight outliers
- Typically six classes are defined, these being the 4 quartiles, plus two further classifications based on outliers. These outliers are defined as being data items (if any) that are more than 1.5 times the inter-quartile range (IQR) from the median. An even more restrictive set is defined by 3.0 times the IQR.
- Similar ideology as Box plots

Cartography - General

Map Projections

Use Project Wizard to select the appropriate projection without knowing the details and maths behind projection!

Spatial Statistics with GIS

Charts and data visualisations

Most importantly, remember the principle of proportional ink (Bergstrom and West 2016):

The principle of proportional ink: The sizes of shaded areas in a visualization need to be proportional to the data values they represent.