Examples for Good Map Design#

🚧This page on the training platform and the entire content is under ⚠️construction⚠️🚧

In this chapter we will be discuss well designed maps and give examples on how to recreate the design elements in QGIS. A second part of this chapter will focus on common mistakes and good practices when designing maps.

In this section, we will present some well designed maps and discuss how to create similar maps. If you need further examples for good map design, check out these websites/repositories:

Map Examples#

Map Example 1: Flood-affected areas and roads in the Somali Region, Ethiopia#

../../_images/ET_Somali_Humanitarian_Access_Flooded_Areas_11152023_A4.png

Fig. 107 Flood affected areas and roads in Somali Region, Ethiopia (Source: OCHA)#

Context: Situation in Ethiopia

The Greater Horn of Africa receives 20 to 70 percent of the annual total rainfall in the months from October to December. The IFRC reports a exceptionally high forecast probability (over 80%) of experiencing wetter than normal rainfall condition. Additionally, El Niño conditions started between July and August, which further accrued the possibility of high rainfall conditions in Ethiopia.

Since October, floods have affected at least 763,000 people across the region, took 33 lives in the Somali Region alone, and a total of 4,806 livestock has been reported lost.. Furthermore, the flooding resulted in immense damage to infrastructure, transportation, schooling. The livelihoods and health of the population has been greatly affected. The impact of flooding is projected to increase in the next years which will lead to more flash and river floods.

Access Maps, such as the one above, play a crucial role in helping informing information manager and ground staff which areas are accessible. This is especially important since a timely deployment of relief or aid operations is of great importance in flooding disasters.

(Source: IFRC)

The map above shows the flood affected areas, as well as the important road networks in the Somali Region, Ethiopia, in November 2023. Maps such as these are crucial for humanitarian aid workers when planning relief or aid operations and need to be up to date. They display important settlements, and most importantly, the accessibility of roads and airstrips.

This is a thematic map with a clear purpose and the elements on the map are reduced to the most necessary elements relevant to the purpose of the map.

  • A shapefile for the flood affected areas was given a hashed fill. In QGIS, you can find this symbology

  • A layer with the road network has been put above the layer with the flood-affected areas. The road symbology has been categorized into three categories: Accessible road (green), partially accessible road (grey), and hard to reach road (red).

  • The topmost layer is a point-layer with information on unaccessible roads or bridges as well as the location of airstrips and which airstrips are accessible. The points have been symbolized with SVG-symbols.

  • (The administrative boundaries of Ethiopia are set apart from the surrounding countries by making the polygon a clear white and the surrounding countries in a shade of grey. This can be achieved by copying the polygon of Ethiopia into a new layer, and changing the symbology respectively)

Note

The color scheme of the roads makes an intuitive reading of the map possible, as red is associated with negative qualities, whereas green with positive qualities. It should be noted, however, that persons with colorblindness will have trouble reading the map.

Map Example 2: Flooding Risk in the Ouham Region, Central African Republic#

../../_images/REACH_CAF_Susceptibilite_inondations_CF32_Juillet2023_A3_FR.png

Fig. 108 Flooding risk in the Ouham Region, Central African Republic (Source: REACH)#

Context: Situation in the Central African Republic

The Central African Republic has been hit by destructive floods in late 2019, which displaced over 100,000 people and causing considerable damage to infrastructure. The floods have destroyed shelters, obstructed transportation routes, and have led to disease outbreaks such as cholera and malaria. Due to climate change, such floodings become more frequent, leading to increased vulnerability for towns and villages. Since such natural hazards are hard to predict, the changing climate reduces the resilience of communities.

Source: REACH Initiative

This map displays the flooding risk using a raster image. The raster data was calculated using several factors, including the precipitation intensity, the maximum duration of precipitation, the height of the nearest drainage, the flow direction and river network, the topographic humidity, a digital elevation model and the ground cover.

  • The raster data is displayed using a diverging color ramp. (Here you can check out how to assign a color ramp)

  • The surrounding administrative districts have been overlayed with a transparent grey.

  • The river network has been added in blue

  • The main roads as well have been added in black

  • Settlements are displayed i black dots. This helps to identify areas with a higher population density in the areas most at risk

Good practices and common mistakes in mapping#

In order to produce good maps, there are some basic rules to follow and common semiological mistakes to avoid.

Map composition#

Key elements of a map#

In order to provide your audience and readers with sufficient information so they can contextualize the map, it is important to add these key map elements:

  • Title

  • Legend

  • Scale

  • Orientation

  • Source

  • Localization (Overview) Map

  • Author

../../_images/en_good_map_composition_example.png

Fig. 109 Elements of good map composition#

The title summarizes in a few words the information represented on the map, giving the reader useful contextual information. Titles should include the following information:

  • The place, with several degrees of precision according to the scale (Country, Region, Township,…)

  • The subject intelligible by all (make sure that the acronyms used are detailed elsewhere on the map)

  • the date of the represented data

Examples:

  • “Access to health care in Maputo, Mozambique in 2022”

  • “Flooding Risk in Ghardaïa, Algeria”

The legend is key to interpreting the information represented on the map. Without it, it is impossible to understand the meaning of the different symbols and colors used map. In order to guide the reader, the legend must be:

  • Comprehensive: All the data on the map must be presented in the legend.

  • Representative: the figures on the map and in the legend must match (same size, same color, …).

  • Organized: the data in the legend can be grouped by thematic categories (health, environment, background map, …) or by type of figure (point, line, surface) to facilitate reading.

../../_images/en_legend_good_practice.png

Fig. 110 Example of a well organized legend#

The scale bar is essential to a map since it gives the correspondence between a distance measured on the map and the distance in the real world. There are two types of scales:

  • The numerical Scale is expressed as a fraction (1/25000 or 1:25000) which indicates the equivalence between 1 centimeter on the map and the real distance. It is a scale that can be calculated with GIS software, and is often found in topographic maps. A scale of 1:25000 means that 1 cm represents 25000 cm (or 250 meters) on the ground.

  • the graphical scale is expressed by a line on the map, with an associated distance value. This scale is very useful to have an idea of the distances on the ground. The graphical scale will always be the correct size, even if a different printing format is used, since it will undergo the same transformation as the rest of the map

../../_images/example_scale_bar.png

Fig. 111 Scale bar examples#

Orientation#

Even if by default the majority of the maps are oriented to the North, it is still necessary to specify the orientation of the map. It is often indicated by an arrow to the North. Sometimes the orientation of different in order to optimize the representation of the study area on the map.

Sources#

Any data represented on a map should have its sources indicated. This provides a record of the data used, but also references the author of the data. The reader will then be able to look for more information on the sources if he wishes. Open access geographic data, such as OpenStreetMap, are more and more numerous and must also be cited on the maps.

It is possible to give the source of each data under the legend, or to do it in a dedicated space in the map. The level of precision of the sources varies according to the author or the precision of the data.

The 4 semiological errors#

1. Proportional circles vs. solid colors#

Caution

DO NOT represent quantitative stock character/data with a solid color.

This is one of the most common mistakes in mapping. While this representation is graphically appealing, it is still false and distracts from the message of the map.

It is a mistake because:

  • You lose the order relationship between the data (a circle can be twice as big as another one, a color cannot be “twice as dark”)

  • Countries with a large surface area stand out visually (eg.: Russia in the example below)

  • We are trying to represent data that has nothing to do with the area of a country, but rather speaks of individual elements

2. Color gradient vs. distinct color palette#

Caution

DO NOT use a separate color palette to represent ordered entities

A representation that “feels right” because it seems logical that a “low” rate would be represented differently than a “high” rate.

It is a mistake because:

  • By using a differentiating color variable, you lose the ordinal relationship between entities. Instead, a gradient of the same color that should be used.

  • Different colors are used to differentiate between distinct entities.

3. Gradient in a single color vs. Gradient between two colors#

Caution

DO NOT use a gradient across two colors for an always positive data.

This is a mistake that is often found because our brains are used to prioritizing certain colors, especially green to red, or blue to red. We must remember that __if our values are always positive, we must stay in the same color that will degrade into several shades.

A gradient between two colors can be used when it is necessary to show a gradation that can go from negative to positive. As for temperatures, it makes sense to distinguish negative values (in shades of blue for example) and positive values (in shades of red).

It is a mistake because:

  • By choosing different colors for values that are linked to each other, our eyes perceive a difference between the elements, and not an order.

  • Darker colors stand out more than lighter colors, and can be perceived as more important.

  • The map will send a message of divergence, of opposition between certain values, when we are simply trying to represent a hierarchy between values

  • In this way, the color itself directly indicates information about the trend (positive/negative or increasing/decreasing).

4. Limited Geometric Symbols vs. Complex Icons and Symbols#

Caution

DO NOT use too many symbols in a thematic map

Incorporating a multitude of symbols (and data) for a informative map is a common desire. However, too many symbols can overload the map and reduce the readability of the map. Using too many symbols (especially geometric ones) can make it difficult to read and understand the map.
__The eye can easily distinguish 4 to 5 different symbols. Beyond that, it is difficult to distinguish the elements. This is a less serious error because it does not convey false information on the map.

It is a mistake because:

  • It complicates the map and limits its impact.

  • Sometimes you are forced to represent several symbols, so you must be careful about overlapping points and overloading the map.