**Hello everyone!** How are you doing people? I hope everyone's having a wonderful day. The weather is still fine over here, giving us the opportunity to visit the beach and spend a couple relaxing hours. However, I am always very busy and that is the main reason why I did not get back to blogging for more than five days. Thankfully that's not the case any longer, as I found some free time and decided to add another part to this series. I am always in a rush though, so let's waste no more time. Let's do this! **As promised in a previous [Cartography post](https://steemit.com/steemstem/@lordneroo/introduction-to-cartography-choropleth-mapping) regarding Chloropleth mapping, we are now ready to proceed to the next category of Thematic maps, having already discussed the basic elements of isarithmic and choropleth mapping. This time we are going to take a deeper look at the fundamental elements of choropleth mapping that were mentioned in the previous part of this series. We will talk about the size and shape of the surface units utilized and share general information regarding the number of classes used and how it affects the process of choropleth mapping. We will also talk about the methods followed in order to define the range of each class, so stay focused.** As always, here comes the part where I include a personal note for all of you who are new to this blog; this is simply an introductory series about Cartography, which is the art and science of extracting metric information in order to create accurate 2D depictions of our 3D world. This means that I will be sharing broad information in a simplified manner, so that nobody gets too bored reading this post! There's always a high chance of learning a thing or two by reading till the end of this publication, so stay tuned! ![earth-634815_960_720.jpg](https://cdn.steemitimages.com/DQmTdJZRTkUJVY1dBd6HQmEKHFYQv4VwN5B9DYkkNsJmjs4/earth-634815_960_720.jpg) *Image Source: [pixabay.com](https://pixabay.com/el/%CE%B3%CE%B7-%CE%B7%CF%80%CE%B5%CE%AF%CF%81%CE%BF%CF%85%CF%82-globalalisierung-%CE%BA%CF%8C%CF%83%CE%BC%CE%BF-634815/)([CC0 Creative Commons](https://pixabay.com/el/service/terms/#usage) Author: [Geralt](https://pixabay.com/el/users/geralt-9301/))* # Symbolization Problems As explained in the previous parts of this series, Choropleth maps are desgined and constructed by taking into consideration the structure of the data being gathered. That said, it is more than obvious that the shape, size and orientation of the units utilized affect the quality of our end product. The Choropleth process relies on the creation and utilization of homogenous surface units with huge variations between the boundaries of successive units. That is the main reason why Cartographers need to approach this matter with caution, as the structure of the data gathered might induce systematic errors in cases where it fails to represent the underlying geographic distribution. There are three categories of errors that are usually generated by the fundamental elements of Choropleth mapping. The number of classes used and the proper selection of class ranges are the main factors of the ones generating systematic errors in Choropleth maps that have been thoroughly studied, to the extent that Cartographes often use error indices in Choropleth map memo boards regarding those types of errors in particular. The magnitude of errors affects the symbolization process and gives birth to more obstacles, as one can't accurately depict a geographic distribution with parameters that are not precisely known. This is the main reason why there are three main categories of errors, depending on the map's purpose and the information it was designed to contain. Some Choropleth maps are built in order to represent the exact geographic location of the distribution units, whereas there are cases in which Choropleth maps were designed to provide a general view of the geographic distribution utilized. Moreover, some Choropleth maps were designed in order to precisely depict the boundaries between classes, which are projected as straight lines. Let's take a look at the fundamental elements of Choropleth mapping. ![world-1626692_960_720.jpg](https://cdn.steemitimages.com/DQmUpwLFwhGCHHAcZTuVEcKW2uTHCCxk2AV8C83Xs9d7iTK/world-1626692_960_720.jpg) *Image Source: [pixabay.com](https://pixabay.com/el/%CE%BA%CF%8C%CF%83%CE%BC%CE%BF-%CE%B1%CF%86%CF%81%CE%B9%CE%BA%CE%AE-%CF%87%CE%B1%CF%81%CF%84%CE%B9%CE%BA%CE%AC-%CE%B4%CF%8E%CF%81%CE%B1-1626692/)([CC0 Creative Commons](https://pixabay.com/el/service/terms/#usage) Author: [PIRO4D](https://pixabay.com/el/users/PIRO4D-2707530/))* # Shape & Size of Surface Units The surface units of an area of interest can be perceived as parts of a pattern that represents a generalized view of the area. If the size of the surface units utilized exceeds standard limits then there's a high possibility that the spatial variation of the data being used tends to be homogenous, while in cases where the surface units are smaller than usual the variation of the end product is much larger. Different magnitude of variation between different areas of the map is often caused by the utilization of surface units that differ in size, resulting in an unequal map generalization which is never a desirable result. The Choropleth process induces the need for the selection of units with the same size and similar shapes; that is the most efficient way to get the best possible end product. # Number of Classes The most commonly used versions of the Choropleth process gives birth to end products that include symbols of a graded range. The number of classes used plays a rather significant role as it defines the level of detail of the geographic distribution being mapped, which basically means that Cartographers choose to include as many classes as possible. The only limitations placed are by the finite dimensions of the map surface, in other words Cartographers will always choose to include as much information as possible, as long as the map remains clear and readable. It is worth noting at this point that the maximum number of classes that can be included depends on multiple factors, one of the most significant of which is the complexity of the geographic distribution. Another significant factor is the utilization of color. In maps where no color is used it is a lot harder to include vast amounts of information and therefore Cartographers can only use a smaller number of classes. That is mainly due to the way the human sensory system works, as explained all over again in the previous parts of this series. It is worth noting at this point that Cartographers often used patterns or even intensity as a primary visual variable in order to depict different classes in greyscale maps, however it has been proven that users cannot observe more than eight different classes in Choropleth maps built without the utilization of color. Nature. ![Australian_Census_2011_demographic_map_-_Australia_by_SLA_-_BCP_field_2715_Christianity_Anglican_Persons.svg.png](https://cdn.steemitimages.com/DQmWLmzeUKoNbyUkefN1qxFh8gDDTPRF9dUB4pGN2rFC7S2/Australian_Census_2011_demographic_map_-_Australia_by_SLA_-_BCP_field_2715_Christianity_Anglican_Persons.svg.png) *Australian Census 2011, Demographic Map - Hue used as a primary visual variable in order to represent quantitative variations./ Image Source: [commons.wikimedia.org](https://commons.wikimedia.org/wiki/File:Australian_Census_2011_demographic_map_-_Australia_by_SLA_-_BCP_field_2715_Christianity_Anglican_Persons.svg) ([Creative Commons](https://en.wikipedia.org/wiki/Creative_Commons) [Attribution-Share Alike 3.0 Australia](https://creativecommons.org/licenses/by-sa/3.0/au/deed.en) Author: [Toby Hudson](https://commons.wikimedia.org/wiki/User:99of9))* # Class Range Defining the values that represent the boundaries between classes with accuracy is one of the most studied and discussed topic in Cartography in general and there are tons of information regarding the methods that are most commonly followed. Those values are calculated by the time that safe conclusions regarding the number of classes that will be used have been reached. The same methods that are used to define the class ranges are the ones followed in the creation of graded point and linear symbols, which by the way was the point of discussion of a previous post. Nowadays' scientific development and available technology has enabled Cartographers to develop more ways of defining the values that represent the boundaries between classes. Choosing class ranges can be a rather confusing task as Cartogtraphers have to make sure that the crucial values of a distribution are depicted with accuracy. The availability of multiple different methods makes it relatively easier for Cartographers to choose and use patterns that would result in a visual outcome that would not represent the data being used appropriately. In other words, it is easier to make significant mistakes that would in return downgrade the end product's quality. This works the other way round as well, meaning that the utilization of the appropriate class range and boundaries would definitely result in a much better view of the geographic distribution. ![800px-USA_states_population_density_map.PNG](https://cdn.steemitimages.com/DQmNrynLETwZtjhBc31b28yzhWJ6r7WPC9jQfpmJPZsgTMr/800px-USA_states_population_density_map.PNG) *Population Density Map, USA - Saturation used as a primary visual variable in order to represent quantitative variations./ Image Source: [commons.wikimedia.org](https://commons.wikimedia.org/wiki/File:Australian_Census_2011_demographic_map_-_Australia_by_SLA_-_BCP_field_2715_Christianity_Anglican_Persons.svg) ([Creative Commons](https://en.wikipedia.org/wiki/Creative_Commons) [Attribution-Share Alike 2.5 Generic](https://creativecommons.org/licenses/by-sa/2.5/deed.en) Author: [Marlon Richmond](https://commons.wikimedia.org/wiki/File:2004US_election_map.jpg))* **Alright everyone, that's it for now. Thanks for being here, another part of my *Introduction to Cartography* series has come to an end. There's still a long way to go, so make sure to follow me and stay tuned. If you do have any questions regarding this blog, please let me know in the comments below and I will do my best to provide prompt and detailed answers. More Engineering stuff regarding Cartography and Geology coming out within the next days, so stay tuned and follow me for more!** # PREVIOUS PARTS OF THE SERIES: 1. [INTRODUCTION TO CARTOGRAPHY](https://steemit.com/engineering/@lordneroo/introduction-to-cartography) 2. [CLASSIFICATION & BROAD CATEGORIES](https://steemit.com/engineering/@lordneroo/introduction-to-cartography-classification-and-broad-categories) 3. [CARTOGRAPHIC TRANSFORMATIONS](https://steemit.com/steemstem/@lordneroo/introduction-to-cartography-cartographic-transformations) 4. [CONFORMAL PROJECTIONS](https://steemit.com/steemstem/@lordneroo/introduction-to-cartography-conformal-projections) 5. [EQUAL AREA PROJECTIONS](https://steemit.com/steemstem/@lordneroo/introduction-to-cartography-equal-area-projections) 6. [AZIMUTHAL PROJECTIONS](https://steemit.com/steemstem/@lordneroo/introduction-to-cartography-azimuthal-projections) 7. [SCALE FACTOR & TRANSFORMATION](https://steemit.com/steemstem/@lordneroo/introduction-to-cartography-scale-factor-and-transformation) 8. [CARTESIAN COORDINATES & GRID SYSTEMS](https://steemit.com/steemstem/@lordneroo/introduction-to-cartography-cartesian-coordinates-and-grid-systems) 9. [3D COLOR SPACE](https://steemit.com/steemstem/@lordneroo/introduction-to-cartography-3d-color-space) 10. [COLOR SYSTEMS](https://steemit.com/steemstem/@lordneroo/introduction-to-cartography-color-systems) 11. [COLOR & PATTERN IN SYMBOLIZATION (Part I)](https://steemit.com/steemstem/@lordneroo/introduction-to-cartography-color-and-pattern-in-symbolism-part-i) 12. [COLOR & PATTERN IN SYMBOLIZATION (Part II)](https://steemit.com/steemstem/@lordneroo/introduction-to-cartography-color-and-pattern-in-symbolism-part-ii) 13. [CARTOGRAPHIC SYMBOLIZATION & VISUAL VARIABLES](https://steemit.com/steemstem/@lordneroo/introduction-to-cartography-cartographic-symbolization-and-visual-variables) 14. [SYMBOLIZING POINT DATA](https://steemit.com/steemstem/@lordneroo/introduction-to-cartography-symbolizing-point-data) 15. [SYMBOLIZING LINEAR DATA](https://steemit.com/steemstem/@lordneroo/introduction-to-cartography-symbolizing-linear-data) 16. [SYMBOLIZING SURFACE DATA](https://steemit.com/steemstem/@lordneroo/introduction-to-cartography-symbolizing-surface-data) 17. [SYMBOLIZING VOLUMETRIC DATA](https://steemit.com/steemstem/@lordneroo/introduction-to-cartgoraphy-symbolizing-volumetric-data) 18. [STATISTICAL SURFACE & POINT SYMBOLS](https://steemit.com/steemstem/@lordneroo/introduction-to-cartography-statistical-surface-and-point-symbols) 19. [STATISTICAL SURFACE & LINEAR SYMBOLS](https://steemit.com/steemstem/@lordneroo/introduction-to-cartography-statistical-surface-and-linear-symbols) 20. [ISARITHMIC MAPPING](https://steemit.com/steemstem/@lordneroo/introduction-to-cartography-isarithmic-mapping) 21. [ELEMENTS OF ISARITHMIC MAPPING](https://steemit.com/steemstem/@lordneroo/introduction-to-cartography-elements-of-isarithmic-mapping) 22. [ISARITHMIC ANALYSIS](https://steemit.com/steemstem/@lordneroo/introduction-to-cartography-isarithmic-analysis) 23. [CHOROPLETH MAPPING](https://steemit.com/steemstem/@lordneroo/introduction-to-cartography-choropleth-mapping) ![DQmQPRBLmhWag36FBxYVNJNKZRUsBbpPeZvm7FVixnWVXhk_1680x8400.png](https://steemitimages.com/DQmTjUEWdmEvtQcJMueV3YTGnHVNweSGbfDAAEVnCRGPJm4/DQmQPRBLmhWag36FBxYVNJNKZRUsBbpPeZvm7FVixnWVXhk_1680x8400.png) **IMAGE SOURCES:** - [pixabay.com](www.pixabay.com) - [commons.wikimedia.org](https://commons.wikimedia.org) **REFERENCES:** ***University Textbooks & Course Lectures:*** - Χαρτογραφία Ι/ Cartography I -TSOULOS(National Technical University of Athens, School of Rural & Surveying Engineering, Course Lecture Notes) ***Internet Links:*** - https://pubs.usgs.gov/tm/2005/11B01/05tm11b01.html - https://www.researchgate.net/figure/A-Isarithmic-and-B-contour-line-maps-produced-by-the-study_fig4_257820422 - https://datavizcatalogue.com/methods/choropleth.html - https://prism.ucalgary.ca/bitstream/handle/1880/45758/2001-693-16.pdf?sequence=2&isAllowed=y - https://gisgeography.com/choropleth-maps-data-classification/ https://cdn.steemitimages.com/DQmRPE1XvcHNHHRD1g5aThwFop2fXAZxrdy198gNH7T86zK/STEEMSTEM-bygtg.gif _{**Video Credits @gtg**
**GIF by @katerinaramm**} ![DQmQPRBLmhWag36FBxYVNJNKZRUsBbpPeZvm7FVixnWVXhk_1680x8400.png](https://steemitimages.com/DQmTjUEWdmEvtQcJMueV3YTGnHVNweSGbfDAAEVnCRGPJm4/DQmQPRBLmhWag36FBxYVNJNKZRUsBbpPeZvm7FVixnWVXhk_1680x8400.png) **Thank you for your attention!** **Hope you enjoyed this post and did learn a thing or two.** **Follow me and stay tuned for more engineering blogs.** **Highest Regards** **@lordneroo**

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