Art and Science of Map Making

Geog 167, Summer 2008

By Aerin Cho
IDS/Geography '08

Week 1:

Qualities of Good Maps
1. A good map engages the reader actively, by allowing a smooth guidance to understand its components by using innovative techniques. (*1)
2. A good map can provide readers with clearly legible symbols and captions. They are not distracted by colors or designs, and are reasonably spaced and well organized.(*2)
3. A good map can clearly portray its objective or purpose. A good map can do this by being selective of certain infromation to portray and omitting unnecessary ones. (*3)

Qualities of Bad Maps
1. A bad map is a representation of too much information being crowded into a small space, or scattered across without any clear overall uniformity. (*4)
2.A bad map lacks in effective figure-ground organization (Robin Ch.18) - including visual contrast in colors and texts. (*5)
3.A bad map fails to deliver the map's purpose to the traget audience, by using a peculiar language or by being outdated. (*6)

Examples of Good Maps

National Geographic - Human Atlas Map
Weather Forecast Map - Infared National Satellite
(I was not able to upload these maps because they are interactive maps - but please click on the links and you will be redirected to the appropriate maps.)

Traditional maps have been imprinted on 2-dimensional surfaces and readers could not engage in changin the images. Today, new computerized techniques encourage readers' participation in exploring different layers of maps, selecting information to appear on maps, or visualize the changes over time. The national graphic human atlas map is an example of an interactive map that allow readers to click on different parts of the maps to zoom in and acquire selective information in an organized way. Because of its selectivity, readers may avoid confusion from trying to take in alot of information at once. The weather forecast map is an example of an animated map that allow readers to observe the changes in clouds over time. Such animation technique allow readers to understand the movement over time on one single map, whereas without it, they would have to flip through several different maps to capture the movement at each time period. Incorporating new and innovative methodologies may better guide readers to understand its components smoothly and cohesively.


(I apologize for the fuzzy-ness. The original image had better pixels - See

I think this is a good map because despite the amount of information and labels the map contains, the primary and secondary variables are well thought out and legibly presented. Presenting names of countries in bold letters, using different colors for smaller provinces and types of boundaries, and italicizing certain geographical components are well done to differentiate the information presented. Symbols like the star and the circle also stand out very well in constrast to others as the national capital and other major cities. Also the types of boundaries are clearly differented by colors and patterns, and its continuation into the neighboring countries are effective. The map is well-centered and is comprehensive to understand general georgraphical knowledge of Sudan.


I think this map is good in a sense that it is clear in its objective and what the map is trying to get across to the readers. The map's captioned "China's Critical Sea Lanes", and the important sea lanes are drawn by red arrows, which stand out the most in the map. The map contains the small scale, and a clear inset with legible symbols. I also thought the small white insets that point to each strait or port was very effective. Though I think that the map could have been centered slightly more to the Southern seas where the most sea routes are, overall I was able to quickly and smoothly capture the objective of the map. The map could have contained more geographical information such as capitals and other landscapes, I felt that the map purposefully omitted unnecessary information to focus on the targeted information.

Examples of Bad Maps


I thought this map was very scattered and failed to create an effective structure to present different information and components. First of all, most of the labelings are too small to read legibly, and the symbols (such as fire represeting the conflict villages) are too similar with each other to clearly differentiate when they are so closely bunched together on the map. Also the placement of the inset boxes are scattered on all three corners, and the upper left hand inset cannot be clearly understood its connection to the map. The middle left inset of an example of a conflict village is too small and its characteristics are not visually represented so I do not see the point of presenting such inset. Overall, the color contrast and the landscape marks make it harder for the readers to examine the map.


This map was extremely hard to read because of its lack of figure-ground orientation. Because the thick green grids that divide the land and sea mass into prospective squares is so vivid, the actual land is faded in contrast and gets lost behind this first layer that pops out too much. Additionally, small squares also create too much visual distraction on the map by hiding other layers behind it. Too improve this map, the color of grid should be lighter and thinner to complement other layers. Also, The map has no clear explanation of what UTM zone is and what the x-axis and y-axis values are.


I thought this was an interesting example of an outdated map that can no longer be delivered to the needs of the public today. This map is found in the middle of downtown Tokyo in Japan (where I grew up in for 15 years.) where it is bustling with new comers to the city, including foreigners who are most likely unable to read Japanese. No streets are numbered or labeled, which are problematic even to the native Japanese who have come to the area for the first time. Only the buildings and stores are mentioned, and only the local residents in the area who have lived there for long enough to have a general sense of the area may find such map helpful in locating stores. However, I am highly skeptical that all of these buildings still exist as the map indicates, as this part of Tokyo is constantly changing and being re-developed. I think that this example re-enforces the significance of updating information in modern world and creating it with universal representation for increasingly globalized networks we see today.

Week 2:

This is a pdf version with better resolution.

The original map of LA metro railway system was a little too simplistic. It could have integrated more useful information in the given space, which was mostly vacant. In order to add more geographical features and details to the LA metro system map, I decided to use the most comprehensive transit system map available on to see what other information will help improve the railway map. The specific details I wanted to modify were the shape of coastlines, simplified rail routes (adding the right bends and curves to it), and more detailed geographical labeling such as cities.

Narrowing down what to include in the map from various information available was extremely difficult, because the information I put in should be presented coherently and with some sort of purpose so the audience can easily understand the map. Some questions I decided to answer before working on the map were, “Who will read this map?”, “How will this map be used for?”, and so on. After browsing through different metro system maps of other cities, I realized (again) that fundamentally the use of public rail system is far less prevalent which leaves a lot of room in the map other major cities in the world usually do not have, which creates the cycle of impracticality to use trains because it does not extend as far. So I wanted to modify the map in ways that the map could appeal more in practicality to use metro for people in LA, though I personally believe the system need a lot of work at this point.

Because the LA district does not have train system that extends far enough, the users tend to often have combination of train and bus. I have personally experienced this inconvenience and have wondered how much more efficient it would be if I could take the bus first to the metro station and transfer to avoid traffic in downtown for example. So I wanted to give the general ideas of how the bus routes intersect with each metro station, and appeal to the public that combination of public transportation is possible. Though originally each bus route was color coded and numbered in several different ways, I wanted to keep the map as straightforward as possible by changing them all to a uniform color. I also wanted to not let bus routes distract readers from the main of this map which is the rail and maintain a clear ground-figure orientation. I also included major airports because they are one of the most practical landmarks for those who would be most interested in utilizing public transportation. Other landmarks could have been also helpful, mainly public spaces known to the most people. I attempted to add more practical information to give an overall appeal to the use of public transportation (with the oil price hiking up, it may be easier than before). At the same time, I tried to not overwhelm it with too many details because when a map is too complicated to comprehend, I believe that it directly correlates to readers’ interpretation that public transportation is too complicated to understand and utilize.

Final Project Proposal:

I plan to complete my final project by creating a UCLA recycle map. I want to identify all the recycling bins and trash shoots that exist on campus, and present a comprehensive map. I hope to create a map that indicates the types of recycling bins (newspaper, glass, cans, plastics, etc) and other related information that will help all visitors and students on campus to understand how they can enhance recycling and raise awareness of it. The map should be appealing to the significance of recycling on campus and its objective to raise recycling rate on campus. As a student on campus, I personally were often confused where certain types of recycling bins were because different locations had different recycling trash bins. I plan to visit recycling office on UCLA campus, to gain more information on locations of recycling bins. I believe that UCLA's recycling facility has recently been trying to increase the amount of its activities on campus, yet they still lack many factors that other campuses use, such as University of Washington where every regular trash can comes with recycling trash bins. UCLA recycling has a discrepant pattern, and recycling bins are placed randomly across campus. I would like to also depict this in creating the map.

Week 3:

Part I

Equal interval classification is easy to understand because all breaks are equal in range. This classification is good when several maps are being compared, because the equal intervals give them a uniformity. However, in this map we are only trying to see the 2000 population density in california alone. And most counties population data have been bunched into one interval, except for the orange county. This makes the map hard to understand and ineffective because all other relative information are hidden or bunched together under this classification.

Quantile classification method distributes a set of values into groups that contain an equal number of values. This is interesting contrast from equal intervals because this classification definitely creates a pattern we can see. There is clear contrast between each density levels and colors. However, its shortcoming may be that its patterns may be overly expressed and intervals range become too distorted. For example, the lowest value interval has approximately a range of 19 where as the highest value interval has range of about 1000. This classification cannot depict outliers, or a case of when a few counties with extremely high (which is often the tendency) density that set them apart from the rest.

Standard Deviation classification finds the mean, and sets itnervals of 0.5 to show how much the data deviates from the mean. This is interesting because we could see from the map very clearly that Los Angeles and San Francisco regions deviate the most from the rest, and that seems very logical from our understanding as well. However, its shortcoming of this map is that overall counties in California have population densities that do not deviate too far from the mean. They are all placed within the two standar deviations, which may be too simplistic portrayal of density data.

It is a manual data classification method that divides data into classes based on the natural groups in the data distribution. It uses a statistical formula (Jenk’s optimization) that calculates groupings of data values based on data distribution, and also seeks to reduce variance within groups and maximize variance between groups. Overall this classification produced the most visually pleasing and informative map that portrays the relative levels of density among the counties. Its shortcoming may be that the classification method is somewhat subjective because it is done manually, and it may be different when comparing data from one year to another. ArcGIS had a function to calculate this which could be read and edited, and for the most part I agreed with the breaks it determined.

Part II

Califonia Population Density: From 1970~2000

Natural Breaks Classification
I believe that out of four methods we've used in Part I, the natural breaks classification method was the best visualization for the density map. However since we are comparing 4 different years in the animated map above, I felt that the shortcoming of all four methods mentioned in Part I was that the density levels varied for data each year. For example, in the natural breaks method above, each year's density levels have different breaks. Perhaps this problem can only be solved by a manual classification method, by creating natural breaks from the aggregate values of all 4 years' data. Otherwise, the natural breaks classification gave these four maps the most comprehensive and relative information about population density. The visualization effect also came out without being overly crammed with dark colors. The natural breaks were able to especially highlight the counties with the highest population density very well (San Francisco & Los Angeles regions), and other counties were well grouped under lower density level in a lighter shade, not distracting the higher density counties. As the maps were animated from the year 1970 to 2000, natural breaks classification was able to clearly emphasize these high density counties and portray the expansion in the surrounding counties of San Francisco and Los Angeles.

I could see clear patterns in the above map that San Francisco and Los Angeles (adjoined by San Diego) regions are the most densely populated areas in California. And over the three decades from 1970 to 2000, I could analyze from the maps that the population density has spread from these centers and out into the surrounding counties. More specifically, population density has increased to the Southern valleys like Fresno from the North Bay area, as well as to the inland region like Riverside from Los Angeles. San Diego has also increased in its density relative to the other counties in this trend. I also was able to see that Southern California's change in population density occured most rapidly in the 90's, where as the Northern California's density has grown slowly since 80's and rapidly in 90's. From this, I specualted the possible effects of suburbanization trend in Los Angeles that correlate with white flight, or richer folks moving out of Los Angeles to the surrounding areas, like Santa Barbara or Riverside that show up as high density only in the 2000 data. Though the natural breaks classification method allows speculation of density level relative to all other values in the data, I was still able to understand general trends of population density in California and how it shifted over time.

Week 4:

Source: US Census
Created by: Aerin Cho

I created three different landuse maps of Carson city in multi-colors, two hues, and in black and white. As the colors decreased in variety from the left to the right, patterns were utilized to differentiate the 13 different landuses in Carson. I also included major roads (with its names) and railroads, since I was aware that the transportation is a key characteristic to this highly industrial city located near the Long Beach. Railroads were easier to see because of its unique shape, major roads were often hard to see in lack of effective figure-ground due to the use of similar colors in the latter two maps. This problem was met by creating halos behind them.

The color combinations in the multi-color map was chosen with intention to differentiate colors as much as possible but to be visually pleasant without one or two colors sticking out among others. I referred to the for the effective combination of colors. Also for the two-hue map, I referred to the website to confirm that yellow and green were a visually effective combination. Then I acquired the RGB values for different shades of green and yellow and found the same colors on Adobe Illustrator.

Use of patterns was limited to four landuses in the two-hue map, because I didn't want to overwhelm the map with it having two different hues available in its shades also. Because of using only a limited amount of patterns, I chose not to use them for the major landuses such as industrial or commercial, otherwise the patterns would stand out too much in the overall balance of the map. Instead, I used the patterns for the landuses that had small areas that were scattered as much as possible around the map. Lastly, for the black-and-white map, I had to be creative about the use of patterns and choose patterns that were most differentiable from each other. (Regan, as you have mention, I should have chosen a different pattern for commercial land, but I had already exported it to AI and had spent too much time on it..) However, I realized that the combination of pattern and shade can also be used to create highly differentiable maps, not just the hues and shades. For example, diagonal lines with a white back ground was easily distinguishable from white lines with a darker background. Such combinations were fund to work with, and this was an easier map to create than the process to create a two-hue map. In the two-hue map, there were two seperate processes, first to choose the colors and its shades, and to integrate patterns to improve the map.

Overall, this was an interesting exercise to understand the use of colors and patterns to create a visually effective map.

Week 5:

Art Museums and Galleries near UCLA (Created with Googlemaps)

View Larger Map

Art Museums and Galleries near UCLA (Created by Geocoding)
Google Maps JavaScript API Example: Geocoding Cache
Go to:

I initially had some difficulties in working with the geocode-cache.html (though I figure it out later thanks to Regan counting my inconsistent number of brackets), so I created my first map with the mymap function. On the website, there is a tag called "my maps" next to the general search section. As long as you have an account with google, you can create your own map through this wizard provided. This was easier to work with than the geocode-cache.html, because it was more interactive and intuitive process to create a map than working with html codes. Adding markers, editing the info in the windows, and adjusting the zoom were able to be added to my map through this wizard. My map indicates six museums and art galleries locations near UCLA, with detailed information about address, admission cost, hours, website, and jpeg images of museums. The "My Maps" function also allows one to draw polylines and shapes to highlight certain streets or areas. So I created three rectangles that group the locations together in generally close approximation, and added transportation information.

I also added the second map that I adjusted from the geocode-cache.html. I learned a great deal about encoding for websites in general and how to work with googlemaps codes through this process. I had to change the placemarks section to change what information would appear on the pop-up windows when clicking on each location. I also had to insert the new coordinates (longitude and latitudes) of each location. Though this method was not as intuitive as the "My Maps" wizard, it allowed creators to add and edit codes to customize the map. In the "My Maps", once the map was converted to html codes, there was no additional changes that could be allowed to the map. Overall, this exercise truly broadened my horizon to understand the current cybercartography, and the endless possibilities of mashup ideas and development in the future.

Week 6: Final Assignment

This is a pdf version with better resolution.

For a final project, I created a recycling map of UCLA north campus. My initial motivation of this project was to create an easy, legible, and somewhat informative map that would promote more recycling on campus. Personally, I have felt the growing need of recycling with the environmental awareness, and saw that the UCLA waste and recycling management facility has had a website that aimed to inform the public. There was no specific map for locations of recycling on campus. Instead, I found the new Campus Map BETA (A new interactive map of UCLA campus), with an option to click on "recycling". The map then showed the recycling symbols on campus, which you could zoom in and out of, but I found various weaknesses of this map that could be greatly improved.

1. First, the background colors of this map was too strong, which hindered an effective ground-figure that could be more visually pleasing.
2. The symbols were too big in size, and many of them overlapped closely on a comprehensive map.
3. There was no specification of which type of recycling was being done in each location (Plastics/Glass/Aluminum, Mixed paper, or Recycling container). This information is important because as you can see on the map there is no specific pattern to how the different recycling bins are placed on campus.
4. There was no informative aspect to this map, because this was only a function of the whole interactive map.

To improve the on these aspects with the time allowed to complete this assignment, I decided to focus my map on the North Campus. I took an afternoon to walk around the campus with the map from campus map BETA, and found out that the map was not accurate. There were more recycling bins actually placed than indicated. So in my new map I updated more accurate locations of the recycling bins, as well as indicating specific type of recycling with different symbols. I simplifed the map by indicating the buildings and the major roads so the map will not be overly crowded. I also added an informative pie chart of how much waste was being recycled and how much was going to the landfill. For legend of types of recycling, I included real pictures of recycling bins to provide the readers clear visual information of how they look like on campus. I also included an inset to inform where the North campus is located in the campus. I paid much attention to the use of colors, in terms of combination and similarity, using the function online.

Overall, I believe I was able to use many skills and knowledge I acquired from the course to create an effective, informative, and visually pleasing map for students and staff to gain a quick insight into UCLA's current recycling system.