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Introduction to Choropleth Mapping

Introduction to Choropleth Mapping

OverviewThis article is intended to serve as a starting point for anyone trying to create choropleth maps. It outlines the numerous free methods for creating a dynamic map from a given dataset.

Choropleth mapping, or “heat mapping” is a ubiquitous element of our visual centric society. It is a method of visually representing data over an area. The most popular form seen today is the election map, where specific counties and/or states are colored to represent their selection of a candidate. Due to the inherent diversity of the United States, they have become a popular form of visualizing the geographic distribution of sociological data.

Until recently, choropleth mapping has been reserved for entities with large resources, that can spend significant amounts of money for software specifically designed for such mapping. Examples of this are Microsoft’s MapPoint or ESRI’s ArcGIS. However, with the advent of AJAX and the increasing popularity of publically accessible mapping software like Google Maps and Yahoo Maps, the costs and learning curve associated with choropleth mapping has virtually evaporated. For Professors, as well as students, data can now be mapped to create powerful visual statements.

Choropleth mapping isin a visualdynamic representationAJAX application operates in a very simple manner. Raw coordinates are fed into the application that specifies an overall shape. This shape is then applied with the appropriate color. The most critical elements are obviously the coordinates, and as such, they take up most of datathe overspace ain geographicmapping area.files. AThis goodproblem example wouldcan be thedealt 2004with Presidentialin Electiontwo Mapways, Here,storing the data, blue for democratic or red for republican is overlaidcoordinates on a mapdatabase, or storing coordinates in the generated file.

Due to the limitations of Google Maps, each of the Unitedfollowing States.

applications

Typically,have choropleththeir mapsown arestrengths createdand usingweaknesses. mappingThey softwarecertainly likelack Microsoftthe functionality of MapPoint or ArcGIS.ArcGIS, However, these programs have licensing costs and a significant learning curve. For simpler choropleth mapping tasks, particularlybut for students,more acasual solutionpurposes based on the Google Maps API is a good alternative. There were several options considered, one was to create a SQL database of shapefiles and overlay them on to Google Maps, a good example of this is Mapeteria. Therethey are somewell drawbacks to this approach. The first was the size of the overall application: converted shape files are quite large, and the database size will grow depending on detail. Another option was to keep a database of latitude and longitude specifying polygons. While not as accurate as shapefiles, the size of the database is more manageable.suited.

Color-It

One implementation in particular is

which was by Zonums Solutions. Color-It allows users to overlay region shapefile polygons over Google Maps. There are a few limitations to point out. Color-It uses a database to retrieve region divisions based on country. While the list is exhaustive, it is far from complete, so you may not find the country of interest. In addition, only one country can be mapped at a time, so you will not be able to compare one country to another.

To begin, you must select what type of coloring you want to perform. Color according to value will automatically select gradients between two colors and color regions based on the data values relative to the maximum and minimum values. Manual color selection will create a map that colors regions based on user input. Then select a country of interest from the list of countries sorted by continent.

Color According to Value

You will be presented with a table with all the colorable regions of a country and a corresponding data value. At this time, the data still needs to be entered manually, but offers the flexibility to easily manipulate data and change the map. If regions are missing data, you may also deselect regions by unchecking them in the table, Color-It will omit these regions. Once data is entered, you can select the colors for maximum and minimum values, the left color being the low value and the right being the high. You can also adjust the % opacity of the polygons as well as the width of the outline. Click on draw map to produce the choropleth map. If changes are required, you may adjust settings and click draw map again.

Manual Color Selection

This time, the data table will be replaced with an ellipsis button. Clicking on this button will bring up a color palette, where colors can be manually selected. The rest of the procedure is the same as Color According to Value.

Generating KML

For more detailed maps, Color-It also has the ability to convert your input into a Google Earth Compatible KML file. To perform the conversion, you can click on the generate KML file after clicking draw map. The file will be in KMZ (KML then ZIP) which you can extract into a KML file and open in Google Earth.

Mapeteria

While manually entering data does have the advantage of flexibility, it can become tedious when dealing with larger data sets. Mapeteria offers the ability to take a specifically formatted .CSV file and shade various geographical regions accordingly. The limitations are that currently Mapeteria only supports the United States, Canada and French Territories. We are currently working on expanding Mapeteria’s range.

Formatting .CSV

There is a strict format that .CSV files must come in. It is a three column table, the first having the ISO prefix for a certain country, i.e. United States is US. Next is the region prefix, California being CA. Finally, comes the value of interest. You don’t have to use a value for every region, just the ones you want shaded. Post this .csv file to a webserver and note the url so that Mapeteria can find it.

Options

There are options to divide your value of interest by the population or geographic area, and are generally useful for density studies. Otherwise, you may omit them. You may also specify what you want the maximum and minimum values to correspond to. This is really a function that adjusts shading contrast. If you find that a map isn’t shaded how you would like, you may change the max and min values to modify the shading.

Output

Finally, the output can be in both Google Maps web output or KML Google Earth. The polygons are generally quite demanding, so Google Maps output may take some time before it appears.

After participating on the Google Earth Community Forum, many users suggested that for educational purposes, Google Earth Pro will provide easy to use GIS and text data file import. Google Earth Pro normally retails for $400 however, Google has continued the Google Earth Education Initiative Program, which gives away Google Earth Pro grants for educational entities. I have contacted Debra Kettmann to see if SSC can obtain Google Earth Pro for educational use. This is a speculative play because there is little public documentation on Google Earth Pro, but the Educational part of the Community Forum suggests that it is essentially the standard version of Google Earth with additional data management functionality. I will keep an eye on this program and see what Debra responds.

Over Winter break, Google responded to my initial request to join the Google Earth Pro for Education Project. While I have played around a bit with the free trial of Google Earth Pro, it still has features like importing tabular data that are still locked in the trial. Google has offered the free use of Google Earth Pro for free for use in curriculums at UCLA. They have requested that we submit an application before we are given the full copy for evaluation.

Many Eyes

Of the many data presentations solutions I have researched and worked with,

  • Many Eyes holds by far the most potential. While not based on open source mapping format like Google Earth kml files, it is easy to overlook this because Many Eyes combines all the ease of use with data set input as Exhibit, and the large geographic database of Color-It. At this moment, Many Eyes supports only 14 different countries for specific region/province detail. Users simply have to create an IBM ID and start entering data or select from the large number of data sets that have already been uploaded by others. The interface is uncluttered, and easy to follow instructions are supplied for each step. There is even a screencast tutorial. The most intriguing function of Many Eyes is the ability to take data that has been simply copied and pasted into a text box and interpret it into full tabular data. I have yet to try this with large data sets. Another impressive feature is the ability to change how you visualize data simply by selecting a visualization type, there is no need to reformat data to suit the chart. My primary concern is still the fact that Many Eyes is not open source. IBM may in the future decide to turn Many Eyes into a profit bearing product, at which point, it would need to be licensed. I have contacted their main research developer, Matt McKeon, and I hope to find out from him how Many Eyes manages geodata and attempt to increase the number of countries available for visualization.

    Custom Solutions

    Yahoo Pipes

    YahooYahoo! Pipes offers an interesting alternative that may enable the integration of Color-It’s diverse KML generator and the flexibility of Mapeteria’s .CSV input. One major advantage to developing a system around Yahoo Pipes is the ability to take advantage of Yahoo’s Location Builder utility which uses Yahoo search to automatically look up the latitude and longitude coordinates. By doing this, the coordinate data does not have to be stored in the KML file. I have created a proof of concept of this: Mexican Migration.Mashup CSV File. Currently, .CSV files are simple to convert into location linked data through Yahoo Pipes, but the difficulty lies in integrating the KML output in order to achieve the desired polygon shading effects. Possible solutions to this are to use a large KML file with every region of interest defined, and applying appropriate polygon shading styles through Yahoo Pipes. Unfortunately, the size of the overall KML file may be prohibitive to this method, as unnecessary polygons would be loaded every time a map was created. This is certainly a work in progress, and updates will be shown here.

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