While a lot user-generated content on Google Maps may seem to suffer pushpin fever, the tool can be purposed for nicer cartographic uses than maps of giant martini glasses, musical notes, and eight-balls. Google base maps can serve as an easy reference for accurately creating custom points and shapes, but may be too noisy for professional, published maps. Luckily, My Maps allows you to export your data to KML which can then be loaded into your handy web-based cartography application, indiemapper!

In this post is an example of how My Maps might be used for a basic overview map of America’s most famous road, Route 66.

Google Maps

Manually drawing Route 66 would be a tedious task with an awful lot of clicking. Google offers a huge advantage by allowing you to create a line that follows roads, using its routing algorithms. Route 66 roughly follows modern interstates from Chicago to Los Angeles. Google wants to use a different route directly between the two cities, but an intermediate click around Albuquerque ensures that it’ll follow the correct southern route.

My final map is meant to appear at a fairly small size, perhaps the width of a couple of columns in accompaniment of a newspaper article. As such, minor deviations of the interstates from Route 66 are not of much concern because of the small scale. However, in certain spots where the difference is notable, such as in western Arizona, I can click and drag the route to conform to the correct road.

Besides the actual path I’ll want to indicate some of the larger cities along Route 66 using basic placemarks. It would be okay to use crazy helicopter or snowflake icons here, but that garish fun won’t be carried over to indiemapper.

That’ll do for now. To export to KML, I save the map and click the “View in Google Earth” link. The KML file that is generated actually only contains a “network link” to a location on Google’s servers. In my experience this means that loading this KML file will always show the latest version of the map as saved on My Maps, no matter when the file was downloaded.

Indiemapper

As the KML from Google Maps will only contain the custom point and line data that I created, my indiemapper map will need a base map. Natural Earth Vector data from indiemapper’s shapefile library is perfect for the job. I’ll add countries, states and provinces, and lakes and reservoirs.

Then after loading the KML and a bit of styling work, everything is in place.

Everything, that is, except labels. I want city and state labels. After choosing to add a layer in the usual manner, the label options for the KML data source are two. name_kml is the titles of lines, placemarks, and shapes—in this case, the cities. Note that the only choices in this panel are for labels and reference layers. For most other data sources there would be options for single and multivariate thematic layers. KML exported from Google Maps contains only text attributes and no numeric values on which to base any thematic layers.

After adding labels for NAME on the States and Provinces layer, I edit the styles and placement of all the labels in the page. I’m going with the Geochet (Georgia + Trebuchet) template for the city and state labels. I don’t need the “Route 66″ label that appeared for the line because that will simply be the title of the map, so I can just drag it off the page and out of view, using the Annotation layer for the title instead.

There. A very simple overview map of Route 66. If you’d like to investigate further, check out the IMP file for this map, the KML source, or the original data in Google Maps.

Final thoughts

Google My Maps tools are geared toward miscellaneous features with names and descriptions, and it is difficult to organize this map data into real thematic content that taps into the strengths of indiemapper. However, Google Maps is ideal for generating simple geodata quickly. I think of two sides to the way indiemapper and Google Maps can work together: Google Maps is a way to add custom data to indiemapper, and indiemapper is a way to add certain custom styles to Google Maps data. For the former, KML from Google Maps may not provide sophisticated thematic data, but it’s great for easily creating ancillary information or features for very simple maps. As for the latter, indiemapper’s built-in reference and thematic data, as well as its projection and export capabilities, offer an alternative base style to Google base maps which are not suitable for every purpose.

When you load indiemapper, you’ll notice a new tab on our open screen:

This tab will take you to our new data library, populated with thematic data from the UNEP Geo Data Portal. We’ve assembled the data into 10 major themes. Within those themes are attributes described in the detailed section. To get the data into your map, just select your theme and click “Open.”

If you’d like to browse all the data themes and attributes at once, have a look at our Google Spreadsheet data inventory. We’ll be adding more data over time so check back often. If you have a suggestion about what we should add, you can submit a request by emailing support@indiemapper.com.

Bonus Map

Just for kicks, I took 3 minutes and threw together this bivariate choropleth map showing CO2 emissions per GDP and GDP growth rate. Look at all the low-emissions growth in South America and Africa compared to North America. Europe’s economy isn’t growing, but they’re not creating much CO2 either.

Want to make your own modifications to the map? Download the IMP.

Indiemapper was born in the classroom based on a simple, shared frustration: Why is it so hard to make good maps? While GIS is very powerful, it easily overwhelms students who often waste precious time hunting for buttons and forgetting how to do simple tasks. All of us at Axis Maps have extensive experience in the classroom; This is the tool we always wished we’d had to teach map-making to our own students.

Fall 2010 we’re offering instructors who want to use indiemapper in their classroom ready-to-go labs, sample data sets, and video tutorials so your students can hit the ground running. This is in addition to the academic discounts we already offer. Plus we are offering a free account for instructors who use indie in their classes. For more information go to http://educators.indiemapper.com/ or send an email to education@indiemapper.com to find out how you can begin using indiemapper in your classroom.

DOWNLOAD: Choropleth Maps Sample Lab Exercise (5.4 MB PDF)

OR

Complete Lab + Data (7.8 MB ZIP)

and like this (capacity of ethanol facilities across the US):

The Good:

1. This data was publicly available and easily searchable.
2. I made each of these maps in about 2 minutes.

The Bad:

1. Wrong projection for choropleth map
2. On the proportional / colored symbol map, a single variable is being redundantly encoded in both size and color.
3. Single color scheme
4. I can only set the extent by typing the name of a country in the text box

I understand that for many people, this tool gives them mapping ability that they didn’t have before. But if you care about having attractive and correct maps, it doesn’t go nearly far enough.

I’m going to do a quick reproduction of each of these maps in indiemapper, and in the process, show you how you can take advantage of the great data in Google Fusion Tables and still make great maps using indiemapper.

Google Fusion Table Basics

Google Fusion Tables are dead simple to use, so I won’t spend too much time on this. First, head over to http://tables.googlelabs.com/ to see what’s there.

• You can upload your own data by clicking “new table”
• You can browse a ton of publicly available data by clicking “public tables”
• You can search for a specific dataset by typing into the search box

Like I said: dead simple. To get a more in-depth tour, visit Google’s own overview here -> http://tables.googlelabs.com/public/tour/tour1.html

US Facebook Participation

The first table I found was Percent of state population on Facebook (2009). To get the data into indiemapper, I’m going to have to combine the tables. Fusion tables do have some geographic export abilities, but it will only export points and I want to attach this data to state polygons. I can export the data by going to File->Export and my CSV will automatically begin downloading. For my geography, I grabbed a states file that also had some census data (in case I wanted to do some bivariate maps).

I did the standard tabular combine process in OpenOffice as described in this post. A few things to note:

• My Facebook data didn’t contain any values for the District of Columbia. I had to add an extra row of zeroes to make sure the data would match up.
• I had to do a find / replace to remove all the commas and %’s in the data so indiemapper would recognize the values as numeric instead of text.

You can download the final combined shapefile here -> http://indiemapper.s3.amazonaws.com/data/facebook_states.zip

I loaded the file into indiemapper and made a simple choropleth of percent of population that is registered for Facebook. I projected the map to Albers Equal Area Conic centered on 100°W. Then I created a choropleth map of the percentage values, just like in Fusion Tables. Finally, I added a label layer and did some quick adjustments to label placement and rotation. After about 3 minutes of work, it looked like this:

Download the IMP

Since I had the census data attached to my shapefile, I thought I would make a bivariate choropleth, just for kicks. Since Facebook used to be the domain of college students alone, I thought I would compare the number of Facebook users to the rate of 18 – 21 year olds in each state. I added the bivariate cartogram layer and adjusted some of the overlapping states to come up with:

Download the IMP

Ethanol Facilities

Google Fusion Tables include a fairly robust geocoding feature, so I wanted to test it on data that was made of discrete points. This dataset shows the location of ethanol facilities along with their capacities. From the table, if I go to Visualize -> Maps, there is a link to export the KML.

I thought I would be able to take this exported KML and use it directly in indiemapper, but unfortunately, I was wrong. The exported KML handled the geography perfectly, however, it did not maintain any numerical data for me to use. I won’t go into too much detail other than to say, the KML data looked like this:

<description>
   <![CDATA[
      <b>Longitude</b>: -103.334403992
      <b>Latitude</b>: 34.1861915588
      <b>Company</b>: Abengoa Bioenergy Corp.
      <b>Address</b>:
      <b>City</b>: Portales
      <b>State</b>: NM
      <b>zipcode</b>:
      <b>Company Website</b>:
      <b>Feedstock</b>: milo
      <b>Status</b>: Not Producing
      <b>Capacity [Mg/y]</b>: 30
      <b>State Date</b>: July 2005
   ]]>
</description>

when it should look like this, as described in the KML reference:

<ExtendedData>
   <Data name="longitude">
      <displayName><![CDATA[Longitude]]></displayName>
      <value><![CDATA[-103.334403992]]></value>
   </Data>
   <Data name="latitude">
      <displayName><![CDATA[Latitude]]></displayName>
      <value><![CDATA[34.1861915588]]></value>
   </Data>
   <Data name="company">
      <displayName><![CDATA[Company]]></displayName>
      <value><![CDATA[Abengoa Bioenergy Corp.]]></value>
   </Data>
   <Data name="address">
      <displayName><![CDATA[Address]]></displayName>
      <value><![CDATA[ ]]></value>
   </Data>
   <Data name="feedstock">
      <displayName><![CDATA[Feedstock]]></displayName>
      <value><![CDATA[milo]]></value>
   </Data>
   <Data name="status">
      <displayName><![CDATA[Status]]></displayName>
      <value><![CDATA[Not Producing]]></value>
   </Data>
   <Data name="capacity">
      <displayName><![CDATA[Capacity (Mg/y)]]></displayName>
      <value><![CDATA[30]]></value>
   </Data>
</ExtendedData>

Since I was only looking for a single numerical value (capacity), I did a quick find / replace to only get the single value. You can download the edited KML file here.

Once I was finally in indiemapper, I wanted to make a quick map. First, I added the Facebook shapefile from the original example. It will be a good basemap showing states and maybe I’ll want that census data in there too. Then, I added the KML data and created a proportional symbol map from the “Capacity” variable.

The map looks good but I think there is more to the story than just this. I will use that census data to create a quick choropleth map of crop acreage and add that under the proportional symbols.

Download the IMP

Now we have a better picture of not only where the ethanol facilities are in the US, but also one possible explanation of why they’re there.

Conclusion

When I started this post, I had hoped that Google Fusion Tables were going to play nicer with indiemapper. While I think the redesigns are a massive improvement over the map visualization built into Fusion Tables, the inability to export usable KML is a major problem. While you still may want to take a look if you’re looking for publicly available data, if it is going onto a map, I would check Geocommons first to see if it is in a usable form.

I have a confession to make: I don’t make as many maps as I used to. My role in Axis Maps usually has me leaving the mapping to our talented designers and developers while I scurry off to do business-y things. I wanted to get back into the swing of making some maps so I thought I would try my hand creating a wrap-up of the 2010 UK election. I posted the IMPs with each map if you want to download my maps and make your own versions!

Full disclosure: I’m American but Britain is my adopted home. I apologize in advance to any UK natives for any inaccuracies resulting from my cursory knowledge of your political system. Let me have it in the comments!

Preparing the data table

My first order of business was locating the election data. I initially started looking for a KML or shapefile containing the election data. However, 3 Google searches later, it looked as if that was a pipe dream. However, what I did find was a VERY complete election table from The Guardian’s Datablog. You can see and download the full spreadsheet on this Google Doc.

The spreadsheet was very complete, but the way it was organized was going to be a problem for getting it on a map. Each party candidate for each constituency was given its own line in the spreadsheet.

Because I am going to be attaching this spreadsheet to geographic data, I needed to alter the layout so there would only be one entry for each constituency. Party information that was currently stored as individual rows would need to be translated into columns. I created a Pivot Table in Excel with constituency in rows and parties in columns. The table has records for 136 registered parties for the UK so I limited the table to the 3 major parties (Conservatives, Labour and Liberal Democrats). For the values in the table, I used number of votes and percentage of votes.

With the pivot table made, I pasted the data out of a pivot table so I could do a couple more calculations using the actual values. I grouped all of the other parties into their own group, copied information about the winning MP over from another table. Finally, I created four columns that only displayed the winning percentage if that party’s candidate won in that constituency (hopefully you’ll see why later). Now I have a final spreadsheet that is ready to get attached to some geographic data.

Getting some geography

After a quick Google search, I located the boundary shapefile I was looking for at data.gov.uk. You can download the file here: http://data.gov.uk/dataset/os-boundary-line. The constituency file comes bundled with lots of other boundary files that I’ll keep around in case I want to add it to my map later as context. A quick look at the data shows:

The data could definitely use some generalization, especially to clear up some of the denser constituencies around London and Birmingham. With Mapshaper, it will be about a 5 minute task. I uploaded the shapefile and generalized to 95% using the special Visvalingam method. Things look much cleaner and I reduced the file size of the .SHP from 68.4MB to 246KB.

Now I have to attach the table I created to the DBF associated with the shapefile. This requires OpenOffice (free download) since Microsoft Excel no longer has support for opening / editing DBF files. I opened both westminster.dbf (this is the DBF file that is part of the downloaded constituency shapefile) and uk_election.xls (the spreadsheet I created of election data) in OpenOffice. I sorted both tables by constituency name and pasted values from the election spreadsheet into the constituency DBF.

Note: At this point, it is very important to make sure your numerical values are stored as numbers instead of as text. Most spreadsheet programs align numbers to the right side and text to the left. If your numbers are stored as text, indiemapper will interpret them as any other kind of text and they will be available for labeling only.

I then ran a quick visual check to make sure the columns were lined up properly, comparing the constituency names from the DBF to the ones brought in from the DBF. I found a couple of discrepancies where my spreadsheet had something like “Yorkshire East” and the DBF had “East Yorkshire.” Doing a quick search through all the cardinal directions got this fixed pretty quick. I saved the DBF and now it was ready to be brought into indiemapper.

Making a map

I loaded my data into indiemapper and pretty quickly knew the map I was going to make. My idea was to create a proportional symbol map of the winners for each constituency where the size of the symbol was representative of their margin of victory. Since I was going to show each party using their respective colors, I was going to need separate proportional symbol layers in my map (which is why I divided the winning party values into different columns). Because each proportional symbol layer was coming from the same data source, I only needed to load in my shapefile once and then I could spawn each new proportional symbol layer from it.

With each layer created, I colored each one by political party and made sure they were classified and sized identically. I used made 3 classed symbols and set the bottom filtering control to 30% to remove all the zero values (where that party didn’t win). I made the other two class breaks at 40% and 50%. After adding transparency and stroke, I ended up with a map that looked like this:

I was pretty happy with it but knew it could use some work. So I called in some colleagues to help me out with the map.

Collaboration

I wanted to get some other people to take a look at my map. I went to My Indie page and invited Mark as a collaborator. This would enable him to see my map and make whatever changes to it he thought it needed.

When I clicked submit, Mark was automatically sent an email that gave him access to my project. I also turned on project notifications on the history page so if he commented on my map, I would be notified by email. When Mark threw down a comment, I was notified and I went to the history page to check it out.

He made a good point. I made a few quick styling changes to my map to bring the dots into the forefront, added a title, fixed my extent and I was done! Download the IMP and make your own edits…

Bonus Map

The coalition government between the Conservative and Liberal Democrat parties has faced no end to post-election dissection. No ink has been spared asking if a party from the right could work with a party from the left and if it actually represents the British people. I put together a quick bivariate choropleth map comparing the percentage of Conservative votes to the percentage of Liberal Democrat votes in each district. The blue areas are high Conservative but low Lib Dem; the areas of orange are high Lib Dem but low Conservative. The areas of “Brown” (ironically enough) are relatively high percentage for both are are the most aptly represented by the Camereon – Clegg coalition. Download the IMP and make your own edits…

Since launching indiemapper, a lot of you have asked: “How do I map my own spreadsheet data?” We are currently working on building this functionality right into indiemapper. In the meantime, here is a simple workaround so you can start mapping your data right away.

This article is reprinted from the indiemapper help website. You can access this article and many others at http://support.indiemapper.com/forums. If you’re looking for additional help or more tips and tricks, you can always email us at support@indiemapper.com or drop by our office hours on Tuesdays and Thursdays.

If you have thematic data in a spreadsheet (*.csv or *.xls) and want to map it, you’ll first need to join it to an existing data source and then load it into indiemapper. In the example below, we’ll join data from a CSV file to an existing DBF (*.dbf) file. DBF files contain the thematic data that is associated with the geographic features in Shapefiles.

1. Get OpenOffice at http://www.openoffice.org
We use OpenOffice (Calc), but any spreadsheet editing program that can open and save DBF files will work.

2. Open the existing DBF in OpenOffice
Here, we’ve opened a Natural Earth DBF downloaded from Natural Earth:
attachment: [50m-admin-0-countries.dbf]

It comes with the following Shapefile:
attachment: [50m-admin-0-countries.shp]

The DBF already has three columns in it for country, feature class, and sovereign nation.

3. Add new columns and column names to the Natural Earth DBF
This is where your thematic data will go in step 5.

4. Grab some thematic data at the country level
We found some free data at the CIA World Factbook on population, internet users, and internet hosts and converted it to CSV (comma delimited *.csv file) for use in Open Office .

attachment: [rawdata_2119_POP.csv]
attachment: [rawdata_2153_USERS.csv]
attachment: [ rawdata_2184_HOSTS.csv]

5. Open the World Factbook files in OpenOffice and copy+paste the cells into the empty columns you created in step 3
Be sure to match up the data correctly – to do this easily, both DBF and CSV should have one column in common. Here, both datasets have a column of country names.

Note: This step can be labor intensive, depending on the number of rows of data you have and because sometimes the two datasets do NOT match up perfectly. In this example, although both datasets have a country name column, the rows differ. For example, the World Factbook file has some countries (e.g., Akrotiri) that are not in the Natural Earth DBF, and vice-versa.

6. Save the DBF
Here is the newly joined data:

attachment: [50m-admin-0-countries_internet.dbf]

7. Launch indiemapper and open the Natural Earth Shapefile (see file above) along with your newly joined DBF
The file names do not have to match. Your new thematic data (from the CSV) will appear in the attributes list when you click on the orange plus button to add a new layer. You are then ready to make your map.

Open the SHP + DBF:

Review your new attributes in the list:

Make your map:

However, we understand that with the current expectations towards web-based software, we cannot make indiemapper an all-or-nothing proposition. For many of our users, indiemapper exceeds their needs or their budget while others may be waiting for a specific feature before they can fully adopt the software.

Therefore, today, we are launching indiemapper lite, a stripped-down version of indiemapper, available free of charge. If your account expires and you have not subscribed to indiemapper, you will automatically be downgraded to indiemapper lite. You can still access the application with your current account at http://app.indiemapper.com. You’ll recognize the same indiemapper UI, however you’ll notice that much of the functionality has been disabled. Saving is disabled and you will only be able to export to a limited size PNG / JPEG. You will be limited to univariate maps, 2 projections and manual labeling. Your current project and data will remain securely stored on our servers and will be immediately available if you choose to subscribe. See the table below for the full differences between indiemapper and indiemapper lite.

As always, please let us know about your experiences with your first 30-days of indiemapper by emailing us at support@indiemapper.com or by visiting our support site or forums.

However, we want to offer more conversational support for our users so we have decided to offer indiemapper office hours.

UPDATE: Indiemapper office hours will no longer be held on a regular schedule. However, someone will be in there to take your questions during regular business hours.

What can we talk about?

You can ask questions about indiemapper features, make a pre-sales inquiry, suggest a feature, lodge a complaint, offer praise, share ideas, discuss mapping issues, or talk about good or bad experiences using indiemapper. Whatever it is, we’ll be happy to chat and help in any way we can.

How do I get in?

During office hours, you can access our chat room from our support site or directly by visiting http://axismaps.campfirenow.com/34975.

We really hope that this is the start of a great conversation. See you Tuesday!

For the full post and lots of other great posts on cartography and information visualization, please visit: http://indiemaps.com/blog/

A little history

Indiemapper took a long time coming. The seeds were planted in December 2007. I had just discovered Edwin van Rijkom’s AS3 SHP library, which lets you load and draw ESRI shapefiles at run-time in Flash. Using widely available formulae for simple projections like Mercator and Lambert conformal conic I began loading and projecting shapefiles in Flash at run-time pretty quickly. These were heady times, and this seemed pretty cool.

Andrew “Woody” Woodruff joined in and we set off to create a full-fledged thematic mapping tool in Flash. We designed the product for ourselves, honestly, and the cartographers we knew. We hoped it’d be useful to other map-makers, whether casual or professional, who may not need nor want to learn the extensive analytical capabilities of a modern GIS, but do want a multitude of symbology and design options for their geographical data.

We presented a super-early version of indiemapper to MACDAD on May 9, 2008.

As you can see, the basic workflow and trademark indie (#0099cc) blue were already in place.

We had some pretty gnarly styling panels, though; at this point we were just working in Flash and creating all the panels from scratch.

Of course things like getting Master’s degrees, real paying projects, moving, and having actual jobs (however briefly) got in the way, and development on indiemapper didn’t restart for another year or so. Axis Maps (where Andy became a partner in Summer 2008) took up development of indie while I went and did something else for a while. Axis Maps released indieprojector as a preview in May 2009, not realizing it’d be another 11 months before the full thing was ready. I joined the team later in 2009, and have been co-developer (with Andy) since.

Development

Mark and Ben are our static and interaction designers here, with Mark also providing the “learn more” content, drawing from his years of academic cartography experience. Dave is our project manager, marketing guru, and AJAX guy; he created the backend to our user management and sharing systems.

Andy and I both wrote AS3 code and MXML markup, but he was mostly focused on the former with me working more on the latter. This meant I programmed more of the framework and UI, while Andy was rocking the math-heavy projections work and all the exporting/imp/svg stuff.

When I joined the company, I immediately set to work refactoring the indiemapper code base to incorporate the MVC framework Mate. Mate, as they say, is “a tag-based, event-driven Flex framework”. I had to use Cairngorm for work a while back, and by comparison Mate is quite lightweight and unobtrusive. There’s much more to say here, but I’ll save that for later.

Though it’s old school what with FXG, I still really like Degrafa, and used it a fair amount for skinning. Aside from Mate, Degrafa, and a few open source Flex components, we pretty much wrote our own little AS3 GIS SDK.

This is just the beginning

Given our platform and development philosophy, we can quickly respond to our users’ needs in a thematic and reference mapping tool. Please let us know what you want.

I think our first goals are:

• performance improvements so you can load larger geodata files faster
• attribute editing and joining
• more charting options for your data as an aid to classification and symbology selection
• more symbologies, like chorodot and additional cartogram styles
• custom choropleth color schemes and graduated symbol size schemes
• line generalization

But let us know what else you’d like to see. We’ve already been able to respond to a few new feature requests and, oh, maybe one or two bugs in our first week.

…a map of Hurricane Gustav showing its path and wind speed, 25 August – 2 September 2008. The reference map data, including bathymetry, is from Natural Earth.