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Everything Sings: Maps for a Narrative Atlas by Denis Wood with an introduction by Ira Glass. Pub date: Nov. 12.
$28  .  Paper  .  112 pages  .  85 black and white illustrations, including more than 50 maps  .  ISBN: 978-0-9799562-4-9

Preorder

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These maps remind me of all the radio stories I love most. After all, most radio is a boring salaryman, waking up before you and me to announce the headlines or play the hits to some predetermined demographic. Yet some radio stories elbow their way into the world in defiance of that unrelentingly practical mission, with the same goal Denis Wood’s maps have: to take a form that’s not intended for feeling or mystery and make it breathe with human life. —Ira Glass, host of This American Life

Lukewarm off the presses, a tome chock full of lofty thoughts on maps and mapping. The blurb about Rethinking Maps, edited by Martin Dodge, Rob Kitchin, and Chris Perkins (Routledge 2009), sez:

Maps are changing. They have become important and fashionable once more. Rethinking Maps brings together leading researchers to explore how maps are being rethought, made and used, and what these changes mean for working cartographers, applied mapping research, and cartographic scholarship. It offers a contemporary assessment of the diverse forms that mapping now takes and, drawing upon a number of theoretic perspectives and disciplines, provides an insightful commentary on new ontological and epistemological thinking with respect to cartography.

A useful overview of what typically gets called “critical cartography,” with a few other voices of reason mixed in.

Denis Wood and I contributed a chapter, a comic with plentiful notes (for those who can’t figure out the pictures). I linked our chapter below, but it works much better as a printed comic.  I have about 10 paper copies, and can mail them to the first 10 people that email me (jbkrygier@owu.edu). Include a mailing address!

Debates rage, and tussles erupt, over the question…

Serious enough, I guess, to be included in a tome of high academic scribblings.

The editors have made the introductory and concluding chapters available as PDFs. Those too are linked below.

The book is expensive ($129.95!) and sales will mostly be to libraries. Check a copy out of your favorite library (or ask for it via inter-library loan) or email the author of a chapter you are interested in and ask if they are willing to share a copy.

Chapters in Rethinking Maps include:

1. Thinking about Maps (360k PDF) (Rob Kitchin, Chris Perkins and Martin Dodge)

2. Rethinking Maps and Identity: Choropleths, Clines and Biopolitics (Jeremy W. Crampton)

3. Rethinking Maps from a more-than-human Perspective: Nature-society, Mapping, and Conservation Territories (Leila Harris and Helen Hazen)

4. Web mapping 2.0 (Georg Gartner)

5. Modelling the Earth: A Short History (Michael F. Goodchild)

6. Theirwork: the Development of Sustainable Mapping (Dominica Williamson and Emmet Connolly)

7. Cartographic Representation and the Construction of Lived Worlds: Understanding Cartographic Practice as Embodied Knowledge (Amy Propen)

8. The 39 Steps and the Mental Map of Classical Cinema (Tom Conley)

9. The Emotional Life of Maps and Other Visual Geographies (Jim Craine and Stuart Aitken)

10. Playing with Maps (Chris Perkins)

11. Ce n’est pas le Monde [This is not the world] (2mb PDF) (John Krygier and Denis Wood)

12. Mapping Modes, Methods and Moments: A Manifesto for Map Studies (556k PDF) (Martin Dodge, Chris Perkins and Rob Kitchin)

When Bill Bunge mapped out the locations of car/pedestrian collisions in Detroit (Detroit Geographical Expedition, 1968) he and the map were advocating a way of thinking about what was happening to the black community in Detroit – and advocating for change.

All maps advocate.

To advocate means to “to speak or write in favor of; support or urge by argument; recommend publicly.” The word derives from the Latin advocate: “to call to one’s aid.”

What map does not advocate, or argue for something? We are always calling maps to our aid.

Three free books on maps and advocacy have been made available for download recently, and are worth a look.

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Two New PDF Books [added June 6 2009]:

Good Practices in Participatory Mapping (2mb PDF here, 2009). Published by International Fund for Agricultural Development.

A review of participatory mapping methods.

This report will review existing knowledge related to participatory mapping and recent developments. Specifically:

• Section 1 will define the main features of participatory mapping;
• Section 2 will discuss key applications of participatory mapping;
• Section 3 will present specific tools used in participatory mapping, including their strengths and weaknesses;
• Section 4 will identify good practices and explore the significance of process in participatory mapping initiatives.

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Toolbox & Manual: Mapping the Vulnerability of Communities (4.4mb PDF English version here, Portuguese version aqui, 2008). Published by Salzburg University Centre for Geoinformatics.

A overview of concepts and methods for community mapping, focused on vulnerability.

Within the research and project context it is aimed to provide the local communities with appropriate maps of their communities. The maps should enhance planning and decision making processes within the communities in regard to reduce local vulnerabilities and allow appropriate planning of disaster response measures. It is the first time in Mozambique that maps have been produced with such an accuracy (high resolution data) and for disaster risk management through the integration of participatory practices.

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Visualizing Information for Advocacy: an Introduction to Information Design (7mb PDF here, January 2008). Published by Tactical Technology Collective.

Succinct, well-designed, with many good examples of maps and information graphics for advocacy.

…a manual aimed at helping NGOs and advocates strengthen their campaigns and projects through communicating vital information with greater impact. This project aims to raise awareness, introduce concepts, and promote good practice in information design – a powerful tool for advocacy, outreach, research, organization and education.

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Maps for Advocacy: An Introduction to Geographic Mapping Techniques (3mb PDF here, September 2008). Published by Tactical Technology Collective.

A great overview of maps and advocacy with many examples and resources.

The booklet is an effective guide to using maps in advocacy. The mapping process for advocacy is explained vividly through case studies, descriptions of procedures and methods, a review of data sources as well as a glossary of mapping terminology. Scattered through the booklet are links to websites which afford a glance at a few prolific mapping efforts.

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Field Guide for Humanitarian Mapping (3.2mb PDF here, March 2009). Published by MapAction.

A textbook for using maps and GIS in humanitarian work.  The Guide provides detailed information on data collection (GPS) and the use of Google Earth and MapWindow (free mapping software).

The guide was written to meet the need for practical, step-by-step advice for aid workers who wish to use free and open-source resources to produce maps both at field and headquarters levels. The first edition contains an introduction to the topic of GIS, followed by chapters focused on the use of two recommended free software tools: Google Earth, and MapWindow. However much of the guidance is also relevant for users of other software.

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Some related resources:

• the Tutor/Mentor Collection’s GIS and Mapping Resources Page.
• slides & text from Erik Hersman’s Activist Mapping presentation at Where 2.0.
• the Atlas of Radical Cartography.
• Counter-Cartographies Collective & 3C’s Blog.
• An Introduction to Critical Cartography (176k PDF) by Jeremy Crampton & John Krygier (2006)
  
• “Protest Maps” (292k PDF) by Denis Wood & John Krygier (2009).
• Mapping: A Critical Introduction to Cartography & GIS by Jeremy Crampton (2009).

Making maps kills baby animals!

Ok, they are claiming the frightened yet adorable faun fawn didn’t die.

A car making images for Google Map’s Street View wacked a faun fawn in upstate New York.

…As some people have noticed, one of our Street View cars hit a deer while driving on a rural road in upstate New York. Due to several user requests using the “Report a concern” tool, these images are no longer available in Street View.

The driver was understandably upset, and promptly stopped to alert the local police and the Street View team at Google. The deer was able to move and had left the area by the time the police arrived. The police explained to our driver that, sadly, this was not an uncommon occurrence in the region.

No word yet if the faun fawn has contacted a lawyer.

Via The Daily What.

Drawing maps used to be a big part of the geography curriculum in the U.S. One guide for students, published in 1900, is Schutze’s Amusing Geography and System of Map Drawing by Lenore Schutze.  Tips for Africa, “The Skull” as Schutze sees it:

1. Cut a square into four smaller squares, and erase the southwest one.

2. Mark the cross-line from east to west, “The Equator.”

3. Draw Tripoli at the north of the division line from north to south, and Cape Town at the south end.

4. Locate the mouths of the Nile River west of the middle of the north side of the second square, and draw from them to a point north of the Equator, on the east side, and print “Cape Guardafui.”  Draw the Red Sea south of this line.

5. Draw from Cape Guardafuit to Cape Town, and print “Cape of Good Hope.”  Zanzibar, Pretoria, and Pietermaritzburg must be south of this line.

6. The west side of Africa extends somewhat above the north side of the first square, and does not quite reach the Equator.

7. Madagascar slants in about the same direction as the line from Cape Guardafui to Cape Town.

The entire page on Africa from Schutze’s Amusing Geography and System of Map Drawing (1900) p. 43 is below:

Map-making has often adapted technologies designed for purposes other than making maps.

I recall Scitex hardware as the state-of-the-art in large format color computer mapping in the early 1980s when I was first learning cartography. Cartography applications were developed when Scitex, its origins in designing and printing textiles, noticed “the similarity between printing large fabric surfaces and coloring topographic surfaces.” (PDF source).

Step back a few generations and we find the then ubiquitous typewriter adapted to making maps by DIY cartographers.

It is not difficult to find old DIY maps that used a typewriter to create type, like this 1950s map (below) of Camp Tonkawa in east Texas (source). This is a sketch map that was run through a typewriter for typographic annotations:

A more sophisticated DIY approach to typing maps was detailed by R. A. Daly in the March 1905 issue of the American Journal of Science. Daly describes a typewriter with special characters – examples shown in the graphic which heads this posting – for creating area patterns on maps:

It is safe to say that the majority of persons are seriously hampered in the preparation of text illustrations by the difficulty and expense entailed in the tedious drawing of map, section or diagram. Yet the desirability of greatly increasing the proportion of such illustrations in the thousands of scientific articles published each year is manifest. That clearness, precision and conciseness in the exposition of a theme are generally enhanced by the use of abundant, appropriate diagrams and maps is as evident as that the blackboard is the constant friend of the teacher.

Ideally, the author should himself be able to make the original drawing quickly, neatly and artistically. The usual execution of drawing with the pen is, to the average author, discouragingly slow and expensive, not always neat, and still less often artistic. The following note relates to some experiments made to increase rapidity and neatness in the production of line drawings by the use of a machine. Enough success has been attained to warrant the recommendation of the machine method to geologists, geographers, and others.

Recently the Hammond Typewriter Company of New York has constructed, for the Geological Survey Department of Canada, a typewriter provided with a carbon ribbon and with ninety special characters designed for the preparation of line drawings to accompany geological and geographical papers.

It is to be understood, of course, in the preparation of a diagram that an outline drawing is first prepared, and that the spaces thus formed are filled with the symbols shown in the legends, by means of the machine.

The earliest printed computer maps, such as the map below created with SYMAP software in the mid-1960s, used a line printer. Line printers were, more or less, a typewriter adapted to printing from a computer.

Computer output, on monitors and printers, was limited to typical typewriter characters – letters, numbers, and symbols such as + or = or %. These limited symbols could be used to create area patterns on maps. A modification of the line printer hardware allowed the overprinting of characters, the darkest being overprinted OXAV ranging down to a “-” for the lightest area pattern. The table below provides the overprint line printer symbols for a nine step range of grey tones:

The output was actually less sophisticated than the output from the 1905 map typewriter given the limited symbology of the line printer:

A recent book by Nick Chrisman called Charting the Unknown (ESRI Press, 2006) documents the early history of computer mapping and GIS at Harvard University’s Laboratory for Computer Graphics and Spatial Analysis, including the SYMAP software which produced the above map.

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Source of above quotes: “Machine-Made Line Drawings for the Illustration of Scientific Papers” by R. A. Daly. American Journal of Science, March 1905.

Source of Line Printer Symbols table: R. Mould and C. Wyld, “A comparison between line printer and conventional Polaroid gamma camera displays using a liver phantom. Off-line computer and contour mapping package.” Physics in Medicine and Biology, 18:1, January 1973, p. 88-99.

Google Earth can display geographic data with a time component, and thus show animated maps. Animated mapping has garnered much attention among cartographers in the last decade.

I created a few Google Earth animated choropleth (literally, area-filling) maps of population change in Ohio. One map shows total population by county from 1900 to 2006. The other shows percent population change from decade to decade. Details on how I created these animated maps along with links to the downloadable KMZ files are below.

In the most recent version of Google Earth (Mac 4.0.2736, Windows 4.1.7087), a “time slider” appears if a KML or KMZ file contains temporal data. For example, many GPS receivers can attach time to a recorded location. When formatted correctly, a series of points can be viewed as an animation in Google Earth, as in this example of a Whale Shark track [download kml]. More examples are in a list of the “Top 10 Time Animations from 2006 in Google Earth” and “Animation Roundup.”

I have not seen any animated choropleth maps in Google Earth. I have my students create animated choropleth maps in one of my courses at Ohio Wesleyan, and thought it would be swell if the students could display the animated maps in Google Earth. The entire project works well for an undergrad cartography/GIS course. Here are my two examples:

Download Ohio Population Change 1900-2006 (192kb kmz)
Download Ohio Population 1900-2006 (208kb kmz)

There are undoubtedly many paths to getting animated maps into Google Earth. I used Excel (to process historical census data), ArcGIS 9.2 to create the maps, and a utility to export from ArcGIS to Google Earth (Arc2Earth). No free software here, but you may be able to repeat the process using less cash-intensive software (and I will try to do so – in a future post). Also, the animations have a few flaws (the flash between maps, a few counties show up with no color, etc.) that I have yet to work out. But the animations work, more or less.

For more information on timestamps and timespans in Google Earth, see the tutorial “Adding Time as a Fourth Dimension.”

The process below will be detailed in my class lab notes here when I update them later this summer. The jargon below will make sense to those who use ArcGIS.

1. Get the historical population data, via the web: grab U.S. Census historical county population data (1900-90) and (2000-06) for your state.

2. Clean up the data in Excel: so it looks like the image below; then save as DBF4.

3. In ArcGIS: Add a map of U.S. counties (I use ESRI’s counties.shp), select your state, and save the selection as a new layer. Join your DBF4 file to your state, using the county fips codes (FIPS) as the common column.

4. Export your state layer (right mouse click on layer, data, export data). This extracts your state from the entire US shape file, and also combines your joined data: you cannot export an ArcGIS project with a joined table to Google Earth using Arc2Earth (step 9 below) [update: I have been told this bug will be fixed in the next version of Arc2Earth]. Add this layer to your ArcGIS project and delete all other layers.

5. Generate the population change data: in a new field, use the field calculator to determine the percent change from decade to decade. For 1900 to 1910:

( ( ( [ Y1910 ] – [ Y1900 ] ) / [ Y1900 ] ) * 100 )

where Y1900 and Y1910 are the names of the columns of total population for 1900 and 1910. Do this for 1910 to 1920, 1920 to 1930, etc.

6. Copy and paste this layer: create as many layers as you have data for: one for 1900-1910, one for 1910-1920, and so on. I did the same for the total population data (one layer for 1900, one for 1910, etc.) but in a second ArcGIS project file (so two ArcGIS mxd files, one for population change, one for total population). Derived data, such as percent change, is best shown with a choropleth map. Total numbers, such as our total population, are not optimal for choropleth maps because geographic areas vary in size (and thus there may be more of something in a geographic area just because it is larger). But Ohio’s counties don’t vary much in size, so we can map totals (and gaze upon the map, as should you always, with a critical eye).

7. Classify your data: If you want to compare a series of maps, you have to use the same classification scheme, that is, same number of classes and same breaks between classes. The bottom of the classification scheme must be the lowest value in all the years in your series, the top of the classification scheme the highest value. If you have negative and positive values (as with my percent population change data) 0 is a good break. Six or seven classes are a good default but you are certainly allowed more or less. Create a second classification scheme that fits your total population data (in your second ArcGIS project file).

8. Choose colors for the maps: Choose an appropriate color scheme (color value is best). If you have negative and positive values use a double-ended color scheme (as in my percent population change example above). I made the county borders white, and 3 points in size. It looks bad in ArcGIS but good in Google Earth (always design for the final medium). ArcGIS allows you to set the classification scheme and colors in one layer and import them to another layer. This saves you from re-typing the custom classification scheme on each layer.

9. Export to Google Earth using Arc2Earth: While there are several free software packages that convert ArcGIS data to Google Earth data, Arc2Earth was strongly recommended to me (and was affordable, at least for my non-profit college). Arc2Earth operates from within ArcGIS. When you export the whole map, you have a series of options. I chose not to have a legend floating near the map itself (the legend does carry over to the Google Earth Places panel) and left the other settings at default. Select a specific layer and hit the time data tab. I applied a time value to the entire layer: so population change 1900-1910 is set as in this image:

Adjust the time settings in subsequent layers (change 1900 to 1910 and 1909 to 1919 for the 1910-1920 layer, etc.). Hit export.

10. Open the files in Google Earth: when you open the files, you should see the time slider:

You probably want to slow the animations down: hit the clock icon (on the left side of the time slider) to set options, including animation speed. You can hit the play button and watch the entire series of maps, animated, or grab the slider bar and move through the layers yourself.

The flashing of the animation is distracting, but that might disappear if overlapping time spans are imposed on each layer (something I will experiment with). Also, the time slider is broken down by month, implying a monthly resolution of time data rather than the decade resolution of census data. There are certainly a myriad of other details – why a few counties dropped out when exported from ArcGIS, how well colors are maintained from ArcGIS to Google Earth, where best to place a legend (on the map or in the Places panel), how to use placemarks and overlays in addition to the animations, etc. But it is great to be able to view animated maps in Google Earth.

I am hopeful that the diversity of ideas about animated maps and animated map types cartographers and others have generated over the last decade will translate into Google Earth.

Update: the GeoChalkboard Blog has a related tutorial entitled “Creating Google Earth Time Display Data with ArcGIS.”

Lets look at a site that has been around awhile: The Modern Language Association’s Language Map. The site allows you map language data collected in the 2000 U.S. Census. A nice focused site with interesting data (I use it in my classes and the students enjoy pondering the patterns): here is the default map of the total number of language speakers in each county:

The basic language map allows you to view 33 different languages, mapped by county in the U.S. The total number of people who speak a particular language (above) can be mapped, but mapping totals can be deceptive, as the sizes of the counties vary. Thus a county may have more speakers of a particular language just because it covers more area than a smaller county. To account for these variations in county size, map the data as a percentage (the percent of people in a county that speak a particular language, see below). But you can map totals and there are sometimes good reasons to do so. Just realize the potential limitations of what you are seeing.

The basic map also allows you to map the data by state or zip code, and to add additional information (cities, roads, county & state names, etc.). The basic map does not allow you to change the classification scheme, and the arbitrary classification schemes the map uses are weird (but probably chosen so different maps can be compared to each other). Different classification schemes will produce different patterns, so take the patterns produced on these maps with a grain of salt: they will change if you (could) change the classification scheme. It would be also good to flip the legend, putting higher numbers (high =more) at the top of the legend, and lower numbers (low=less) at the bottom.

Here is the % by county map of the same data:

The symbolization of the county (or state or zip) boundaries on the map is annoyingly prominent. One of the Six Fancy Ideas (future post!) I took from Edward Tufte’s first book (The Visual Display of Quantitative Information, 2001) is to remove or minimize non-data ink, or, in this case, less important data-ink. This is a version of the old cartographic adage about visual hierarchies: stuff on your map that is more important should jump out, and stuff that is less important should fall back. The county boundaries (in gray) are so prominent that they obscure the data in smaller counties on the MLA map (at a national scale) and are certainly overly noticeable at all scales. Why not just make the boundaries white, and as fine as possible, so we can see the most important part of the map, the language data?

The map projection (the manner in which the surface of our 3D earth is flattened to 2D) is the plate carree, a typical default for web mapping software. Unfortunately, the plate carree distorts area (as you move north) thus this map projection is distorting the data. Dammit! Counties and states in the north are bigger than they should be in comparison to the counties and states in the south, which may distort your interpretation of the area patterns on the map.

Finally: map crap alert! Why include a north arrow when the vast majority of map viewers will recognize the U.S. and that north is up is? Why a scale bar showing 838 (?!) miles? Zoom in and you get 419 or 209 miles. Is anyone ever going to need to make measurements on this map? And the plate carree projection distorts distances anyway.

So: a decent, focused and useful site that could use a few tweaks. The MLA site also allows you to compare two language maps and play a bit with the data (in the Map Data Center).