© AP Photo/The Australian Transport Safety Bureau
KRISTEN GELINEAU, Associated Press
SYDNEY — After a four-month hiatus, the hunt for Malaysia Airlines Flight 370 is about to resume in a desolate stretch of the Indian Ocean, with searchers lowering new equipment deep beneath the waves in a bid to finally solve one of the world’s most perplexing aviation mysteries.
The GO Phoenix, the first of three ships that will spend up to a year hunting for the wreckage far off Australia’s west coast, is expected to arrive in the search zone Sunday, though weather could delay its progress. Crews will use sonar, video cameras and jet fuel sensors to scour the water for any trace of the Boeing 777, which disappeared March 8 during a flight from Kuala Lumpur to Beijing with 239 people on board.
The search has been on hold for months so crews could map the seabed in the search zone, about 1,800 kilometers (1,100 miles) west of Australia. The 60,000-square kilometer (23,000-square mile) search area lies along what is known as the “seventh arc” — a stretch of ocean where investigators believe the aircraft ran out of fuel and crashed, based largely on an analysis of transmissions between the plane and a satellite.
Given that the hunt has already been peppered with false alarms — from underwater signals wrongly thought to be from the plane’s black boxes to possible debris fields that turned out to be trash — officials are keen to temper expectations.
“We’re cautiously optimistic; cautious because of all the technical and other challenges we’ve got, but optimistic because we’re confident in the analysis,” said Martin Dolan, chief commissioner of the Australian Transport Safety Bureau, the agency leading the search. “But it’s just a very big area that we’re looking at.”
That area was largely unknown to scientists before the mapping process began in May. Two ships have been surveying the seabed using on-board multibeam sonar devices, similar to a fish-finder. The equipment sends out a series of signals that determine the shape and hardness of the terrain below, allowing officials to create three-dimensional maps of the seabed.
Those maps are considered crucial to the search effort because the seafloor is riddled with deep crevasses, mountains and volcanoes, which could prove disastrous to the pricey, delicate search equipment that will be towed just 100 meters (330 feet) above the seabed. Two of the search ships will be using underwater search vessels worth around $1.5 million each.
“You can imagine if you’re towing a device close to the seafloor, you want to know if you’re about to run into a mountain,” said Stuart Minchin, chief of the environmental geoscience division at Geoscience Australia, which has been analyzing the mapping data.
The terrain isn’t the only challenge. The area is prone to brutal weather, and is so remote that it takes vessels up to six days to get there from Australia. Water depths are also tricky: They range from 600 meters (2,000 feet) to 6.5 kilometers (4 miles). That’s about the deepest the sonar equipment can go, Dolan said.
“In all sorts of ways we’re operating towards the limits of the technology that is available,” Dolan said.
With the mapping nearly complete, the GO Phoenix, provided by Malaysia’s government, will begin hunting in an area considered the likeliest crash site, based on an analysis of satellite data gleaned from the plane’s jet engine transmitter and a series of unanswered phone calls officials on the ground made to the plane.
The other two vessels, the Equator and Discovery, provided by Dutch contractor Fugro, are expected to join the hunt later this month.
Malaysia and Australia are each contributing around $60 million to fund the search.
The ships will use towfish, underwater vessels equipped with sonar that create images of the ocean floor. The towfish, which transmit data in real time, are dragged slowly through the water by thick cables up to 10 kilometers (6 miles) long. If something of interest is spotted on the sonar, the towfish will be hauled up and fitted with a video camera, then lowered back down.
The towfish are also equipped with sensors that can detect the presence of jet fuel, although that would likely be a longshot.
David Gallo, who helped lead the search for Air France Flight 447 after it crashed in the Atlantic Ocean in 2009, said that even if the fuel tanks had survived the impact, strong currents in the search area probably would have dispersed any leaking fuel by now. Still, he said, it’s worth a try.
“In some of the steep rugged areas any kind of additional information would be useful to help peer into the dark shadows,” Gallo, an oceanographer with the U.S.-based Woods Hole Oceanographic Institution in Massachusetts, said in an e-mail.
There will be between 25 and 35 people on each ship, and crews will likely work around the clock. The ships can stay at the search site for up to 30 days before they must head back to shore to refuel and resupply.
“The most efficient way is to keep going,” Dolan said. “But you have to be careful with the well-being of your crews, to be sure you’re not pushing them too hard.”
The work will be painstaking. The ships can move no faster than 11 kph (7 mph) while towing the sonar equipment. If a vessel needs to change direction, the crew must first pull the towfish up enough that it won’t fall to the seafloor during the turn — a process that takes hours.
“None of this happens very quickly,” Dolan said.
Irene Burrows, whose son Rodney Burrows was on board Flight 370 with his wife, Mary, believes the plane will be found. Not knowing her son’s fate has made moving forward a near impossibility.
“We’re in limbo,” she said. “It will be good to know where it is — I think that’s what is important to all the family.”
Search officials are acutely aware of the sentiment.
“We’re doing this primarily because there are families of 239 people who deserve an answer,” Dolan said. “We will give it every possible effort and we think our efforts will be really good — but there’s no guarantee of success.”
The other day on Twitter, Albert Cairo tweeted about a great visual map he found in a 1938 issue of Fortune Magazine at Steve Heller’s Moving Sale on Saturday, June 28th, 2014 in New York City.
Steven Heller wears many hats (in addition to the New York Yankees): For 33 years he was an art director at the New York Times, originally on the OpEd Page and for almost 30 of those years with the New York Times Book Review. Currently, he is co-chair of the MFA Designer as Author Department, Special Consultant to the President of SVA for New Programs, and writes the Visuals column for the New York Times Book Review.
He is the co-founder and co-chair (with Lita Talarico) of the MFA Designer as Author program at the School of Visual Arts, New York, where he lectures on the history of graphic design. Prior to this, he lectured for 14 years on the history of illustration in the MFA Illustration as Visual Essay program at the School of Visual arts. He also was director for ten years of SVA’s Modernism & Eclecticism: A History of American Graphic Design symposiums.
The World in Terms of General Motors
The visual in the December 1938 issue of Fortune Magazine was called The World in Terms of General Motors. It depicted a sketch map showing the location of (then) GM’s 110 plants. The spheres representing each plant are proportional (in volume) to their normal number of workers. The key numbers of the spheres are indexed on the map. The map does not include those manufacturing plants in which GM has less than 50% stock. The principal ones are Ethyl Gasoline Corp., Bendix Aviation Corp., Kinetic Chemicals, Inc., and North American Aviation, Inc.
Not shown are GM’s many non-manufacturing interests, domestic warehouses, etc.
So, finally, here is the complete map.
[Click on the map image to enlarge]
Charles Minard’s Map of Napoleon’s Russian Campaign of 1812
One of the most famous maps incorporating time was created in 1861 by Charles Minard, a French Engineer. The map and chart, entitled, “Carte figurative des pertes successives en hommes de l’Armée Française dans la campagne de Russie 1812-1813″, brilliantly illustrated the march to and from the Polish-Russian border to Moscow by Napoleon’s army and was profiled in the article, Spatial Unmapped on GIS Lounge.
422,000 soldiers began the journey in June of 1812 towards Moscow and only 10,000 made it back to the border after the failed invasion. Minard’s map has been acclaimed by many for its clear use of geography and time to show how devastating the invasion of Russia by France was on the troops.
Noted statistician and Yale professor, Edward Tufte, declared in his 1983 book The Visual Display of Quantitative Information , that the Minard graph “may well be the best statistical graphic ever drawn.”
Esri Press has recently released a book inspired by Minard’s Map entitled, Mapping Time:
Published by Esri Press, Menno-Jan Kraak’s book Mapping Time: Illustrated by Minard’s Map of Napoleon’s Russian Campaign of 1812 combines historical and geographic analysis with cartography to examine mapping change over time.
The book includes more than 100 full-color illustrations inspired by graphic innovator Charles Minard’s classic flow line map of Napoleon’s disastrous invasion of Russia.
Kraak is a professor of geovisual analytics and cartography at the University of Twente in Enschede, Netherlands who has also written the textbook, Cartography, Visualization of Geospatial Data.
Book details: Mapping Time: Illustrated by Minard’s Map of Napoleon’s Russian Campaign of 1812 is available in print (ISBN: 9781589483125, 168 pages, hardcover) and e-book format (ISBN: 9781589483668).
The Lionel Pincus & Princess Firyal Map Division, New York Public Library (NYPL) has announced the release of more than 20,000 cartographic works as high-resolution downloads. The New York Public Library believes these maps have no known U.S. copyright restrictions.* To the extent that some jurisdictions grant NYPL an additional copyright in the digital reproductions of these maps, NYPL is distributing these images under a Creative Commons CC0 1.0 Universal Public Domain Dedication. The maps can be viewed through the New York Public Library’s Digital Collections page, and downloaded, through the Map Warper. You will first need to create an account, then click a map title and go.
What’s this means for all of us map lovers?
It means you can have the maps, all of them if you want, for free, in high resolution. NYPL has scanned them to enable their use in the broadest possible ways by the largest number of people.
Though not required, if you’d like to credit the New York Public Library, please use the following text “From The Lionel Pincus & Princess Firyal Map Division, The New York Public Library.” Doing so helps them track what happens when they release collections like this to the public for free under really relaxed and open terms. NYPL believes their collections inspire all kinds of creativity, innovation and discovery, things they hold very dear.
* The maps may be subject to rights of privacy, rights of publicity and other restrictions. It is your responsibility to make sure that you respect these rights.
Source: Josh Marshall, Artifacts #1: The First Map of Africa, talkingpointsmemo.com, March 7, 2014, http://talkingpointsmemo.com/edblog/artifacts-1-the-first-map-of-africa.
Mr. Marshall notes that the map below is believed to be the first map of Africa, as a continent. “Africa” was originally a Roman term for the region of modern Tunisia and the western portion of Libya. The Arabs later adopted a similar definition. But this is the first known map of the new concept of Africa as a continent stretching from North Africa down to a southern tip that could be rounded and from which you could then sail on to India and Asia.
Princeton University, Historic Maps Collection.
The map is the work of Sebastian Munster (1489-1552), a professor of Hebrew at the University of Basel. This is mid-16th century, so going on 60 years after Europeans first rounded the Cape of Good Hope to Asia, though the Portuguese had been exploring the western coast of Africa a good deal longer.
Mr. Marshall continues by saying that this map is a fascinating period in the history of European map-making since most were then being strung together through an odd partnership between university academics and printers in Europe on the one hand and explorers and traders on the other, the former still partly hung up on ancient ideas on the shape and outlines of the world as well as theories about where certain things must be and the latter with real observational data about what they’d seen.
Not surprisingly, North Africa is fairly accurate and the key rivers in West Africa bear at least some resemblance to their true locations. Things get a good deal iffier about Central Africa and the scale of Subsaharan Africa. And there’s a pretty serious Ethiopia fail. It’s right over the one-eyed giants who live in Nigeria. When you consider the limited observational knowledge, extremely poor ability to measure distance, obstacles to communications and the fact that the key sea-faring powers treated all this information as state secrets, the degree of accuracy is fairly remarkable.
In viewing the map below, Mr. Marshall notes that still more remarkable is this Abraham Ortelius map from only 30 years later. Published at Antwerp in 1584.
Princeton University. Historic Maps Collection.
As you can see, on a quick look this could almost be a modern map of Africa, though many things are distorted, not least the scale of the Red Sea relative to the rest of the continent.
Digital artist Eowyn Smith has created a map of the world highlighting the location where animated films by Disney and Pixar took place. The fan art maps 44 Disney animated films 13 Pixar films. It reaches as far back as Disney’s first film, Snow White, and includes Disney’s 2013 release Frozen.
In traditional cartography fashion, Wall-E, Monsters, Inc., Dinosaur, Treasure Planet, and Wreck-It Ralph are given an inset. The films are variously set in the future, prehistoric past, or alternate universes.
- Movie was placed based on the location IMPLIED IN THE DISNEY/PIXAR VERSION
- If the movie was too vague to determine a location, the original story/myth was consulted.
Source: Katherine M. Hill, Laughing Squid, February 11, 2014, http://laughingsquid.com/a-map-showing-the-geographic-locations-disney-and-pixar-films-around-the-world/.
Today I am going to show you a fantastic choropleth map created by Matthew Bloch, Matthew Ericson and Tom Giratikanon from The New York Times. Their graph maps poverty in America.
Now, before we look at the map, let’s discuss what a choropleth map is.
A choropleth map (Greek χώρο– + πλήθ[ος]), (“area/region” + “multitude”) is a thematic map in which areas are shaded or patterned in proportion to the measurement of the statistical variable being displayed on the map, such as population density or per-capita income.
The choropleth map provides an easy way to visualize how a measurement varies across a geographic area or it shows the level of variability within a region.
A special type of choropleth map is a prism map, a three-dimensional map in which a given region’s height on the map is proportional to the statistical variable’s value for that region.
The earliest known choropleth map was created in 1826 by Baron Pierre Charles Dupin. The term “choroplethe map” was introduced 1938 by the geographer John Kirtland Wright in “Problems in Population Mapping”.
Choropleth maps are based on statistical data aggregated over previously defined regions (e.g., counties), in contrast to area-class and isarithmic maps, in which region boundaries are defined by data patterns. Thus, where defined regions are important to a discussion, as in an election map divided by electoral regions, choropleths are preferred.
Where real-world patterns may not conform to the regions discussed, issues such as the ecological fallacy and the modifiable areal unit problem (MAUP) can lead to major misinterpretations, and other techniques are preferable. Choropleth maps are frequently used in inappropriate applications due to the abundance of choropleth data and the ease of design using Geographic Information Systems.
Incorrect (population, left) and correct (population density, right) application of a choropleth to data for Boston, Massachusetts
The dasymetric technique can be thought of as a compromise approach in many situations. Broadly speaking choropleths represent two types of data: Spatially Extensive or Spatially Intensive.
- Spatially Extensive data are things like populations. The population of the UK might be 60 million, but it would not be accurate to arbitrarily cut the UK into two halves of equal area and say that the population of each half of the UK is 30 million.
- Spatially Intensive data are things like rates, densities and proportions, which can be thought of conceptually as field data that is averaged over an area. Though the UK’s 60 million inhabitants occupy an area of about 240,000 km2, and the population density is therefore about 250/km2, arbitrary halves of equal area would not also both have the same population density.
Another common error in choropleths is the use of raw data values to represent magnitude rather than normalized values to produce a map of densities. This is problematic because the eye naturally integrates over areas of the same color, giving undue prominence to larger polygons of moderate magnitude and minimizing the significance of smaller polygons with high magnitudes. Compare the circled features in the maps at right.
When mapping quantitative data, a specific color progression should be used to depict the data properly. There are several different types of color progressions used by cartographers. The following are described in detail in Robinson et al. (1995)
Single-hue progressions fade from a dark shade of the chosen color to a very light or white shade of relatively the same hue. This is a common method used to map magnitude. The darkest hue represents the greatest number in the data set and the lightest shade representing the least number.
Two variables may be shown through the use of two overprinted single color scales. The hues typically used are from red to white for the first data set and blue to white for the second, they are then overprinted to produce varying hues. These type of maps show the magnitude of the values in relation to each other.
Bi-polar progressions are normally used with two opposite hues to show a change in value from negative to positive or on either side of some either central tendency, such as the mean of the variable being mapped or other significant value like room temperature. For example a typical progression when mapping temperatures is from dark blue (for cold) to dark red (for hot) with white in the middle. When one extreme can be considered better than the other (as in this map of life expectancy) then it is common to denote the poor alternative with shades of red, and the good alternative with green.
Complementary hue progressions are a type of bi-polar progression. This can be done with any of the complementary colors and will fade from each of the darker end point hues into a gray shade representing the middle. An example would be using blue and yellow as the two end points.
Blended hue progressions use related hues to blend together the two end point hues. This type of color progression is typically used to show elevation changes. For example from yellow through orange to brown.
Partial spectral hue progressions are used to map mixtures of two distinct sets of data. This type of hue progression will blend two adjacent opponent hues and show the magnitude of the mixing data classes.
Full spectral progression contains hues from blue through red. This is common on relief maps and modern weather maps. This type of progression is not recommended under other circumstances because certain color connotations can confuse the map user.
Value progression maps are monochromatic. Although any color may be used, the archetype is from black to white with intervening shades of gray that represent magnitude. According to Robinson et al. (1995). this is the best way to portray a magnitude message to the map audience. It is clearly understood by the user and easy to produce in print.
When using any of these methods there are two important principles: first is that darker colors are perceived as being higher in magnitude and second is that while there are millions of color variations the human eye is limited to how many colors it can easily distinguish. Generally five to seven color categories is recommended. The map user should be able to easily identify the implied magnitude of the hue and match it with the legend.
Additional considerations include color blindness and various reproduction techniques. For example, the red–green bi-polar progression described in the section above is likely to cause problems for dichromats. A related issue is that color scales which rely primarily on hue with insufficient variation in saturation or intensity may be compromised if reproduced with a black and white device; if a map is legible in black and white, then a prospective user’s perception of color is irrelevant.
Color can greatly enhance the communication between the cartographer and their audience but poor color choice can result in a map that is neither effective nor appealing to the map user; sometimes simpler is better.
Mapping Poverty in America: A View of Philadelphia
Below is a screenshot of the choropleth map from The New York Times Web site. For my example, I focused on Philadelphia (no specific reason; just the one I happened to click on).
To view the actual interactive version of this map, just click on the image below.
 T. Slocum, R. McMaster, F. Kessler, H. Howard (2009). Thematic Cartography and Geovisualization, Third Edn, pages 85-86. Pearson Prentice Hall: Upper Saddle River, NJ.
 Mark Monmonier (1991). How to Lie with Maps. pp. 22-23. University of Chicago Press
 Robinson, A.H., Morrison, J.L., Muehrke, P.C., Kimmerling, A.J. & Guptill, S.C. (1995) Elements of Cartography. (6th Edition), New York: Wiley.
 Patricia Cohen (9 August 2011). “What Digital Maps Can Tell Us About the American Way”. New York Times.
 Light et al. (2004). “The End of the Rainbow? Color Schemes for Improved Data Graphics””. pp. 385. Eos,Vol. 85, No. 40, 5 October 2004.
Mapping time has long been an interest of cartographers. Visualizing historical events in a timeline or chart or diagram is an effective way to show the rise and fall of empires and states, religious history, and important human and natural occurrences. To see more interesting maps ranging in date from 1770 to 1967, visit over 100 examples in the Rumsey Map Collection.
Source: BETSY MASON, 11/20/2013, WIRED
There is a temptation with any kind of data that has a geographical aspect to display it on a map. While maps are by far the best way to convey many of these data, sometimes they are not. This is one of those times.
Even though data on migration between states would seem to cry out to be mapped, this circular visualization by independent data journalist Chris Walker (@cpwalker07) can convey a lot of information far more neatly than a map. Patterns leap out that might have been obscured on a single map, or required many maps to convey the same information (see images below).
“It’s useful to think beyond maps especially for cases where you want to show interconnectedness between regions, which is what I was trying to do,” Walker wrote in an email to WIRED.
[NOTE: The interactive map discussed below can be found on WIRED’s site by clicking the link here. I should note that it worked best for me using Google Chrome]
When I first saw Walker’s migration circle (which he built using D3.js), it looked like a jumble that was impossible to untangle, but that’s before I realized it was interactive. If you haven’t already, mouse over the graphic to display information from single states to see where people from that state moved to last year, and where the people who moved into that state came from. More than 7 million Americans moved within the country, so if you’re looking for a time sink, you’ll find it in this circle.
“I think we can learn a lot from migration patterns,” Walker wrote in an email. “In a way, migration flows are one of the oldest forms of crowdsourcing. They tell you which geographies the crowd deems to be low-opportunity, and which the crowd deems to be high-opportunity.”
I live in California, so I started there. I love this state, and it seems to me people are moving here all the time. But it turns out, more people are leaving (73,345 more). As you can see in the snapshot to the right, Californians don’t usually stray too far though, tending to migrate to other western states. Or Texas. A likely explanation for the outflux is that you could buy a mansion in some parts of the country for the same amount as a 2 bed, 1 bath house in the Bay Area.
Despite the initial jumble, a couple of things jump out before you even begin interacting with the graphic. A lot of people are moving out of New York (135,793 net loss) and ending up all over the place, including the other side of the country. The same is true for the Midwest, with people mostly landing in the Southeast, Southwest and California. These trends are clearer when you look at individual states, but the broader trends would be easier to grasp if you could mouse over the region names to see where, say, everyone in the Northeast moved.
One thing to note as you look at what’s happening with New York, for example, is that only exchanges of at least 10,000 people are depicted. This, Walker says in his blog post, is to keep the graphic from becoming to messy. So, while many people are moving into New York, most of them aren’t shown because they are coming from many different places in smaller numbers.
Some of the other things Walker noticed include that fact that a lot of people are moving to Florida, many of them likely retirees. “Interestingly the state contributing the most migrants to Florida is neighboring Georgia,” Walker wrote in his blog. “Texas, New York and North Carolina are the next largest contributors.”
The second largest draw for migrants was Texas. “Over 500,000 people moved to Texas in 2012,” Walker wrote. “People tend to come from the Southeast, Southwest and the West, with the biggest contributor being California. 62,702 Californians packed up and moved to the Lone Star state in 2012.”
People who leave D.C. don’t really leave, generally moving next door to Virginia or Maryland. In contrast, people moving from Maine and Alaska are chasing the sun all the way to California and Florida. Check out his blog post for more insight.
In contrast to Walker’s circular visualization, old census atlases used maps to show the migration data. In August, we visited the Prelinger Library here in San Francisco and took a look at some of these atlases in their collection. In the images below, you can see how the data was displayed. On the right is a map showing where New York natives lived in 1890. New York has the most natives, unsurprisingly, and is the darkest. But the migration pattern is similar to 2012 with New Yorkers heading all over the place. These maps highlight some of the limitations of maps for displaying this kind of data.
Maps from the 1890 Census Atlas at the Prelinger Library in San Francisco. (Ariel Zambelich/WIRED)