Monthly Archives: October 2013

D3 Maps the Filling-Up World

D3 images, or data-driven maps, shift with the content that they seek to display.  They in other words provide tools of spatial analysis unlike static maps or terrestrial projections:  for rather than reflecting or arranging data in a static form, by analogy to a window, such maps reveal the changing data that drives their design.  Such maps lend themselves in timely ways as tools able to chart a changeable terrain–or the shifting configuration of a distribution–which often are tied to data feeds, rather than employing a fixed dataset.

Since D3 maps are often able to take advantage of their mutable forms by being incorporating new data, using it to determine the rendering of a shifting actual space or set of inter-relations.  So the mapping growth of population in the world’s countries is a classic example of a D3 tools of visualization, determined by the growth of residents in each country:  although the base-map of the recent simulation of world birth/death rates by software developer Brad Lyon is a familiar grey projection of the continents, the constant data feed that shapes the map, locating individual births and death in specific places, and tabulating the greatest numbers of births in individual countries, is also a visualization of Tobler’s first Law of Geography:  that “Everything is related to everything else, but near things are more related to distant things.”  For the changes in global population are understood in the unit of the entire inhabited earth in this very catholic map, rather than as able to be confined to the borders of individual countries.

Among the benefits of using D3 visualizations to chart the rhythms and rates of births and deaths is a channelling of immense amount of information that is both a tremendous ramping up of cartographical omniscience that the viewer can often barely process or register in its totality–for the edges or contours of the map can be changing constantly, rather than the map being designed to reflect a stable dataset.  The popular new map of changing numbers of birth and deaths in the global population provides a neat visual example of using maps to geo-tagged births and deaths to part of a nation, offering, in either simple screen or beta-version simulation, something that would not be possible in a static or simple paper map.  In a visualization of the drumroll of births and deaths, the resulting map creates a record of the inhabited world that is “eerily omniscient” as James Hamblin aptly put it in The Atlantic, and God-like in its observation of births and deaths everywhere:  as the map’s odometer-like upper panel trucks past the 7 billion, 93 million mark, we are asked to face the challenges of comprehending on individual terms what truly approaches, if only asymptotically, something close to a God-like perspective on mankind.

By visualizing an approximate record of “world births and deaths in real-time,” in a map that extends to its literal meaning the notion of the “inhabited world,” the content of this map challenges not the borders of maps, as do so many D3 projections, but the viewer’s own boundary of self, or the meaning of this endless tabulation of the appearance and disappearance of lives on the planet and the regions of their greatest increase.  This single frame of the ongoing graphic portraying a record of world populations over the globe’s surface, in what might be called, with more than a wink, a truly existential map of the place of humanity in the world:


Visualizing Birth and Death world Wide at 5-27 Oct 30 2013


Never mind that the countries are only light grey outlines, and the subject of geography is secondary to the map’s shifting contents.  At issue is not how we inhabit the space, and not the centers of population or their distribution, but a statistical ping of each birth and a death that can be easily geo-located, blips of text that overwhelm and even detract attention from a grey base-map that seems to recede below each announcement, until they entirely bury the map, no doubt as our population will bury our world if its numbers proceed to grow by a further 44 percent by 2050.

There is no need to ask where these people will live or how they will be fed in this visualization:  we can wonder that all we like as the number of births proceed unimpeded, always far in the lead of the counting off of individually tragic deaths.  But in their collectivity, the amassing of these numbers is difficult to comprehend or register–and not only because of the relative objectivity of the simulation.   As one looks at the data visualization and the so rapidly increasing numbers of its statistical simulation, it starts to become evident that the perspective it offers is just not tenable for a viewer to start to process; its numbers perform an odd if awesome balancing act between concrete actuality and abstraction impossible to really comprehend, and we wonder where this data flow derives, as its ticker-tape pop-ups jerkily transport us to half-familiar or unfamiliar cities as it notches population growth, and the map is buried by textual banners–much as their viewer is buried by an unweildly surplus of information.

Software developer Brad Lyon used some ideas and concepts of Mike Bostock’s D3 maps in order to create a real-time register of births and deaths worldwide–or a simulation of them–that the viewer could gape at in wonder, and view almost as the objective correlative of the bulging population of the world.  As was recently reported in The Atlantic, this digitize simulation charts the contours of the inhabited world, expanding the use Lyons made of United States Census data in his popular simulation map, designed with Bill Sneebold, to create a  visual readable interactive map of the country’s population.

The overwhelming effect is immeasurably more dizzying than looking at a paper or static map.  But perhaps this also conveys some share of the immensity that must have overwhelmed classical viewers, unlikely to have ever been able to process information of far-off lands, in early images of the classical concept of the bounded ecumene.  The cartographical canvas is both familiar and  disorienting, if only because of the size at which every birth and death appears, generating banner toponyms rapid-fire progression that one can allow oneself to imagine reflects the actual swelling of population numbers across the world in real time.  The immensity with which the momentary geo-markings of this tally invests new claims in a pretty standard projection of the planisphere; highlighting specific places in what almost seems a random-generator makes its surface a field that is entirely disorienting in its surplus of detail:  as soon as one finds ‘news’ of a death here, in Khasakstan, there is a birth in Bolivia, and two more in Punje, so that numbers  Starting from the very moment that you open it up, and continuing until the screen becomes completely illegible as ticker tape birth and death announcements utterly obscure its surface–


10;24 to 10;53--Oct 30

or until you get in a hazy-headed stupor and realize that you’ve been watching the register doing its’ job for too long, and just have to leave the room since you can’t really keep up with all this–is an real-time image of the inhabited world, and a reminder we may have just have access to too much data.

The visual register in the screen image not only announces each and every birth and death with a punctual precision that is always eery, but keeps a tally of the totals and their distributions in each country, and they all cause one to be reminded relentlessly that births always outstrip deaths.

Visualizing Birth and Death world Wide at 5-27 Oct 30 2013


In ways that mapping the boundaries of mapping the world challenges the boundaries of self, the popping of up sites of individual birth and death on the simulation, which occurs below a population counter of the high velocity of our course of global overcrowding, the map is mind-blowing because it challenges the boundaries of what the viewer can hold in her or his head, as much as because of its terrestrial coverage–there is a sort of hortatory “look here!” “no, here!” “here goes again!”–that calls one’s eye back to the day-to-day nature of lived experience that is so often outside the horizon of maps, and rooting them in an ostensibly exact record of the transit of time:  from 5:10:26 p.m. to about 5:30 on October 30, births occurred at a rate of 4.2 per second, as 4,210 lives began, a large number (about a sixth) in India and a fourth in India and China, compared to 1,879 reported deaths during the same interval:  the explosion of population is captured nicely in that chunk of less than twenty minutes.



Visualizing Birth and Death world Wide at 5-27 Oct 30 2013


And indeed it seems, at first, that the number of births in China and India dominate the map overwhelmingly, as they also  form by far the greatest percentage of births world-wide, according to the data feed, as text appears that clutters the expanse of the terrestrial world, as if to provide a dizzying counter-map to the stability of terrestrial contours, that will eventually obliterate the map itself:


Births and Deaths in Asia?


But then one realizes that this is a conceit of the format of the map, or its display of geo-tags, which oddly cluster over the area of Eurasia as they are generated by incoming data, even if they are from cities in the midwest of the United States.

Of course, it’s not like you never knew that folks were regularly born and died in this world, even in places that you’d never been or will ever visit, but this almost “odometric  perspective” of individual lives clicking by, new ones popping up in places and others vanishing elsewhere, could either be a Buddhist envisioning of the ephemerality of being or a worrying sign of just how quickly things are crowding up.

Take a look at the beta version in Google Drive:

The post-modernity of this form of D3 mapping takes the ancient idea of the expanse of the ecumene, but turns it on its head:  the population takes over, swallows, and erases whatever qualitative content was on the map, as the base-map starts descends to irrelevance, and, illegible, is unable to offer us any bearings at all.  As much as offering a material subject, the D3 map unwittingly charts the ephemerality of the ecumene.

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Filed under data driven maps, data visualization, Google Drive, Interactive Maps, mapping population, mapping the populated world, Mike Bostock, terrestrial cartography

Data Creep

The relative onslaught of poor data visualizations so plaguing much of the news media may derive from a hope to attract new audiences as budgets shrink and bureaus decline:  by boiling down a “story” by dispensing with those bothersome words, they seek to make immediate impact on an audience by a powerful (and eye-catching) graphic.  Based on the self-reported responses to the “Big Five” personality test questionnaire that was developed in the 1970s, but recently used to aggregate responses via Facebook, which posits “five dimensions of personality” to distinguish personality types, based on the odd belief that, rather than reflecting individual character, one could detect “different regions of the U.S. have different personalities.” The self-reported rankings of attitude (curiosity, energy-level, tenseness, quarrelsomeness, forgiveness), efficiency (reliability, laziness, perseverance, efficiency), and character (shyness, moodiness, distractibility, sociability, rudeness) are values with little possible quantifiable relationship among themselves, which translate into a data-distributions of limited legibility or credibility after they’ve crept into a map.  Projected onto a map the colorful choropleth offers a “mood-ring for the nation” whose choice of hues communicates little intuitively:


Unimaginative data overlays like this  lie somewhere between video games, a MacPaint program, and an adult coloring book approached with Prismacolor markers–more a diagram than a map, they serve to carve the nation into clear blocks as if this would clarify anything about national unity or collective networks:  such visualizations take pride in how they disrupt continuity in a search for a narrative about the national divides that are revealed in our political process, and do so with varying degrees of precision.   Their production seems to be driven creep of data into overlays atop base maps, as if to awkwardly digest the familiarity with data–and make all feel like they have access to truly “big data”–by using an image of the nation to bequeath authority even to miniscule data samplings by treating them as images able to visualize datasets:  this is an insidious format makes us thirsty for more of the same, as we seek to grasp divides and parse divisions with the apparent exactitude of a surgical scalpel.

The recently widely retweeted but fairly facetious map of “America’s Moods”, an interactive graphic mapping emotions titled “America’s Mood Map,” has circulated online with considerable popularity but is able to be blamed on Time magazine’s website.  The data visualization has just the right mixture of declarative insouciance and light-heartedness make it a meme and bane of online journalism, and a typical illustration of this dilemma.  The distribution of data that results deflect scrutiny from the very data that they’re employed to embody.  The interactive blocks of color in what seems a choropleth distribution are a bit compelling, until one asks what state-lines have to do with emotions after all, or if this just was a nifty way of converting data to visual form.

What sort of embodiment of data is going on here, one might well wonder, and question what the mosaic of colors communicate or signify.  Not to mention the map’s confusion of a question of individual psychology and gross geographic regions–especially such abstractly construed categories as the legal boundaries of forty-eight individual states’ authority in our nation’s union.

The interactive ‘map’ demonstrates the recent discovery that responses to the great American greeting, “How you doing?,” differ starkly across state lines in the lower forty-eight:  if in benign fashion, the result proclaims divisions and splintering that trump the continuity of territorial maps, and perhaps map an explanation for all the differences we already know.



America's Mood Map



Why “friendliness” is signified by red, “temperamental and uninhibited” by blue is as problematic as the lack of any continuity among these personality types, and the relative subjectivity of judgment:  it turns out that these are self-classifications, anyway, rather than determined by objective criteria–as if values like these could be objectively assessed.

The lack of material references in such ‘maps’ almost winks to viewers not to take them too seriously.  Yet the relative ease of converting statistics into overlays on base-maps in web-based formats, seems the rationale for their popularity as interactive media in on-line news publications.   Forget the actual map that orients its viewer to the lay of the land:  this is immersion in the map as interactive data environment.

The deepest difficulty of this data visualization may lie in how it confounds the empiricism of a map with pretty relative–and pretty vaguely construed–psychological categories. Although Time magazine science editor Jeffrey Kluger seems to have fun downplaying is meaning at the same time as he promotes it, “America’s Mood Map” is the most popular in the section “Science and Space” among readers of Time this past week, and a success by journalistic standards, is the interactive map of emotions across the United States, across which one can glide one’s cursor to reveal a virtual version (and modernization) of the early modern Carte de Tendre over which you can mouse about to find a place that “matches your personality”:  but rather than visualize material renderings of feelings or emotions, as that topography of amorous practices, the imaginary topography over which we mouse to find the ranks of each state’s inhabitants reveals clear divides rather than a detailed qualitative record.  Data has crept into this map’s bright mosaic of colors can’t help but engage other data-vis maps, with which its full-spectrum color schema stands in such stark contrast.


Moood Map of US

Although the color blocks are arranged in something like a spectrum of friendliness to temperamental, the actual values on which they are based provides something of a map of mental constitutions, as much as emotions, and one can range of neurotic to extroverted, with open-ness thrown into the mix.  The explorer of the map can find themselves, for example, in “agreeable, conscientious and open Tennessee;” we all know a few who fit the description:


Conscientious Tenessee


The ranking of each state surely increased its popularity, as the map becomes yet another tabulation of characteristics after one mouses around a bit on its surface.  California, predictably, is both relaxed and open (#2 nation wide!) and low in neurotics (#43; agreeable Utah lies at the bottom of the heap at #49), and New Yorkers are temperamental but ranked as among the most open (#3).  (Such classifications based on a sampling of 30,000 must conceal the detailed nature of the questionnaire.) Who would have thought that largely rural Wisconsin, a state with one large city, possessed the most extroverted population in the country? Or that Maine stood near the nation-wise apex of neuroticism?  New York gets pretty low marks for “agreeableness,” whatever that means (#48 in the nation), if it is also pretty high in “openness.”

There might be some problems with the data pool.  Perhaps the map’s very lack of materiality makes it difficult take seriously, even if the pleasure of using moods to divide the country seems a relief from dividing the nation by ideological divisions.  (The next step that this map seems to invite is no doubt for carto-data-crunchers or map-readers to map the moods of the nation onto those political divisions:  how better to easily explain the ideological divisions that grip our media on the eve of the Affordable Care Act and the morning after the Government Shutdown?)   Indeed, the interest in the “mood map” among Time‘s readers might been generated in part by hits from all those readers, long subjugated to an onslaught of data visualizations, who want to explore their own states in the mirror of their own states of mind or who want to try to map the now-tacit maps of national division onto the far more innocuous (and un-ideological) question of moods.  Indeed, this stepping out of the recently emerged graphic lexicon of ideological division and splintering is somehow reassuring, as, much as the article announced, maybe its mistake  this country “features the word United in its name,” since “we splinter along fault lines of income, education, religion, race, hyphenated origin, age and politics.”

Maybe it does really all boil down to constitution and emotions, all those earlier data distributions be damned.  The end-product is something of a polemic rebuttal to the authority of earlier data visualizations in the news, to be sure, of a very tongue-in-cheek sort of very, very muted irony.  The text’s injunction to find where you belong in the map–by your mood, not by where you actually are–invites you to glide your mouse over a map with the authority of a spatial distribution of the rainbow colors of a mood ring, in a pretty abstracted state of mind, so unlike the ways in which, say, a detailed topographical map registers the measurement of physical elevations by exquisitely exact orographical detail.

The survey employed was based on a sample of under 30,000 respondents, but passes itself off as a pretext for self-examination or -understanding, complete with the assurance that results won’t be reported or stored by Time is respectful of your privacy (perhaps to marketers of antidepressants?).  Whether it is able to map such stark divisions of “mood”-tendency beyond statistical error is unclear, although the almost spectroscopic division of the nation into stereotypes seems somewhat persuasive:  the center of the country, if not so large a swath as the “red-states” of Bush years, is proudly “conventional and friendly,” unlike the creative types on both coasts:  the mapmakers permit little constitutional overlap among these categories, or multiple combinations of them, so much as render one of the three criteria for each state, and allow little overlap among them; the cartographical “paratext” to the map placed above its panels invite its readers to take a short test so that one might place your personal constitution where it really belongs, and suggests that these three metrics are rigidly exclusive from one another.


Moood Map of US

The result is a new portrait of the dis-united states, several of which are already in widely circulation–and some even so widely internalized as ideological divides that one can’t make associations between this “map” of emotions to more familiar political and social divisions.  The data visualization may be taken as a pretty light-hearted response to our dramatically increased geographical mobility, or our obsession with data-visualization maps.  But Kluger and co-author Chris Wilson use the data of fellow-American Jason Rentfrow, obtained at Cambridge by a multinational think-tank created data by a psychological survey of their own device, and the map is presented in the rubric of the “Science” section of the magazine’s website.  The data that was used to inform the visualization, under the name of science, claims to reflect the salient divisions of what “for a country that features the word United so prominently in its name, the U.S. is a pretty fractious place,” as if it might be a more credible set of criteria to ascertain relative depths of fractiousness and their causes–despite its odd metric for measuring “emotional” divisions.

And its interactive features create at least half of the fun for its readers.  The notion of locating diversity in our moods is a lot more appealing than finding it elsewhere; the mirror of the interactive map is no doubt a partial reason for its popularity.  Indeed the invitation to guide oneself to one’s own and one’s nation’s emotions might be hard to pass up, if it suggests quite a lack of complexity in the terrain revealed by introspection, which seems, here, to be equivalent to the completion of a modular form, rather than offering a topography that might be worthy of future qualitative detail.

There is a more authoritative, and perhaps more familiar, map of which the map dissected above might be called the comic repetition.  The study of state-specific variations in happiness (one emotion–that’s a better concept already) was the result of a study based at UVM of geotagged tweets, published in the online journal PLoS ONE, whose tabulators ranked over 10,000 words on a graduated scale to score some millions of tweets across the country, irrespective of their context, to reveal significant differences in sadness and happiness across the nation, perhaps better translating what might be called a set of emotional divides:


Happiness Score in One Map


Indeed, the clear “sadness belt” marked so appropriately in such sombre black hues, and casting a deep shadow over our southern states which curls up to the economically depressed areas of the midwest, suggest something like a meaningful map, with the noting of neat exceptions of particularly happy cities, Asheville and Green Bay.   The weighing of these cities as exceptions lends a credence to the overall distribution of tweets the researchers collated in their data visualization, and the depth of data on which they relied.  The substantive study collated tweets over several years, even tracing computable variations in daily happiness averages that could be mapped to contemporary events, creating a set of stunning data visualizations in this “hedonometric” visualization from 2008 to the present whose units of days are suitably color-coded for weekday, allowing one to register how daily variations are effected by workdays and weekends.  The “hedonometer” seeks to provide the most accurately parsed chart of “happiness” based on daily counts of the tweeted words of happiness–the most common five words of happiness used each day suddenly appear when the day is hovered over.  The  graph is great fun to investigate, and can be tied to news events that impacted the nation’s overall index, from the Newtown shootings to inauguration days or holidays:  note the nation-wide spike on events like Christmas, which, since we still seem to all celebrate or at least note in some fashion, always reliable produces incalculable tweets.

If the first map from Time is a descendant and comedic successor to the UVM map of happiest states, both seem to rehabilitate the paper map in digital form as something like a response to the need for a “GPS for the soul,” an unfortunate mash-up if there ever was one.  Such maps exist in the big data-visualization echo chamber that has dominated our abilities to envision our country.  This echo chamber has existed ever since we came to believe that the country could be meaningfully cut up in meaningful ways for ready consumption.  If it could lie in the easy access to maps and data visualizations, it seems to respond to an unquenchable the thirst for images explaining regional differences that underly such a dichotomously divided status quo, since the division has roots that cannot be purely ideological in nature.

The single spectre that haunts the rise of even the most banal of data visualizations in media news in recent years may be maps of electoral results, especially from the Bush-Kerry 2004 election, in which that large red expanse of the middle of the country created a contrast to a close electoral contest of 296 to 242, which could have been upset by a single state.

Bush 296 - Kerry 242

The map haunted because it was almost repeated in 2008, with a key variation, only to be beaten back in recent years.

Obama:Biden McCain:Palin

These images seem to be seared into viewers’ minds, or at least into the unconscious of data visualizers.  Data of all sorts has since seeped into the map of the contiguous forty-eight.

Of course, the mother of all data-visualization maps is the most spectral, which still resonates with what some still consider the death-toll of democracy that at least one justice has come to regret:




The contrast between that map and the popular vote led to something of a polemic exchange that was based on peering into data visualization maps to parse the vote, we might have forgotten, that familiarized everyone with data distributions:


County by County Bush v. Gore


The mapping of the country’s population has gained increased symbolic currency as a sort of transparent rendering of national opinions, only dreamed of in the early days of NORC’s General Social Survey, and far more easily visualized.  The creeping of data into such visualizations of the nation as “America’s Mood Map” has, after all, lent new authority to a visualization both more colorful and less depressing than the dichotomous division of the nation into “Red” and “Blue” states of almost Manichean terms.

And they are also much, much less depressing than the sort of heavy-handed Google Map divisions of the country into those regions that are ready to relinquish pre-K funding or subsidies, an idea that seems to undermine our national interest, as well as of those states that refuse the expansion of Medicaid, all in the name of undue federal influence.  To start with the first, we can view it two ways in news media, but both ways to illustrate the difficulty of ever arriving at consensus:  the below interactive (and informative) map that explores the educational opportunities in the Southern states of the US illuminates differences in pre-K funding (click on the above to explore funding changes in each state from 2009 to 2011, since the color-scheme is not self-evident).





Below is a far more austere and stark way to visualize the data on how low many states rank kids less than four years of age, in which depression about care for pre-schools increases for the viewer in inverse relation to darkening of states’ hues.

PRE-K US 2005

In the colors of the data visualization blender, where data undermines map, there seems no consensus at all, and a pronounced fraying of the country’s diverse demographic.

One can always cut up the country in different ways, and the preferred way seems less based on splinters than blocks.  But some of the choropleths are striking and scary, as the refusal to expand health subsidies in the American Care Act, to which we’ll return.  The proliferation of these visualizations of difference may arise from the rise of the mythic “sea of red” in the general election of 2000 election through the Obama victory of 2008 may have left us barraged by the cutting up of the nation into camps.  The rise of new data visualizations seek to address these divides, but often seem to lie in the data visualization echo-chamber–as in the case of the “map of emotions”–as much as

But then there are those who reject either the Common Core standards or Affordable Care Act alike as forms of undue federal interference.




Rejection of the ACA reveals a similar fragmentation, despite some serious number-crunching that went on to illustrate the high proportion of poor, uninsured and low wage-earning residents in may those very same blocks of states:


legend- Poor and Uninsured Americans

8% poor and uninsured

This is an odd echo, as I’ve elsewhere noted, between the very regions which outright refuse government expansion of Medicare and those with lack of insurance and large numbers of low-wage earners and some of the same states that refused to accept clearance by the Dept. of Justice before they changed voting procedures as an instance of undue federal interference.


Clearance Required


It’s nicer just to think that it all boils down to individual moods, which the scientific status of ““America’s Mood Map” nicely parse along clearly defined state-lines–even if its end results may have the scientific status of a mood-ring.  The chromatic variations are at least attractive, and able to be read easily, removed from political dissensus.  And it’s certainly more fun to imagine that we might be able to find a sense of constitutional differences inherent in the atmosphere of a region, and mirrored in lines of state sovereignty, that somehow miraculously reflect an almost Hippocratic sensibility of the shifting humoral constitutions of residents of different climates, rather than political or sociocultural (and socio-economic) differences.

But it’s hard to make any sense of the visualization, largely since the very values that it depicts do not lie on a continuum in the manner of most polls or degrees of gradual difference, but seem qualitatively distinct, and even, often, judgment calls.  The state-by-state map of personal constitutions hearkens back to an early modern notion of how place and season inform the humors, or regional climates color the mind.

It is perhaps not a far stretch to include a data visualization of a state-by-state map of obesity trends (and no doubt diet)–


OBESITY 2010–although such a map seems to isolate the deep south and its southern neighbors from Texarkana to New Mexico.

A vague overlap of data seems to exist similarly sized region, sadly, is plagued by lack of completing High School–although this has little relation to body-size, and there is little evidence of a relation between them, even if it does speak to the difficulty of valuing educational reforms like Common Core.

The difficulties created by “inadequate education” does seem to divide the country, however, as this choropleth reveals, and not only among those able to complete High School, but even in those who, having completed High School education, were not allowed to be part of the Army corps–a truly shocking statistic that effectively does divide the nation.




Perhaps the only visualization that communicates unity is one of  cell-phone coverage, which customers, after all, desire–




By way of contrast, and a lightening of humors in how our country sees itself, “America’s Mood Map” shows a diversity around that one red block at its center, oddly located at Iowa–and whose deep red oddly seems to signify conventionality and friendliness–a quality the color does not suggest.

America's Mood Map

Other blocks of states are similarly lumped in oddly generic categories of states of mind–states of mind with limited relation to one another.  Hence, California, following, perhaps, conventional stereotype, is both open (if not that extroverted at all, particularly), and the among the least neurotic of the entire bunch.


Open and Un-neurotic California


In the most charitable reading permitted by the aggregation of data, the map would be an exercise in empathetic understanding of one’s neighbors limitations.   If one can permits an excursus, contrast it to the varied topography in the historic early modern “Carte de Tendre,” whose richly varied landscape suggests dangerous sites of delay or lack of clarity that the unaware and unsuspecting traveler may chance across by means of its locally detailed variations.


Carte de Tendre


These elegant enterprising travelers with cockades are gallant explorers of the outdoors, of course, rather than perched behind their screens.  Both the material and metaphorical nature of the data-visualization map are absent:  for in these cartographical transpositions, the data poses irreconcilable and absolute divides, and blocks any consensus from emerging.

“America’s Mood Map” is an artifact that serves as something of a mirror to make sense of our divided polity.  If one can given it a generous reading as an amusement, however, it may merit being taken seriously.  The eerily radical conceit of the data-visualization is not only that we are not “United” at all, but that one can naturalize states’ rights arguments in the radically different constitutions of their inhabitants, as if separate nations:  hence, conscientious Tennessee lies beside irascible Kentucky; open New York nearby to closed New Hampshire, and far from neurotic Maine; agreeable and conscientious North Carolina beside a Virginia that lags behind in both categories.  The authority that data is conceded in this visualization in fact erases mappable divides between rural and urban differences, socioeconomic distinctions, and patterns of wealth or any qualitative detail, taking the blocks of the electoral college as something like a national phrenological map.  The notion of an absolute difference in constitution as lying in direct relation to those state boundaries creates a particularly insidious illusion of differences that essentializes state lines–rather than following the idea of national character–that echoes one of the deepest presuppositions of what might be called Tea Party doctrine.  For the diversity depicted in data visualizations is always one engraved in hues of essentialization, rooting regions dispositions as fixed in a spectrum as different wavelengths, and empties the map of any continuity or local detail with those flat color blocks of distinctly defined individual “moods.”

How are you feeling?

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Filed under America, America's Mood Map, Care de tendre, choropleth maps, data visualizations, Google Maps, Hippocrates, Hippocratic humors, Jeffrey Kluger, MacPaint, mapping national divides, pre-K funding, Red states v. Blue States, Tea Party, Twitter map

More Better Mapping of Oakland’s Populations


Maps have long been described or conceived as windows–analogous in ways to pictorial perspective–that invite viewers to look into a space in new ways.  But both word maps as the above, made of the names of Oakland’s almost 150 different neighborhoods, or more statistically derived data visualizations of the city are mirrors that present a less homogeneous or continuous image of the city that we want to see:  if the roughly type-set image above suggest a make-do approach of the somewhat scruffy post-industrial port city with big loading docks, but erase its dirt or drastically depressed areas with lively type.

Data visualizations offer mirrors of the city’s inhabitants and shifting neighborhoods that are both dependent on the source-data that they use, and how they obtained it, but also on the dynamic layers that digital mapping allows us to place as overlays on the base-map of the city’s mountains and shores.  While these maps are only as good as the data that they use, they reflect back some of the divisions in the city that we might not otherwise notice or want to see.

And while not based in prose in the same manner as the Ozan Berke’s word-map that nicely knit together the city’s 146 vastly different neighborhoods, they offer ways of reading the city’s multiple divides.  The increased data that is available from Open Oakland and other sources will doubtless offer further–and far more refined–images of the city’s deep differences and their bridging, and can serve as better and more detailed maps of its populations.  But in the meantime, the sorts of mirrors these maps offer can also provide ways to imagine paths toward a future for Oakland, and better understand ways forward in its public policies.  Many of them draw from the American Community Survey, created by the US Census and discussed in earlier posts, but all seek to focus attention on the city and to serve, as mirrors, to show differently refracted visions of its divides, in the hope that few distort Oakland’s diverse populations.

A famous image of the distinctly uneven distributions of Oakland’s inhabitants is clear in a recent mashup of maps of the Bay Area Rapid Transit system’s public transport map–or, more simply, BART map–with the very zip codes that the American Community Survey mapped, which offers a condensation of the remarkable disparities and differences between income, education, child health and life expectancy at separate stations on the same public transport lines:

BART Health Map:Life Expectancy at BART stops

While, to be sure, the system includes suburbs such as Walnut Creek or Fremont, its focus on the East Bay  immediately indicates the deep divisions in a city where a BART stop can take one between areas of over ten years difference in life expectancy, and two more stops down either line sees life expectancy rise by seven or eight years once again.  The huge rise in childhood hospitalizations because of asthma in the City Center–far greater than in Fruitvale–suggests the unique pollution habits of a city whose air quality is still shaped by its proximity to a port.

The image of the diverse city whose neighborhoods are bound together as one unit starts to reveal fissures when one examines its ethnic and voting distribution at a somewhat finer grain, adding to the historical variations in the picture of the city summarized and surveyed in an earlier post.  The problem of mapping those populations adequately, both to reveal the ongoing inequalities and spatial injustice within the city, is not inherent in the city’s structure or divisions, but something that compels visualization in a myriad of ways, and in which we can look for different understandings of the shifting nature of the city’s socioeconomic (and sociocultural) divides.  As well as mapping the lay of the land, mapping the habitation of space creates even more of a “mirror” on the organization of th eplace.


The census mosaic only shows part of the inhabitants’ picture.  Indeed, perhaps a “racial dot” map can be rehabilitated, rendering one dot/twenty-five people, to create a rough distribution Bay Area-wide that respects the looser definition of “neighborhoods,” and does not impose strict racial segregation, as in this image by Eric Fischer, using red dots representing whites, blue representing blacks, green representing Asian and orange Latino populations, in trying to prevent  overlapping and blending of color-points,  and better to define neighborhoods as an ethnic or racial enclave:

Racial Map SF--25:dot Eric Fischer

Fischer seeks to respect Bill Rankin’s cautionary words that boundaries of neighborhoods are never so stark as on informational graphics, and that a cartographical index of one dot for twenty-five people is better able to allow “transitions also [to] take place [registered] through gradients and gaps” in the map’s surface, suggesting an urban geography without clear boundary lines, clear spatial differentials clearly emerge across the neighborhoods of Oakland, CA:
Oakland Alone--Fischer

And while the city was once historically predominantly black, or African American, in its population, one still found clearly define enclaves of blacks that are, sadly, starkly isolated in census blocks, based on results of the 2005-9 U.S. Census:

2005-2009 % Afr Am Oakland

One can map, in relation to the racial composition of the city, the relative percentages of kids in public schools, one index of its community, and the stark dividing lines created by some of its highways and major roads, which divide the regions of the hills from the flats, where few kids attend private schools.

Elementary School Kids in Private Schools

This is given much further definition by the map of those who have completed high school, already used in in my earlier post in a slightly different version, which suggests a chasm between cultures of neighborhood far deeper than race alone.

High School Graduation

Perhaps the starkest underpinnings of this cultural divide is a map using the 2010 Census to define an ESRI visualization, of the city’s divide in income levels in the city and outlying areas:

oakland's Income in bay Area

Which one can zoom into for the City of Oakland, revealing a clearer divide in incomes around  Highway 24, still using Census Blocks, that again reveals some intermingling albeit with sharp divergences in Oakland that stand in sharp contrast to the larger Bay area:

Median household Income East Bay-Oakland in it

To track a deep change in the population of the city that occurred in only recent years,  Pietro Calogero tracked racial displacement from many neighborhoods that illuminate this divide in incomes, around the aftermath o California’s housing crisis.  The map of foreclosed real estate in west and southeast Oakland, the former “industrial areas,” which stand in sharp contrast to wealthier areas in the hills, to illuminate an economic ravaging of the city that shows up in no other way in a simple map–and indeed masks innumerable individual stories of foreclosure and moving out:

Foreclosures OAK

Although perhaps the map of foreclosed houses is difficult to tie to race, Calogero comes closest to revealing stories with a map in choosing to map how African American families were in fact disproportionately effected by foreclosures, and how former African American neighborhoods were gutted from the inside out as residence became unsustainable:

African Americans and Foreclosure in Oakland

The effective narrative of racial displacement that these dynamic maps isolate and present is not only compelling, but raises questions of social justice–and perhaps of social justice and urban mapping.   Despite the broad interpretation of displacement, both when occupied by owner or purchased as an investment, the clear overlap between categories of race and foreclosure seems not only unjust, but a deep crisis, underscoring and mirroring the deep segregation that continues in so many American cities.

And the repercussions of this sort of segregation are evident in the apparent disenfranchisement of despair, revealed in this simple map of voter participation that Ofurhe Igbinedion so astutely thought to create from Alameda County electoral data, which shows a valley of voter absenteeism in an area where the 2010 voting held low potential or positive prospect:

Oakland Voter Turnout

(Igbinedion’s striking–and dismaying–map, reduced in size above, may be viewed in far greater detail here, and will be posted in full with a commentary at

The huge fall-off in turnout among the same population of a territory of disclosure suggests a political disconnect scary in its dimensions, if sadly typical for most American inner cities.  But the cavities of voter turnout in an election for which turnout was itself particularly high–or just short of 75% (74.52%)–suggests a sense of a politics of abandonment.  What, indeed, did the election accomplish for a large percentage of the city?   What resonance did the candidates even hold, or could they hold?  The topography of disenfranchisement is arresting if not puncturing of a vision of a city united in its neighborhoods, and sort of undoes the unity of its own mapping of continuity.

It is a sort of inversion of density.  Mapping the density of population in Oakland by census blocks reveals not only clear neighborhood divides but a uniquely geographic dispersal of demographics, most dense between the freeways and thinning out to the hills and the flats:

Oak Pop Density

There may be real reasons for not living by the shore below the freeway:  the area is not only late-industrial, but the ships spewing sulfur dioxide and pollutants exceeding standards for vehicles that are registered in the United States create a spew of particulate matter over the downtown area not confined to West Oakland, but reaching in to Chinatown, Emeryville and the Downtown area, areas downwind of the port, in this truly terrifying map, posted in 2013 by Sarah Brady and Alfred Twu, and charting the sulfur dioxide and particulate emissions of ships, using the Port of Oakland Emissions Inventory:


The map reveals regions with air pollution up to 10 times the national average a couple of miles from the port, but whose effects increase risks of cancer and asthma extending twenty miles inland, creating a poorly-known map of particulate matter as an argument to raise pollution standards in Oakland’s port.  Notwithstanding the much-vaunted clean-up of the Port of Oakland, which were aimed primarily at legal safeguards at the level of diesel particulate emissions–emissions that have been largely blamed for sever respiratory problems among local residents–which have indeed decreased from 261 tons to some 77 tons in seven years. (If this was a reduction of 70%, the stated goal of the Port is to further reduce the emissions by 80% by 2020; since July 2009, ships have been required to use low-sulfur fuels within twenty-five miles of the coast, however, and the sulfur-dioxide emissions tied to asthma are not likely to decrease.)

Perhaps it’s not uncommon to value (and inhabit) property away from the shoreline.  Examining relations between elevation and population density in the wake of the shifting consciousness of the relation between water-elevation and land-use after Hurricane Sandy, Stephen von Worley offered the following interesting alternative visualization mapping elevation and population density on a spectrum moving from white to yellow to orange to blue, to show the sharp divide between hills and flats in the East Bay:

Stephen Whorley, Elevation and Poopulation Density (2010)scale von whorley

A nice register of how this space is actually used or perceived, and, equally important, moved through, based on a collation of the adjustments to Open Street Maps of the city, suggests the well-travelled nature of Oakland’s major arteries and downtown roads.   How might this be registered in the surface of the map? is a question that is nicely resolved in this map of Oakland’s self-mapping of its major roadways.

Oakland, McConchie-every line, every point- OaklandAlan McConchie–Stamen design

The Open Street Map view of Oakland, rendered so distinctively by Alan McConchie, tells a perfect story of the inhabitation of Oakland’s space by its routes of mobility, recalling the sort of GPS-derived maps increasingly common from artists like Jeremy Wood, who practiced “drawing with GPS” as a line of work:  it would be interesting to be able to map street-use at different times of the day, if possible, though deriving data of the abandonment of downtown Oakland when dark is undoubtedly difficult.

The divergence of nighttime and daytime is evoked, if not measured, in Michal Migurski’s brilliant layering of a “heat map” of crime–based on police visits per unit of time–over an OSM template, both layered with a semitransparent streets that interact smoothly with the underlaid data; the combination of layers effectively allowed Migurski to adapt a heat-map of crime to downtown Oakland, using police visits per unit of time as a metric as part of his active and for its time particularly innovative Oakland Crimespotting, in the hope that the HeatMap APIs won’t obscure either context or specifics, and provide a legible text.


One could argue that this mapping of hot-spots excessively illuminates those areas of BART stops, where more police calls would tend to occur–and, in the case of 12th street and downtown, more street folks congregate.  But the increased number of calls provides a basis to register local attention to crime and property protection, or how the city sees itself.

And how Oakland maps its own crime, or tends to monitor its own possessions, is foregrounded in this striking map of the downtown density of security cameras, often placed in response to fears as much as evidence.  This final map of the installation of security cameras downtown points up the increased anxieties of its safety, almost in response to and the perceived need to monitor public life, and registers the odd dynamic of a downtown business zone that has few residents, and whose topography of suspicion vastly changes as one moves from daytime into night–when downtown is increasingly abandoned by workers or street populations.

We’re clearly fascinated by the different images of the city’s different composition and divides, and in understanding how best to work within them, or to heal them as best we can. The mapping of security cameras–if focussed in the downtown area–reveals a sense of deep divides, and a perceived in security, no doubt partly voiced as inadequate police coverage among businesses, as much as the city’s residents.  This map, also a mirror, in part doubtlessly contributes to the image Oakland projects, an image that is underscored by deep divide Eric Fischer revealed in his remarkable ‘Bay Area’ map of photographs uploaded by “tourists” v. “locals,” red v. blue, in a database that charts a tale of the visual interest of two cities:

Eric Fischer- Locals v non-Locals in SF:Oak

There are many other, more positive maps of the city’s populations, no doubt, and other mirrors that reveal great changes in the city’s diverse communities.  But only by understanding the lay of the land, as it were, and situation of these communities, can we hope to understand the unique challenges that the city faces.

The ambitious investment by a generous benefactor of a whopping $34 million in Oakland’s job-training and education efforts in the summer of 2015 may be the start of a broader investment in what the city has to offer.  The distribution of needed resources by the San Francisco Foundation seems both brave and smartly apportioned:  the decision to focus on specific neighborhoods, and improve the access of those regions to both in-school training and potentially productive housing to public health and from public instruction to community arts groups seems a good one, and breaks down along lines that the city could use, with East Oakland getting an important and much-needed injection:


If many public services are lacking in Oakland–and the poor fit between local economy and job-training has been endemic to much of the city–this seems at least to be a fortunate and very well-intentioned start.

The huge impact on introducing training and resources for early childhood education, trauma and health specialities, and, in part, conflict resolution, provides an important start to break from the deep divisions that have long been present in public education, and the lack of needed resources for many public schools not located in neighborhoods that are able to subsidize or assist needed programs.

Impact on Oak Schools


Filed under mapping racial segregation, Oakland

Mapping Populations in the Open Seas

Eric Carle commemorated the tragic story of the 1992 loss at sea of some 28,800 rubber ducks from a container ship in Day-Glo colors in “Ten Rubber Ducks Overboard.”   But rather than encountering multiple marine creatures in their adventures, the orange rubber children’s bath toys were in fact carried on quite circuitous routes of nautical travel:   after leaving Hong Kong, individual ducks migrated over fifteen years along ocean currents across the polar regions to as far West as the islands of the Hebrides and eastern France, or as far South as Peru’s coast.


Rubber Duckies


We don’t know the exact numbers, but at least several seem to have avoided, happily, the treacherous waters of the Northern Pacific Gyre of the Great Pacific Garbage Patch–which sadly remains the unfortunate fate of so much plastic substances and waste–where a large portion no doubt lie.




Carle took poetic license to reduce the ducks to ten in his 2005 board book, leading them to meet  seagull, geese and whales on their picturesque voyages in the seas.



Whereas Carle offers readers a narrative of charting how the plastic bathtub toys encountered a live flamingo, pelican, sea turtle, seagull, whale and, of course, a group of live ducks, recent maps of ocean populations portray a population that churn beneath one’s feet so rapidly as to challenges a static mapping of the range of its inhabitants–and the changing nature of its populations of the waters, in a range of maps that leave behind the inhabited earth to foreground shifts in the inhabitation of the seas.

Digitized projections narrate the currents of marine biodynamics narrative in a far more three-dimensional fashion than the voyage that Carle charts in charming tissue collage.  Digitized projections of the shifts of ocean use similarly bright colors to visualize the shifts in oceanic populations tied both to global warming and atmospheric pollutants.  They offer dynamic tools to re-imagine the uses of maps, providing a less prosaic narrative of marine residents that the ducks encountered, and give new urgency to the informational (and narrative) content of oceanographic maps–even as they tracked a similar narrative of the scariness of the interaction between the “natural” and man-made.


Carle's Ten Ducks


The dynamic mapping of oceanic populations suggests ways of responding to the shifting climates of oceans–rooted less as bucolic preserves of nature or wildlife, than as spaces actively reshaped by the human presence and industries.

The visualizing the increasing ‘jellification’ of oceans, created by both global warning and the effects of modern industry, has gained increasing attention as the increasingly abundant populations of jellyfish  floating along the currents of ocean waters have begun to be mapped, and the permanence of their presence in the oceans begun to be assessed.  The overcrowding of jellyfish in the ocean waters have led oceanographers to worry about the impending ‘jellification’ of the seas that would only spare the Peruvian coasts, and a veritable swarming of jellyfish not only in China, where they might be eaten, the northeast waters of America, the Mediterranean, and Alaska but around the Antarctic:




The wide blooms of the jellies bode not only bad news for swimmers’ jellyfish injuries, and led to record numbers of those treated for stings–in Barcelona, upwards of 400/day–but to fishing economies, as the proliferation of the stinging blobs that can cope with increased pollution, murky waters and algae blooms more than other ocean inhabitants, and threaten the food supplies of fish in overfished waters, by competing for zooplankton, as well as nets of fishermen.  They flock in large numbers to polluted waters  and overdeveloped shorelines with specific intensity.

Among the prime beneficiaries of global warming, jellyfish blooms lead to the release of toxins to oceanic areas and enclosures of farmed fish, jellyfish invasions are described by oceanographer Josep Maria Gili as a simple message of the oceans to mankind: “Your are destroying me.”  Driven by currents and carried in the ballast water of tankers and container ships, jellyfish not only displace local populations, but face reduced predators, including, potentially, the monster jellyfish Nemopilema nomurai, with its six-foot bell diameter.




Despite considerable worries that there is actually more plastic than plankton in the ocean, suggesting less mutually convivial relations between synthetic objects and marine life than Eric Carle would have:  indeed, oceanic gyres where plastic products tend to be trapped–and some of the ducks no doubt resulted–swirling around in a region twice the size of the state of Texas, that might in time form a destination of disaster-tourism of its own.  In the gyre, plastic refuse often outnumbers marine plankton by an astounding and terrifying factor of six to one.




As much as mapping the distribution of plastics in the ocean, ‘mapping’ plankton populations provides a snapshot of varied distributions of these microscopic inhabitants of the ocean’s expanse.  The mapping of the larger plankton populations congregated on the poles, and pteropods in the most crowded seas–as well as huge “dead zones” where oceanic plankton recedes–in a complex mosaic of local ecosystems, evident in the computer-generated MAREDAT distribution of photosynthetic plankton, and showing the abundance of zooplankton, that do not use photosynthesis, in comparison to photosynthesizing phytoplankton, and a range of plankton varieties:



A smaller-grained image of a phytoplankton distribution creates a wonderfully iridescent map of plankton’s oceanic presence in this global distribution of chlorophyll producers–until one can read its legend, or grasp the low levels of populations in areas of the deepest blues, near to the equator.





This spectral map of plankton distributions conceals the  shifts with seasonal variation, but one can see in these images of plankton populations (based on data generated by NASA’s MODIS instrument) that the distribution of these mostly oxygen-producing microorganisms has higher presence in colder climes, removed from most human effects, where their higher quantities are registered as yellow–in contrast to the absence of dark blues.   (The entire plankton atlas database is available online.)  The shifts of phytoplankton is marked by a seasonal ebb and flow, however, almost echoing a tidal chart, whose annual flux is tracked in speeded-up time in this digitized “map” based on satellite registrations, in this holistic time-stop graphic of the oceans’ smallest inhabitants.



The above visualization echoes the distribution of sea-surface chlorophyll, now averaged out from between 1998 and 2006, to reveal the rise of large “dead-zones” poor in plankton in the oceans, which bode poorly for waters furthest from land:

sea surface chlorophyll


Regionally, plankton favor colder waters, but its growth is stimulated and nourished, as this map of levels of chlorophyl worldwide in  September, 1988, which shows the autumn northern sun nourishing a band of chlorophyl plankton, when southern seas are just begun to bloom:



The result is a visualization in which, even in a flat projection, one can see land and earth alike teeming with life, as a SeaWiFS instrument scans the world’s oceans for phytoplankton even as it scans the earth’s surface to look for plant life, by measuring the global circulation of carbon in order to track photosynthesis on land and sea like:


NAS MAPS PLANKTONNASA Scientific Visualization Studio (2001)–SeaWiFS (Stuart A. Snodgrass)

In this synthetic global view, the dark blue areas of low plankton are similar to the aridity of orange deserts, which also provide no chlorophyll–or oxygen–to the atmosphere.

Somewhat similar seasonal variations are nicely revealed in relatively recent visualizations charting their monthly distributions in the Mediterranean, whose warmer waters of the summer (from May to October) especially diminished the plankton populations in its southern edge, closer to the equator, when the north African coast seems to lose its populations, only to be replenished by January, in a set of images that reveal the variability and resilience of local populations:


chlorophyll med


The increased limits of oceanic zooplankton suggests the shifting nature of the oceans, and their close relationship to our atmosphere.





But it does not measure their variability–or the specificity of distinct plankton populations that far off waters and streams hold, and their lack of discrimination weakens the effective understandings of oceanic biodiversity they communicate.  New tools for visualizing these unseen micro-populations that generate so much oxygen on our planet were developed to visualize specific plankton distributions, first prepared for San Francisco’s Exploratorium, based on plankton variety, producing a map of greater discriminating power.  The user-friendly map “Living Liquids” was planned by Jennifer Frazier with a computer scientist and help from the MIT’s Darwin Project and the Center for Visualization Interface and Design Group at UC Davis, to create a map of plankton distributions that visitors to the Exploratorium could explore.  Living Liquids began from a fluid base-map of varied regional phytoplankton distributions that focussed viewers’ attention on the oceans as a site of rich chromatic and ecological variations, without discriminating between them, to encourage exploration:


Plankton Visualization

Plankton Legend

The images of such large expanses of declining populations of plankton paint an unpretty picture of our oceans, that parallels the fear of jellification of ocean seas, but also allows us to “see” a richly variegated image of where plankton live–and what type of plankton live where–that provide a clearer holistic image of oceanic populations, using an interactive touch-screen to zoom in on close ups to reveal and explore qualitative diversity within the distribution of local plankton populations with more immediacy than a four- or five-color map allows, creating an illusion of being able to scoop up a handful of water at any place and view it under a microscope, switching registers of visual investigation and exploration.

Plankton View 4

Plankton Viewer 8

Plankton Viewer 6

The complex visualization of the nature of micropopulations is dramatically distinct from a static map; its actively  readable surface is a tool of independent investigation in itself.

Local maps of ocean populations also provide crucial tools to frame an exploration of causes for the local variability in such microscopic micro-organisms that examine the specific impact of local industrial change on the living landscape of the sea.  If not three-dimensional, such maps chart a nuanced picture of the biodynamics of marine diversity than the static maps of marine life, and powerful tools to register shifting temporal distributions and densities in the boundaries of specific oceanic populations.

To select but one example of oceanic maps of the impact of human life on biodiversity, let’s start from the dangerously low oxygen levels in the Gulf of Mexico–caused in part by marine pollution.  The massive changes in the Gulf’s waters afflict both deep sea populations and phytoplankton alike, has created a “dead zone” of diminished distributions that by 2009 increased worries that pollution–largely caused by fertilizer run-off that augments the presence of nitrogen in the waters and create algae blossoms–and may eventually lead to a local ecosystem collapse.  (The so-called “dead zone” came to occupy an area larger than the state of New Jersey, before ocean currents changed its shape.)  Similar “dead zones” threaten to expand near the habited shore world-wide, increased by global warming.



Yet concerns for the growth of oxygen-deprived regions worldwide, paralleling oceanic jellification, create conditions for the abandonment of waters by fish and shrimp alike in “hypoxic” regions, whose number has doubled every ten years since the 1960s, with huge economic consequences for regions as the Gulf of Mexico, whose hypoxic conditions are colorfully mapped by red below during the previous year:




Which brings us back, almost full-circle, to the rise of global populations of jellyfish, and maps onto a change in the population of the open seas.

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Filed under chlorophyl plankton blooms, hypoxic regions, Interactive Maps, jellification, Living Liquids, mapping hypoxic regions, mapping jelly fish, mapping sea surface populations, marine biodynamics, Marine mapping, oceans, oxygen-deprivation, phytoplankton, plankton maps, rubber ducks

Mapping the Expanse of our Health Care Debacle

There have been compelling suggestions that racial categories and racism are rearing their ugly heads in the debate over healthcare.  It’s telling that Atul Gawande has likened the attempts of conservatives to persuade folks not to sign up for health care exchanges not only as “advice that no responsible parent would ever give to a child,” but to an obstructionist tactic that recalls resistance to integrating schools after Brown v. Board of Education under the distorting misnomer of “freedom of choice.”  As Gawande notes, courts had to intervene to prevent such retroactive obstructions, much as the Voting Rights Act had been designed to allow courts to intervene in obstructions of the right to vote in similar regions.  And Gawande is not alone in finding that the mantra “defund Obamacare” that is sponsored by “almost exclusively white members” who were elected to represent “bright red districts” to be fueled by racist hatred and to be a cover for deeply racist fears.

The majority of poor uninsured reside in 114 of the 3,000 counties in the nation, and of those 52–just under half–have created obstacles to access to health care.  It is telling that almost half of the counties with uninsured populations lie in states that have not accepted the expansion of health care under the Affordable Care Act:  from Texas to South Carolina, state legislatures have created obstacles to its adoption or implementation, rejecting funds needed to expand Medicaid programs–as have twenty-five states–or even to sponsor health exchanges in their states to make programs available as options for health insurance through the Affordable Care Act.  Both such runarounds do disservice to their populations, as are the attempts of other states to limit the possibilities of access to health-care “navigators” who assist people with enrolling at local health-care centers:  states have independently set up obstacles mandating criminal background checks, fees, exams, or additional course work to sabotage folks from selecting health insurance, and in so doing perversely perpetuate the gaping pockets of inequalities in the current status quo which a map divided by the percentage of populations receiving Supplemental Nutrition Assistance Programs (SNAP)–one important indexed of the uninsured–reveals.


SNAP map


The divides within the southern states of America, where a consistently large proportion of the numbers of uninsured reside, suggests something link a deep valley deeply entrenched within the national landscape but rarely appreciated or explicitly mapped.  When Sabrina Tavernise and Robet Gebeloff examined the results by mapping the refusal to accept an expansion of insurance or even Medicaid against census numbers of poor and uninsured in The New York Times; the coincidence between lack of insurance with refusals of government funds for health care was so frightening that it merited a follow-up editorial on the injustice of blocking health reform–asking how we can accept placing at risk the most vulnerable in our society, including uninsured single mothers, children living below the poverty line, and uninsured low-wage earners, according to data also coming from the Kaiser Foundation.

The interactive four-color map used estimates provided by the 2011 Census Bureau‘s  American Community Survey to reveal how the twenty-six states refusing federal funds (through Medicaid or assistance to buy policies) are also distinguished by terrifyingly high levels of poor or uninsured:


% Uninsured in States Saying No

legend- Poor and Uninsured Americans


As the Times noted, this includes all the Deep South save Arkansas.  The twenty-six states, whose governors or legislatures have intentionally hampered the implementation of the Affordable Care Act, have seceded from federal health care reform, by taking advantage of the Supreme Court’s decision that the expansion of health reform was optional, and not able to be federally mandated.

It scarily mirrors the states whose populations of uninsured exceed 8% of their total populations, or where suffering from poverty and inadequate heath care is most intense:


8% poor and uninsured

legend- Poor and Uninsured Americans


To be sure, much of the arguments against the ACA are rooted in the fear that the act will be a nail in the coffin of the United States as we know it and lead to an insurmountable increase of national debt:  but the paranoiac fear that its perpetration is so short-sighted that it is intended to prevent a return to smaller government has deeper roots.

The depth of local opposition to the ACA follows a deeply disturbing map of national disparities.  Indeed, the refusal to implement the law reflects disturbing ties to the sort of census data on large numbers of African American populations, if one compares the distribution of this refusal to the one-to-one mapping of our population provided in the “Racial Dot Map” designed by the statistical demographer Dustin Cable, who used data of racial populations across national census blocks as measured in the 2010 Census to provide a “snapshot” of the national population.  The map assigns each inhabitant a single dot, colored by a collapsed category of racial self-identification.  Mapping the same data on racial classification alone, using a more simplified classification of racial identity than the census itself, reveals an eery echo of deep segregation among those regions rebuffing the plan for national health care:
SouthWest Dot Map with Names

The disturbing nature of this coincidence, while not measuring to poverty or to low wage earnings, reveal a scary image of the very regions that are ready to spurn federal assistance for the uninsured members of their populations.

Indeed, a focus on the Deep South in Cable’s map, here presented with place-names to render it more legible, reminds us of the relatively clear boundaries in many of these regions among areas which are populated by “whites” or by “Blacks” and “Hispanics”, and a focus on the Deep South reveals the striking nature of the lack of integration in counties that single-mindedly stubbornly refused to expand health care.
Dot Map in the South


There are, to be sure, serious criticisms that can be leveled against the categories retained by the census or instantiated within Cable’s map.  But the  esthetically appealing rendering of census data in the Racial Dot Map reveals some deep divides in our nation’s fabric which may well lie at the heart of the refusal of accepting a mandate for health insurance, even though the refusal is regularly framed as an issue of states’ rights or resistance to federally imposed exchanges of health care.

Indeed, even when stripped of place-names, the distributions that the demographer Cable extracted from the data in 2010 Census blocks creates something of a graphic counter-prompt to the assertion of states’ rights that justifies for such recalcitrant and obstructionist refusing to expand health care:


SouthWest Racial Dot


Although the Racial Dot Map is not an exact tool, and randomly redistributes an average of individual color points within census blocks, we might compare the gross level of integration, which only generalize racial characteristics of a population, to urban areas on the Eastern seaboard:


Eastern Seabord and MD Dot Map

While gross data, and hardly refined as an image of how we live, the contrast with the clearly segregated boundaries of isolated cities suggest a topography of not only racial, but social distancing, and one in which one might imagine anger directed toward the devotion of federal monies to those in need.

Of course, the story is not all bad–even if the crafty recalcitrance of these twenty-six states threatens to erode its ability to reach the most needy among us.  For the profiles of counties within states that have accepted the expansion of course contain uninsured who can be expected to benefit greatly from it–most notably in Arkansas, the one state in the Deep South to accept the ACA–and New Mexico, as well as the more rural areas of California’s central valley, rural Virginia, and the Northwest.


% poor and uninsured in state accepting expansion
legend- Poor and Uninsured Americans



The government shutdown from the start of the fiscal year has prevented many Americans from enrolling for health care online, as was long expected to be possible.  Many will, as a result, rely on filling out paper long forms when seeking to enroll in the program most suitable to them.  But the government shutdown may be a smokescreen meant to cover the obstructionism that the expansion of healthcare, as well as a tactic to delay its final implementation–both since the attention to shutdown has absorbed the 24 hour news cycle, and detracts attention from obstacles to the ACA’s effective implementation.  The shutdown seems to appeal not only as a stunt, but as a final line of resistance to providing universal health care, for a contingent convinced that it will be actually impossible to repeal “Obamacare” once it is enacted and goes into effect.

The mean-spirited nature of this obstructionism is revealed once one examines who will be hurt by a refusal to put the ACA into full effect.  Indeed, a  state-by-state examination of the distribution of non-elderly uninsured across the nation offers a somewhat terrifying profile of troughs of national inequities with which we have yet to contend.  Take, for example, the deep pockets of an absence of insurance among populations in South Carolina:


South Carolina



Or, even more scarily, perhaps, the deep trough in much of central Florida and the panhandle:





While the entire state suggests a massive picture of uninsured, the central region is dominated by huge numbers of uninsured, which the governor stubbornly refuses federal insurance:


Central Florida


An even more grave disparity of access to health care is revealed in Alabama as a belt across its more rural areas:


Alabama's Belt


The divisions in Arkansas are almost a belt around Little Rock:




Or a dismaying divide within the rural areas of Georgia, where Atlanta seems something like an island of access to insurance only in its best neighborhoods, but swamp-like regions of uninsured spread out at its northwest and southeastern edges:



And, in a particularly terrifyingly unethical mosaic, the disparities between rural and urban Texas appear particularly strikingly stark, and reveal a deeply historical artifact of income disparities and economic livelihoods across the state:




One could continue almost ad infinitum, covering the ground of the United States as if it were a map coextensive with the nation, but one doesn’t have to struggle much to grasp the depth of disparities and the dangerousness of perpetuating such deep divides in access to adequate health care.

When one speaks of two nations in America, divides between red states and blue states mask the depth of divisions between the uninsured and insured, and reveal the increasing difficulty of the blindness of one population to the other.  Discounting populations whose lack of adequate health insurance is, in essence, naturalized as part of the status quo may provide the clearest illustration of the persistence of racism in America.


Filed under Affordable Care Act, Deep South, Dustin Cable, Obamacare, Racial Dot Map, Voting Rights Act