Jennifer Hyndman gives @UKGeog Semple Day Lecture

Semple Lecture Poster

The Department of Geography’s 44th Annual Semple Day Lecture was given this year by Dr. Jennifer Hyndman (York University, Toronto). Her topic was “Refugees on the Edge: ‘Distant Suffering’ or Domesticated Distance?”

Here are some pics. (A video of the talk will be posted shortly.) Thanks Jennifer!




Pictures from other people of the awards ceremony later that evening:

Laura Greenfield (Geography) with her Pauer Award for best Mapping Project with Matt Wilson.

Emily Kaufman (Geog PhD student) delivers the laughs with some fresh #flatcomics!


Consider Smell: Arctic Edition

Great event in Alaska if you’re in the area! “Consider Smell: Smelling Imagined Geographies through Time and Space.”

The Smell of Evolution

Kara C. Hoover and Julia Feuer-Cotter

4 March 2016. Anthropology Colloquium in Bunnell 405 from 3-4:30
Consider Smell: Smelling Imagined Geographies through Time and Space4 March 2016. First Friday at Ursa Major Distillery from 5-8pm
Join us for a multi-sensory experience that opens the nose to engage deeply across the senses via multisensory molecular cocktails with locally produced spirits, neurogastronomical foods, and interactive art that imagines other geographies. Art pieces range from molecular rendering of olfactory signaling, photography enhanced with bespoke smells, interactive sculptures, crowd sourced smell maps, and smell masks which explore another person’s reality through the nose. This series of works explores the synergy of art and science via the sense of smell. Kara C Hoover uses the nose as an environmental probe to explore smelling across time and space. Julia Feuer-Cotter explores how this environmental perception is enacted in Alaska’s recent past through cultural practices along the Dalton Highway.


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ICA/Esri Cartography Summit


I’m just back from Redlands California (Esri HQ) and 3 days of a “Cartography Summit.” This was a small meeting considering the future of cartography and mapping, divided into three topics: Data, Design, and Media. I gave a lightening talk on “Designing Geoprivacy in the Age of Big Data.”

There was great back channel on Twitter, and you can sort through the tweets there with hashtag #cartosummit. The talks were also livestreamed and recorded for later playback, and I think the slide decks will be available. They key tweeter was Stephen Smith, @themapsmith, so just check his TL for details.

Esri generally was discreet (this wasn’t an Esri-themed event after all), Jack dropped in occasionally, and it was nice to be in 85F (dry) weather for a few days.

Here we are!


Building age maps

This was the year the building age map broke into the mainstream. Or maybe I’m just saying that because I chose to use the challenge of making one as the Final Project in my intro GIS and mapping class. Nevertheless, there are increasingly many examples available. In my estimation, their mix of colors provoke a captivating aesthetic almost like a Chagall stained glass window.

The first one to draw my attention was the Dutch building age map. Covering the entire country, it includes an incredible 9.8 million buildings!

The latest one is also interesting, though a read of the small print reveals it is not strictly a building age map.


“Modal” building age

This is the area around Cheltenham and Bishop’s Cleeve where my mum lives. Here, blue indicates older housing and red is newer (an opposite scheme to the Dutch map, and one that doesn’t strictly conform to cartography textbooks–or Edward Tufte’s guidelines of one symbolic dimension for each data dimension). Beware this note however:

Important note: Classifications are an average across the local area, rather than for individual houses, therefore the colour coding on a building is not necessarily indicative of that building.

There’s also a lot of missing data where building age is not captured. Looks like the Brits still have some way to go to catch up with the Dutch!

In my class project, students created an overall map of Lexington, KY building ages as a first step. For the second step, they chose a block or hyper-local area and supplemented it with other data they collected or created. This way the project balanced a sense of structure with a sense of freedom (students are often stymied by too much freedom and revert to mundane projects such as mapping bike racks).

It’s tough to choose an example here as they were all very good (and we’ll be posting them all as pdfs on New Maps soon!) but here’s one that achieves a particularly strong sense of layout, in addition to the great use of color and legend design, as well as a pretty unique way of collecting data.


Final Project by Kelly Jackson and Ben Mills


These are done in ArcMap, not particularly known for its design aesthetic, and so are doubly impressive. On the left you can see Lexington by building age, with the bluer outer suburbs of more recent vintage. In the inset, the students have used a data source called iTreeCanopy, which allows you to crowdsource the presence or absence of tree cover (canopy) from a digital image of an area. Like the Amazon Mechanical Turk, you are presented with an image and decide for each click you make on it whether there is a tree there or not. Do this enough times, and you make a canopy layer of sorts. The end result is a comma separated file containing lat-long points and a tree designation. (For more on the methodology, see here.)

Why not just use a canopy layer for Lexington you ask? Because the available data are nearly two decades old (1998). It would be bad manners to complain about free open data without doing something about it, so hopefully in the long run we can establish partnerships with local data providers where we’ve improved the data layer, at least locally.

Why aren’t geographers talking more about robots?


Robbie the Robot generates 480 pints of whiskey overnight

Why aren’t geographers talking more about robots? This question struck me, paradoxically, as I sat on a panel on robots at the last AAG (see del Casino Forthcoming). While this might seem the last place to have this thought, it was prompted by two things. First, the smiles of slightly startled amusement from people when I told them I was on a robot panel, and second, my co-panelists, who I thought were missing out some important terrain about robots.

Putting aside the no doubt justifiable bemusement that the AAG had a robot discussion, the other topics discussed that day dwelt on sexbots, love dolls, cyborgs and the more-than-human. These are part of, but not the whole story, as Rosi Braidotti’s recent book on posthumanism documents (also putting aside how/if more-than-human is different from post- or transhumanism).

For me, the latter are cultural or philosophical issues, and no matter how pertinent and interesting, they leave aside the political-economic, which is what I’m interested in here. Vinny’s piece (which has just been released by PiHG online first) does partially offer to take up this issue. He does this in the context of a report on social geographies, perhaps meaning that the economic and political are marginal for his piece, which nevertheless remains required reading.

What I mean is quite simply issues around automation, artificial intelligence, and computerization. For me, these point to one thing: algorithmic life. One big part of this is the effect on jobs and wages, and therefore we need to do a better job of integrating tech with geographies of the economy.

Or what I called on the panel “Geographies of neoliberal robots.” Everyone probably has seen a version of this graph:

Looking at some of the economic changes between blacks and whites.

The productivity-wage gap

A version appears in Harvey’s book on neoliberalism. The point is that since the advent of the neoliberal era (say 1970s and early 80s) productivity has not failed to climb, but the amount returned to workers has stayed about the same, creating a productivity-wage gap, which in turn widens income inequalities.

As I said on the panel:

Two explanations are usually offered: “robots ate all the jobs” (people are put out of work by automation), or a deliberate political project by a revanchist capitalist elite (Harvey).

These explanations are not mutually exclusive. What is interesting is that automation and robots may no longer be occurring in only unskilled and repetitive jobs. Research suggests jobs that are more routine and less “cognitive” are the most susceptible to automation. A well-known 2013 study at Oxford Martin School estimated that nearly half (47 percent) of US jobs are at risk of automation. Geographers are not immune:


Source: NPR/Oxford Martin School, Univ. Oxford

Things we can do

    1. Given that we have this listing of job susceptibility, it would be nice to get at least a baseline map of where jobs are at stake. How about a county-by-county map of potential automation? Take all jobs per county and multiply them by the relevant figures in the study. It wouldn’t be perfect but would give us a baseline map.
    2. The PC was Time magazine’s “machine of the year” in 1982. But a one-for-one replacement of a human job with a computer job need not be the most important development in automation or intelligent machines. Rather, production may undergo wholesale reorganization. (Brynjolfsson and McAfee make this point in their recent book The Second Machine Age.) Geographers can contribute to our understanding of this by analyzing which industries are susceptible, and where they are located.
    3. Turning to computerization and automation, I mentioned above that these evidence algorithmic life. What I mean by this is very simple, if you follow Tarleton Gillespie’s definition of the algorithm:

      they are encoded procedures for transforming input data into desired output, based on specified calculations (Gillespie 2014: 167)

      Notice here three useful points: encoding, desire, calculation. An algorithm is that which enables desire to proceed by making (performing) the world as calculative. So it is a capacity-making. Here there would be plenty to look at in terms of uneven geographical outcomes of the work algorithms do in the world, for example on tracking and geosurveillance.

      In fact, Rob Kitchin and his group have just published a useful listing of the ways this occurs. One example likely to be of interest to geographers is automated facial recognition. I really think we need to think “beyond the smartphone” as the only way we are tracked to include ALPR, gait observance, wearable devices/Fitbits/smart watches, and Minority Report style live biometric tracking (face|iris|gait). I document some of these in my piece “Collect it All” as does Leszczynski in her “Geoprivacy” overview.

    4. Beside being part of algorithmic governance, drones (and I include commercial drones especially here as they are predicted to far surpass military drone spending) could be an object of geographical enquiry, or what I call “the drone assemblage.”
    5. Read Vinny’s piece for a more general overview of many aspects of robots and intelligent machines.

      “Where have you been? It’s alright, we know where you’ve been!”–Welcome to the Machine, Pink Floyd

Where can tell me who I am?

In September I published a few musings on the topic “Where can tell me who I am.” This was preliminary for a talk at this year’s SEDAAG meetings. Here’s a link to the talk as delivered and the slides I used are here.

Where can tell me who I am (pdf)

New Maps, New Mappings

The following are my “Thanksgiving Reflections” or statement about our group here at the University of Kentucky. We call ourselves the New Mappings Collaboratory and I had some time over the Thanksgiving break to sit down and try to think what we’re about. I shared these with colleagues and we discussed them at our “Map Chat” yesterday (our bi-monthly meeting of the larger group). Since it looks like we may want to push these four points forward (with the addition of Matt Zook’s suggestion of new kinds of agency in an era of Big Data and algorithms) I publish them here for comments and reactions.


The New Mappings Collaboratory is about the creation of new maps:

  1. New forms of maps.
  2. New ways and practices of mapping.
  3. New ways of thinking about maps (new concepts).
  4. New educational encounters with mapping.

It is not just maps as such, but the event of the map (mapping). We are interested in creating spaces where these new mappings can occur, propagate, and multiply.

As such, we hold to a view of the encounter with mapping as one of maximal openness in terms of technologies, data and thought. We wish to explore material and discursive “digiplaces” and the intersection of virtual, actual and material places.

New Mappings Collaboratory was founded in 2011 by Jeremy W. Crampton, Matthew W. Wilson and Matthew Zook on an equal basis. Sue Roberts suggested the word “Collaboratory” to designate the open and mutually assistive nature of the effort, which has no formal membership but rather interesting/ed people who participate on a loose ad hoc basis.

Specific projects

  1. Histories of critical mapping and cartography. How does the “new” arise and what work does it do? Is the new always recognized as such at the time, and is it a matter of distinguishing itself from the old? Perhaps it is not so much a history as a genealogy that would give us a history of the present. We are interested in this “minor” critical history of cartographic thinking. Specific projects include the Harvard Graphics Lab, landscape planning and Ian McHarg, and mapping as governmental technology, as some of the “new lines” of flight.
  2. Non-representational mapping. We are interested in the performativity of mapping; what work mappings do in the world. Under this project we are investigating the nomadic life of the algorithm and “algorithmic governanceaffective value in geospatial startups, hacking and encryption geographies, and the fragility and transience of the (data) archive (how data are stored, accessed, and distributed, how quickly the field changes in terms of pedagogy). [Fragility also refers to] mutability of forms. CartoDB–Leaflet–Mapbox.
  3. Socio-technological. We continue to investigate the lives of spatial Big Data, technologies and politics beyond the geotag, that is, mapping as “unfolding social relations.” With the advent of the Smart City, Big Data, everywhere sensors and the Internet of Things, we are confronted by new ways of doing business, governance and possibilities of living. How do geoprivacy and geosurveillance operate in this new condition?