This post starts with an exploration of what happens when bloggers don’t source their material (in this case, maps), but ends with a cool discovery of a resource for all you dasymetric mappers out there (you know who you are).
Earlier this month my wife forwarded me a link to a Gothamist Map of the Day — see below.
The map is interesting (though somewhat problematic) in several ways. But what struck me about it is that: 1) I definitely had seen it before, but 2) there was no attribution at Gothamist – no indication of what time period the map covered, who made it, the source of the data, etc. So, a cool map, but zero context and no way to verify it or really understand what the map was telling us.
Sure there was a link to the “source” — but this just took me to Buzzfeed, where someone had posted the map, also with zero attribution or any other context. (One of the commenters at Buzzfeed says that “this is the most frustrating thing about buzzfeed— they fail to attribute a lot of stuff properly.” Someone responded to this commenter noting that “it is annoying sometimes [providing no attribution], especially with stuff like this chart which is supposedly based on some facts” (my emphasis).
Another commenter at Buzzfeed has a link to doobybrain.com which claimed the map (or, “infographic” as doobybrain described it) was from a 2007 issue of Time Magazine, though the source for the doobybrain item was another blog post. (In the world of web anonymity, the doobybrain source is misterstarfish.typepad.com from haj718(at)mac(dot)com .) Alas, misterstarfish/haj718 offers no attribution or context either.
I looked around a bit on Google and Bing to see what I could find, but didn’t turn up any other useful references (I found a few other blogs and graphics sites that had re-posted the map, but no details). I even commented on the Buzzfeed piece, but no one responded with more info.
Then I happened to have a conversation last week with the director of Urban Omnibus, an online project facilitating a conversation about New York’s architecture, planning, development, and all things urban. He mentioned in passing the “map” tag on his site, I clicked it, and struck gold. Earlier this year (March 2009), Urban Omnibus published an interview with Joe Lertola titled “Let’s Talk About Maps 2” (the first installment of Let’s Talk About … being an intro to the column). The interview highlighted Lertola’s work at several publications, including Time Magazine, and of course included the “Day and Night Population” map along with a brief description from Joe. Mystery solved! … mostly.
I needed to visit Lertola’s website directly to find out more, and it turns out he did create this map for Time in 2007 (the Nov. 26, 2007 issue, to be exact – click the “City Population Shift” tab). But it was part of an overall layout that highlighted portions of several cities across the US, and the “NYC” graphic was just an inset of a larger graphic — which is why it only focuses on lower Manhattan (not all of New York City, as several blog commenters pointed out).
But even Lertola’s website and Time itself didn’t provide more precise details on the data source. The original Time piece lists the sources as:
Census Bureau, Bureau of Labor Statistics; Texas Transportation Institute; Oak Ridge National Laboratory/UT-Battelle LLC.
Lertola’s website goes a bit further, noting that:
the Geographic Information Science and Technology group at Oak Ridge National Laboratory has developed LandScan USA, the most detailed population model available. By integrating Census data with extensive information on other daily activities, LandScan can predict the population of any U.S. location at any time of day.
Aha, a searchable term – LandScan! It didn’t tell me data vintage or anything like that, but at least I can go to the source. And the results are intriguing. The LandScan website states that
LandScan USA is more spatially refined than the resolution of block-level census data and includes demographic attributes (age, sex, race). The model includes development of an “ambient population” (average over 24 hours) for global LandScan and development of spatial distributions for “residential or nighttime population” as well as for “daytime population” as part of LandScan USA. Locating daytime populations requires not only census data, but data on places of work, journey to work, and other mobility factors. The combination of both residential and daytime populations will provide the best estimate of who is potentially exposed to ambient pollutants.
In other words, the data claims to address two interesting GIS issues related to demographic analysis: dasymetric mapping (modeling population patterns for smaller areas than typical Census geography, which allocates population across an entire tract, say, regardless of where people actually live within that tract) and daytime population (Census population data correspond spatially to where people live — i.e., the population at night — rather than where people work or shop — i.e., the population during the day). Each of these issues is compelling for a variety of policy areas, spatial analysis theory and practice, and creating cool maps.
Needless to say I’ll be emailing the keepers of the data (Oak Ridge National Lab at LandScanTechnical@ornl.gov) to find out more. If anyone has any other leads, please let me know.