How we read maps and dataviz - new research needed?

There's a fairly long academic tradition of looking at how humans interact with maps but, in my view, there is a need to revisit such research in relation to the new wave of digital mapping and dataviz currently available online. Some of it is fantastic and some less so, but this isn't about being critical of the bad stuff. Instead, I'm hoping others will share what they've been doing or what they've seen (via @undertheraedar) to try to understand the effect of new dataviz/mapping on how we perceive/read maps - and what impact this might have on cognition/understanding of underlying issues. 

Early last year I had some discussions about this with a very helpful colleague in psychology at Sheffield - Megan Freeth - and I gave her one of my blog images to test with her eye tracking technology. The results are shown below, in sequence (click to enlarge). I've also put them together in a slide show if you want to download them all at once.

The original 3D image

Scan path from first 10 seconds of map viewing

Scan path for one minute of map viewing

Heat map showing areas focused on most

'Region of interest' analysis

I'm aware that I am probably just not up to date with the kind of research being done in this area but before going further I should say that I am aware of people across the world who have done work in these fields - e.g. Alan M. MacEachren and others at the GeoVISTA Center at Penn State and this study from Brodersen et al at Risø National Laboratory in Denmark - but I'm not aware of what's been done in the last 4 or 5 years in particular to help us understand the effects of new approaches to mapping and visualisation on cognition and perception.

Are we understanding more because of the new wave of mapping and dataviz? Are we understanding less? Are we just enjoying how things look and being wowed by the technology more than we are critically engaging with the underlying content? Has the method become the message?

I'm as guilty as anyone of posting maps and images on twitter and this blog without necessarily thinking too much, though my aim is always to inform and engage - but as the protagonist in David Lodge's Changing Places says, "Every decoding is another encoding" and my visual 'decodings' of spatial data will always be 'encoded' by the viewer in ways I might not have expected - or even want. It's always interesting to see how people interpret things and whether this aligns with what we'd hoped. This perception issue might also come up tomorrow when one of my maps appears in the new HS2 report in the UK - we'll see.

Anyway, thoughts and insights welcome via @undertheraedar.

Filtering Flow Data

My adventures in spatial interaction visualisation continue. I'm currently finalising some more of this work in a paper I'm writing and it gets quite complicated so I've tried to think of ways to simplify the patterns within the vast datasets I've been working with.

The image below shows inter-district migration in the UK for 2001 at different flow magnitudes in a very short animation. This is just one example of the kind of visual things I've been working on recently.

Manchester Commuter Inflows

A short post today on visualizing commuting flows. I've used some 3D GIS techniques to create a commuting surface for the North West of England (based on wards). Areas with peaks represent high in-commuting. Manchester dominates the North West pattern, as seen below.

I added in flow lines to this map in order to see which 'peaks' were being by-passed on the way to Manchester, and from where. The lines on the map below represent flows of 25 or more from individual wards in the North West. Not a huge number per ward, but it all adds up. When you think of how many people are doing this and how far they come it is significant however...

This is only really a rough draft, but it does communicate quite a bit of information and it tells a familiar story of urban commuting. Click on the map to see it in full size.

Geovisualization

Following on from the previous post, I dug out some of my previous work, did a bit of experimenting, editing and touching-up to produce some new geovisualizations. I believe that geovizualisation is about more than just making pretty maps - it is about communicating a lot of spatial data in an effective way, which could not otherwise be easily digested.

In short, geovisualization is part spatial data analysis, part graphic design, part art. In this post, I've tried to use a combination of techniques in order to produce the set of images below. The data displayed is commuting for wards in North West England in 2001. I used a GIS to create the raster images and convert them to 3D, I used some image editing tools to add labels, and I used some more advanced techniques for the colour/grey background focus ones.

Click on the individual images to view in full size at best resolution - the smaller versions below are not super high quality. Areas with high red spikes = areas of high in-commuting and blue = areas of high out-commuting. In effect, the red areas are where people work and the blue areas are where people live, though in reality there is of course some overlap.

Image 1 - Commuting in NW England, 2001

Image 2 - Same image as above, but with labels

Image 3 - Same image, with different colours

Image 4 - More colour experimentation

Image 5 - Colour focus area for Manchester

Image 6 - Colour focus area for Liverpool

Fly to in Google Earth

Another video post today. Some time ago I was experimenting with the latest update of Google Earth, which at the time was (and still is) version 5. The 'Fly to' function allows you to enter a place name, address or other geographic identifier and when you hit search Google Earth flies there. There's a short video on this on the Google Earth pages.

I find these kinds of tools very useful for teaching and helping students think about spaces and places, though not usually at the global level. There is now even a Flight Simulator in Google Earth, one based on a jet and one based on a slower aircraft - lots of fun, but not totally relevant for teaching planning students...

The short video below starts includes the places I've lived in and/or worked in since I was born and ends at the University of Sheffield, where I currently work.

London Commuting Surface in 3D

I've moved on from some of my original flow mapping work of 2008/09 and am now working on different kinds of things. However, I came across some interesting work on geovisualisation at The University of Manchester Geospatial blog which made me want to revisit previous work.

In particular, the reference to a short population density animation caught my attention.

In short, I have experimented with 3D animated geovisualisations - in this instance it is of my London flow surface and flow lines using commuting data. There's a short video below (it may take a moment or two to load - it's a large file).

Connected London

This is a short post about some recent GIS-related work I've been doing. I've moved on from all the original flow-mapping geovisualisation stuff to consider how best to illustrate spatial dynamics for urban systems. One way is a 3D geovisualisation of the kind shown below.

What I did was create a raster surface of net commuting (by district) for the whole UK in 2001 (the latest data). Then I created a flow map vector layer for the UK at district level. Then I chopped out Greater London, displayed only those flows of more than 1,500 commuters, and put this together with the raster layer. The final image communicates a lot of information quite simply.

In the image below (click on it to view full size), the red peaks are areas of high in-commuting and the blue troughs are areas of out-commuting. The flow lines illustrate the spatial patterns of movement. Note the area of high in-commuting to the west of London - the Heathrow effect.