I’ve been reading through a recent book entitled “Qualitative GIS: A Mixed Methods Approach” by Meghan Cope and Sarah Elwood, hopefully I’ll post a full review it soon. In the meantime however, I want to think about one of the sections in it by Marianna Pavlovskaya, specifically her discussion of whether or not GIS is inherently a quantitative tool. I tend to agree with Marianna on one front – rarely do most GIS users directly engage with the quantitative aspects of GIS, use of GIS becomes about spatial reasoning with overlays and logical tesselations of geometry and the impact of visual depiction. On the other hand though I offer a photo of books currently on my desk:

Figure 1: Some books on my shelf

I think there is a serious point here; GIS is a tool- people are happy to use tools to get the jobs they need doing done, I trust an allen key to undo parts of my bicycle without breaking them, and tighten them to a safe level. I don’t however need to know exactly how the tool is made, I just trust I know how to use it. The same is true of GIS, functions such as overlays are tools (in fact this is the exact terminology that ESRI use in ArcGIS), you use tools to analyse maps in a non quantitative way, because you reason and understand their usage; I don’t specifically need to know how the overlay works in a mechanical sense, just that it does. It is generally that case that such tools, even simple tools have a basis in quantitative fields, often mathematics; an overlay is a topological operator deriving from that branch of mathematics.

Now, in a GIS such tools are formed from solving challenges in ‘computational geometry’, and I agree with Pavlovskaya again in that ‘computerisation is not quantification’, except that in this case; that is exactly what it is. There are numerous instances in GIS, shown through point pattern analyses, topological functions and distance decay in which it is clear that GIS is a quantitative tool with a quantitative development.

So is Pavlovskaya wrong then? Well, no. There are different kinds of users in GIS and for the most part users aren’t looking ‘under the bonnet’, to them a GIS is a set of tools, the use of which causes them to construct (make) GIS as a non-quantitative thing. What seems strange is that in looking for opening for non-quantitative GIS in this perspective, the current way of constructing GIS quantitatively had to be challenged, or seen to be wrong and somehow misguided. In my eyes the interesting thing that comes out of this discussion is the idea of abstraction.

In a sense quantitative, or technical, ways of seeing are increasingly being abstracted: bundled and enclosed into something you can think of as a ‘black box’. This encourages engagement as the most common user experience is a qualitative one, as qualitiative experiences for most are more intuitive – generally we have the appropriate skills to deal with such experiences, but may need to learn the skills to engage quantitatively in a complex system such as GIS. Software such as GIS packages have the effect of making previosuly difficult quantitative functions much more accessible, even a measure of straightline distance is a quantitiative function – the Pythagorean theorum, and this can be done in Google Earth and Google Maps which are probably the most accessed GIS in the world (if not also the most accessible). I think the question we have to ask is: what are the tradeoffs in making quantitative functions more accessible, in having them reconstructed as qualitative tools? The obvious answer to this is that when things are conceived as ‘black boxes’ they are exactly that: we have no idea of what is going on inside them. Thus, qualitatively, we have to decide whether or not that is important; in fact for qualitative GIS is may not be that important, as the world is reseen with ‘fuzzy’ characteristics.

References

Cope, M. and Elwood, S. (2009) Qualitative GIS: A Mixed Methods Approach. Sage, London

(much of Pavlovskaya’s chapter also appears in the following paper)

Pavlovskaya, M. (2006) ‘Theorizing with GIS: A Tool for Critical Geographies?’ Environment and Planning A 38(11) 2003-20

Addendum

Muki Haklay often blogs about usability and critical GIS, amongst numerous other things of interest at his blog here.

Here are a selection of the presentation from Day 1 of Popfest 09 that I have enjoyed, or have interested me so far:

Thomas Clemens – University of St. Andrews – “Unemployment, mortality and overcoming the problem of health-related selection: Evidence from the Scottish Longitudinal Study”

Tom gave a really interesting talk, based on a paper he has written that challenges commonly held assumptions in the construction of a robust methodology for longitudinal research. Starting with the idea that there is a correlation between unemployment and health, namely that there is a strong relationship between not having a job and being more prone to illness and inevitably death, Tom enlightened us of the issue of reverse causality in longitudinal research. This issue is this: the researcher has a window within which the status of employment, and health characteristics of a person are evident, within this window there is the possibility of observing a relationship between poor health and unemployment, however it is impossible to say whether this is causal, i.e. that poor health derived from not having a job, or reverse causal, i.e. poor health was the cause of the unemployment. The net result of this reserve causality is the idea that you therefore overestimate the correlation between unemployment and mortality/morbidity. The common tactics here is to enforce a ‘wear-off period’, commonly 5 years, in which observed deaths are ignored in order to account for  the likely effects of short-term health problems (i.e. death or recovery and readmission to the labour force). In his analysis Tom found that the data from the Scottish Longitudinal Study didn’t support the need for a wear off period in the assessment of unemployed status leading to poor health, and that instead adjusting for limiting longterm illness may be a crude but useful way of accounting for the effect of the ‘wear-off period’ in other contexts.

Michael Grayer – QMUL – “Estimation of life expectancy for small areas”

Michael, in a delightfully geographical study, showed how he was able to compute the likely life expectancy for London wards. Life expectancy is a good summary indicator of population mortality, however its appropriateness for small area studies has been, upto this point, challenge by the inherent small numbers problem of small areas, that in a small area with few people a single person can have a large effect on the result. Michael demonstrated this with some examples, showing that small variations in the numbers of elderly people created an uncharacteristic ‘long-tail’ in the survivorship curve for a ward when compared to the expected shape, this artificially raised the estiamted life expectancy for the area. In order to adjust for this Michael introduced ‘Silcock’s Bias correction method’ a mathematical function which seems to have the effect of smoothing the tail of the survivorship curve and creating a survivorship curve of the expected shape. The next set for Michael is to look at applying confience intervals and doing some ward-by-ward comparisons.

Ignacio Pardo Rodriguez – Universidad Complutense de Madrid – “Mixed methods and demography: why, when and how”

I wanted to flag this talk, not because I particularly agreed with the message per se, there seemed to be an advocation of ‘all mixed method, all the time’, but because I think it is an important and fascinating discussion. No one can claim to be unaware of the increasing buzz surrounding mixed-methods, certainly in the world of GIS we have increasing seen it. I particularly like Pavlovskaya (2006) on this very issue, as well as the myriad examples in Public Participation GIS (PPGIS) and Critical GIS (CGIS) and am personally quite interested in the emerging world of ‘critical quantitative geography’ as posited by Mei-Po Kwan and Tim Schwanen (2009 and forthcoming) which elaborate on and break down the quant-qual divide that has been seen to persist since perhaps the cultural turn. Personally I favour an approach which uses the most appropriate tool for the job, be in quant, qual or a bit of both informing the other, certainly I favour the inter/intra – disciplinary working approach which engages the expertise of others, with differing skills to yourself, in order to formulate an approach to methodology. This kind of discussion reminds me of a paper by Bell and Reed (2004) entitled “adapting to the machine” in which the possibilities of mixed-methodologies are expounded in essentially a kind of socratic dialogue.

James Cheshire – UCL – “Surnames as Indicators of cultural regions in the UK”

I work with James, so perhaps it is unfair to expound the virtues of his work too greatly, but I am fascinated by the methods he has used to manipulate and transform surname data and create something actually very interesting and perhaps culturally significant. James uses several different techniques, cluster analysis and Multi-dimensional scaling (MDS) in order to represent the existence of distinct ethno-linguistic regions in the UK. What really fascinates is the time frame, James has data for the 1881 census and the 2001 electoral register, basically millions of names. He seems to demonstrate with this that actually, we don’t move around all that much. In an interesting case study of Corby, James showed how his 1881 data suggested the town of Corby to be ‘English’ and yet in 2001 it was consistently clustered with Scotland, qualitative research on the matter demonstrated that this wasn’t an error, but that a factory had moved into town employing only Scottish workers which had had a long-lasting impact on the town as shown by his analysis. The map visualisation throughout this presentation were excellent.

See James’ blog here.

Fabian Neuhaus – UCL – “Urban Diary – The spatial extension of everyday life”

Fabian’s presentation was perhaps the richest of all in the first two sessions, dealing with the many-fold overlays of people and place, and their activities within the city as a way of understanding and documenting urban rhythms and behaviours. Fabian used the space-time cube, or space-time ‘aquarium’ technique very well to visualise his participants activities and is able to draw on a strong graphic design background to really elicit the maximum aesthetic from his experiments. I was also particularly take by his considertion of different transport modes and the urban experience, as well as his use of mental maps in conjunction with GPS traces. Fabian also keeps a rather good blog, access here.

The references from the brief discussion of mixed methods were:

Bell, S., and Reed, M. (2004) “Adapting to the machine: Integrating GIS into qualitative research” Cartographica, 39(1), 55-66.

Kwan, M-P and Schwanen, T. (2009) “Quantitative revolution 2: the critical turn”, The Professional Geographer, forthcoming

Kwan, M-P and Schwanen, T. (2009) “Critical Quantitative Geographies”, Environment and Planning A, Vol. 41(2), 261-264

Pavlovskaya, M. E. (2006) “Theorizing with GIS: A tool for critical geographies?”  Environment and Planning A, Vol. 38(11), 2003-2020