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Automated interpretation of the spatial distribution of socio-economic conditions
 Dr Jack Massey Principal Research Fellow, GISCA The University of Adelaide, Australia jmassey@gisca.adelaide.edu.au
Abstract
Over the past decade GIS has achieved recognition, consolidation and, for the most part, commercial success. We – the practioners – can be proud that GIS will have a grand future. But what should we do next? I consider it important to identify our big theoretical problems and start to solve them. The big theoretical problem I am trying to solve is the automated interpretation of the spatial distribution of socio-economic conditions through the manipulation of population and housing census data. I am solving this problem by the quantitative analysis of what I call spatial cognition surfacesTM – perspective views. The results of this work will be most relevant to specific purpose problem solving by members of governmental agencies and private sector entities. Currently, most investigators intuit their decision. Then they find the data and make from these several choropleth maps. The data and the maps substantiate the intuition. At best a choropleth map is an inappropriate representation of the spatial distribution, and, at worst, it contributes manifestly to the already difficult task of interpretation. Contour maps are aesthetically unpleasing, but at least they go part way to characterizing the continuous nature of the spatial distribution of a socio-economic condition. Regardless, similar to choropleth maps, interpreting reality from a contour map is a long and tortuous job. A perspective view gives a good – even exciting – idea of the spatial distribution of a socio-economic condition. However, apparently, it is only a qualitative characterization. Regardless, what is it about perspective views that captures my attention and holds it? Perspective views simulate the way humans construct an answer to a question about the spatial distribution of a socio-economic condition. Surface shape is the key to understanding and, in particular, quantifying this simulation. I have started to investigate the distribution of the volume beneath a spatial cognition surfaceTM and an intersecting plane above and parallel to the x,y-plane which represents the study region. There appears to be an important relationship between the nature of the spatial distribution and the change in the area circumscribed by what are termed “volume contours”. Success with this research will lead naturally to solving the problem of the automated interpretation of the spatial distribution of a socio-economic condition. If this can be achieved then we are looking forward to a time when substantiation will be replaced by an approach based on a strong, quantitative bridge between data and decision. Caveat This paper must not be referred to or quoted from without the written permission of the author. The author reserves the right to edit this paper and publish it elsewhere. The author asserts his moral right to the intellectual property vested in this paper, and states that this intellectual property is owned in its entirety by Spatial Cognition Surfaces Pty Ltd. GIS Context Past and future There have been remarkable advances associated with the implementation of the aftermath of the quantitative revolution in geography. By the late 60s geographic information systems (GIS), then commonly referred to as exercises in “geographic data handling”, represented an important but still only one quantitative sub-discipline of geography. There were also determined efforts in studying applications of univariate statistics, distributions of point patterns, methods of modeling processes, and techniques of multivariate data analysis. However, as time passed many would-be quantifiers drifted back to their idiographic research, while others jumped first on the social justice and then on the post-modernism bandwagons in what has proved to be a futile attempt to adapt a nomothetic explanatory form. In particular, the post-modernists can be singled out as those responsible for bringing geography that was so strong at the start of the 20th Century into disrepute by the end. There were exceptions to this trend and these persons comprised the young and hard-core investigators of GIS. They persevered, and by the early 80s quantitative geography and GIS were virtually synonymous. GIS development accelerated in the early 80s and has been growing ever since. It has followed closely the development and commercial availability of computational technologies. By the end of the 70s raster and vector technologies - using television monitors as the primary presentation device - made high quality desktop mapping possible. However, it was still restricted to few investigators because of the expense of both monitors and the associated mini-computers. This changed in the early 80s with the introduction of the IBM PC. Within a short period computing in general and color raster graphics monitors in particular became affordable; the impact on GIS was dramatic. GIS development in the 80s could be described as an intellectual and commercial roller coaster ride, but the 90s has been characterized by consolidation and commercial success for those who got into GIS in the early days, maintained their faith in its potential, and worked very hard. If you want evidence of this assertion examine the history of ESRI. Those of us old enough to remember have much of which to be proud. The others can be proud of becoming part of a strong discipline that has a grand history. GIS was born in the irrefutable paradigm of geographic regionalisation or “areal differentiation” of the first half of the 20th Century and it matured during the second half by identifying appropriate applications for which appropriate technologies were developed and applied. Regardless of our age and our experience we can all be proud that GIS – as a result of our efforts – will have a grand future. It is to the shaping of that future that this paper is directed. So the question is: What should we do next? It can, in part, be answered in the negative by urging a slow down in new software feature development. We do not need an integer increment in a software version number every several months, but it would be nice to think that efforts were being made to find and correct bugs in existing general-purpose GIS software and improve its performance. Why not a moratorium for the next two years on anything but decimal point increments of version numbers? Additional functionality serving little purpose, referred to as “flabware”, may do more harm than good to the reputations of the established vendors of GIS software products. A positive response to the question is exemplified in the applications orientation of Map India 2002. There seems to be the explicit recognition, at least among Indian practitioners, that GIS is something to be done, done now, and done with what tools are available. There are paper sessions in this conference on applications in agriculture, applications in telecommunications, applications in banking and insurance, applications in highways and transportation, and the list goes on. Each is a frontier that represents important applied problems which when solved in the Indian setting with its multifaceted complexities and subtleties will provide wonderful models – “solution models” - to be adapted to problems elsewhere. We can not afford not to solve these problems; it is time that GIS practitioners realized the broad significance and fundamental importance of our discipline. Another positive response is to urge the GIS community – students, academics, consultants and vendors – to take stock of what GIS has achieved and, in particular, what it has not. As a result we must identify the big theoretical problems of GIS. Out of all the work around the world over, say, the last forty years can’t we distill the essence of these big theoretical problems? As a function of lack of time and/or money they remain as obstacles to continued strong growth. They also remain as obstacles to the acceptance of GIS as a legitimate academic field instead of just a sub-discipline of geography obsessed with the development and application of technology. I identified one of these problems five years ago and since then my research has as its goal the finding of a solution. But this is the effort of only one investigator working alone and without funding. So here is the challenge to the GIS community: Identify the big theoretical problems of GIS and start to solve them. To do otherwise may result in stagnation of the growth we have experienced for more than twenty years.  Fig. 1: A choropleth map of Burnside
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