Ian Turton

Web-based public participation geographical information systems: an aid to local environmental decision-making

Current research examining the potential of the World-Wide Web as a means of increasing public participation in local environmental decision making in the UK is discussed. The paper considers traditional methods of public participation and argues that new Internet-based technologies have the potential to widen participation in the UK planning system. Evidence is provided of the potential and actual benefits of online spatial decision support systems in the UK through a real environmental decision support problem in a village in northern England. The paper identifies key themes developing in this area of Web-based geographical information systems (GIS) and provides a case-study example of an online public participation GIS from inception to the final phase in a public participation process. It is shown that in certain UK planning problems and policy formulation processes, participatory online systems are a useful means of informing and engaging the public and can potentially bring the public closer to a participatory planning system.

Public participation, GIS, and cyberdemocracy: evaluating on-line spatial decision support systems

In this paper we describe the development of Internet-based approaches to public participation and on-line spatial decision support systems in particular. Two case studies in developing web-based public participation GIS (PPGIS), one local and one regional, are described in detail. Results from the live testing of these systems are shown. These are discussed in the light of recent developments in ‘cyberdemocracy’ and conclusions are drawn about principles of on-line PPGIS and problems associated with public participation, user interaction, and familiarity with IT, copyright issues, access to the Internet, and relevant political structures.

A parallel Kohonen algorithm for the classification of large spatial datasets

Abstract The paper describes the development of Kohonen-net-based methods suitable for the classification of large spatial datasets suitable for parallel processing. Parallelising the Kohonen net is not easy because the degree of natural parallelism is finely grained. This paper presents a new algorithm and demonstrates its performance on the Cray T3D parallel supercomputer.

High-Performance Computing and Geography: Developments, Issues, and Case Studies

In this paper we outline some of the results that were obtained by the application of a Cray T3D parallel supercomputer to human geography problems. We emphasise the fundamental importance of high-performance computing (HPC) as a future relevant paradigm for doing geography. We offer an introduction to recent developments and illustrate how new computational intelligence technologies can start to be used to make use of opportunities created by data riches from geographic information systems, artificial intelligence tools, and HPC in geography.

Using computational intelligence techniques to model subglacial water systems

Abstract. Measurements of water pressure beneath Trapridge Glacier, Yukon Territory, Canada show that the basal water system is highly heterogeneous. Three types of behaviour were recorded: pressure records which are strongly correlated, records which are strongly anticorrelated, and records which alternate between strong correlation and strong anticorrelation. We take the pressure in bore-holes that are connected to the evacuation route for basal water as the forcing, and the other pressures as the response to this forcing. Previous work (Murray and Clarke 1995) has shown that these relationships can be modelled using low-order nonlinear differential equations optimized by inversion. However, despite optimizing the model parameters we cannot be sure that the final model forms are themselves optimal. Computational intelligence techniques provide alternative methods for fitting models and are robust to missing or noisy data, applicable to non-smooth models, and attempt to derive optimal model forms as well as optimal model parameters. Four computational intelligence techniques have been used and the results compared with the more conventional mathematical model. These methods were genetic programming, artificial neural networks, fuzzy logic and self-organizing maps. We compare each technique and offer an evaluation of their suitability for modelling the pressure data. The evaluation criteria are threefold: (1) goodness of fit and an ability to predict subsequent data under different surface weather conditions; (2) interpretability, and the extent and significance of any new insights offered into the physics of the glacier; (3) computation time. The results suggest that the suitability of the computational intelligence techniques to model these data increases with the complexity of the system to be modelled.

A Spatial Microsimulation Model for Social Policy Evaluation

Evaluation is a critical step in the analysis of social policies which, itself, can influence public thinking (Unrau, 1993; Manski and Garfinkel, 1992). Policy-relevant spatial modelling is an expanding area of research, which has a lot of potential for the evaluation of the socio-economic and spatial effects of major national social policy programmes. However, traditional modelling approaches to social policy analysis usually focus on the impact on the socio-economic structure of the population and they have tended to ignore the geographical dimensions of social policies. In particular, the focus has usually been on the redistributive effects of government policies (such as budget changes and social security benefit policies etc.) between households, but there has generally been a paucity of studies that investigate the spatial impacts of these policies.

Using a Geographical Explanations Machine to Explore Spatial Factors relating to Primary School Performance

The development and application of an automated geographical data explorer designed to look for potentially interesting geographical associations in a GIS database without any prior hypotheses as to what to look for or where they may be applied are described. The method is briefly described and then demonstrated via a case study. This case study examines how the geographical variations in primary school performance in northern England can be related to other variables. Finally, suggestions are made for its further development by the addition of a smart search capability.

Application of Pattern Recognition to Concept Discovery in Geography

This paper explores the ways that pattern matching techniques can be applied to raster datasets to develop new concepts for geography. It is argued that it is becoming increasingly important for geographers to develop new ways of generalising datasets that will allow them to overcome the increasing data richness of the geocybersphere. The data set used for this study is a population density surface derived from the 1991 census of population by Bracken and Martin (1989). Using this data set the aim is to take the data-poor geographical theories of urban social structure of the first half of the century and make use of the data-rich environments of the 1990s to test the theories in a general and robust manner. To achieve this pattern matching techniques used in computer vision and other fields will be applied to raster data of population density and social and economic variables for Great Britain. Initially the raster data is segmented by the application of image analysis techniques to identify 129 urban areas in Britain. These urban areas are then compared to templates of the theoretical models of Burgess (1925) and Hoyt (1939) using methods developed in the fields of computer vision and medical imaging. Several urban areas are found that are similar in social structure to the theoretical models developed earlier in the century. The urban areas are then compared to themselves to determine if there were any other groupings of modern British cities that can be made in terms of their social structure. Several such groups are discovered and will be briefly discussed. 30 March, 1998. p 2 Introduction Openshaw (1994) argues that as the amount of data that is collected as a result of the GIS revolution increases geographers must start to apply new methods to these new data riches. It is no longer enough to merely catalogue the data and draw simple maps of it. It is also no longer acceptable to use crude statistical measures that average over a whole map or region and in so doing throw away the geographical content of the data. In other words geographers must generalise or drown in the flood of spatial data that has increased many fold during the 1980s and 1990s and which will continue to grow into the next century. As the amount of data grows, it becomes increasingly difficult for humans to find the time to study and interpret the data; the only solution is to pass more of the routine analysis to computers leaving the researcher with more time to study the truly interesting parts of the output. This paper is a first attempt to apply these ideas to a geographical data set. One data set will be studied in detail though the ideas and methods developed will be applicable to many other data sets. The data set selected for this study is a population density surface derived from the 1991 census of population by Bracken and Martin (1989). Using this data set the aim is to take the data-poor geographical theories of urban social structure of the first half of the century and make use of the data-rich environments of the 1990s to test the theories in a general and robust manner. To achieve this pattern matching techniques used in computer vision and other fields will be applied to raster data of population density and socio-economic variables for Great Britain.

Some Geographical Applications of Genetic Programming on the Cray T3D Supercomputer

The paper describes some geographical applications of a parallel GP code which is run on a Cray T3D 512 processor supercomputer to create new types of well performing mathematical models. A series of results are described which allude to the potential power of the method for which there are many practical applications in spatial data rich environments where there are no suitable existing models and no soundly based theoretical framework on which to base them.

Putting the 1991 Sample of Anonymised Records on Your Unix Workstation

The authors describe the development of a customised computer software package for easing the analysis of the UK 1991 Sample of Anonymised Records. The resulting USAR package is designed to be portable within the Unix environment. It offers a number of features such as interactive table design, intelligent data interpretation, and fuzzy query. An example of SAR analysis is provided.