Planning Support Systems: Progress, Predictions, and Speculations on the Shape of Things to Come

In this paper, we review the brief history of planning support systems, sketching the way both the fields of planning and the software that supports and informs various planning tasks have fragmented and diversified. This is due to many forces which range from changing conceptions of what planning is for and who should be involved, to the rapid dissemination of computers and their software, set against the general quest to build ever more generalized software products applicable to as many activities as possible. We identify two main drivers – the move to visualization which dominates our very interaction with the computer and the move to disseminate and share software data and ideas across the web. We attempt a brief and somewhat unsatisfactory classification of tools for PSS in terms of the planning process and the software that has evolved, but this does serve to point up the state-ofthe- art and to focus our attention on the near and medium term future. We illustrate many of these issues with three exemplars: first a land usetransportation model (LUTM) as part of a concern for climate change, second a visualization of cities in their third dimension which is driving an interest in what places look like and in London, a concern for high buildings, and finally various web-based services we are developing to share spatial data which in turn suggests ways in which stakeholders can begin to define urban issues collaboratively. All these are elements in the larger scheme of things – in the development of online collaboratories for planning support. Our review far from comprehensive and our examples are simply indicative, not definitive. We conclude with some brief suggestions for the future

How Can Geography and Mobile Phones Contribute to Psychotherapy?

Interdisciplinary relationships between Geography and Psychotherapy are an opportunity for innovation. Indeed, scientific works found on bibliographic databases and concerning this theme are scarce. Geographical sub-fields, such as the Geography of Emotions or Psychoanalytical Geography have started to emerge, theorizing about and interpreting feelings, emotions, moods, sufferings, of the chronically ill or diversified social groups and sites. But a less theoretical and more practical approach, in the sense of proposing, predicting and intervening, is lacking; as well as research into the possibilities offered by communication technologies and mobile phones. In the present work, we present the results of a review of the most relevant scientific works published internationally; we reflect on the contributions of Geography and mobile phones to psychosocial therapies and define the orientation and questions that should be posed in future research, from the point of view of geography and regarding psychotherapy. We conclude that the production of georeferenced data via mobile phones concerning the daily lives of people opens great possibilities for cognitive behavioural therapy and mental health. They allow for the development of personalized mood maps that locate the places where a person experiences greater or lesser stress on a daily basis; they allow for a cartography of emotions, a cognitive cartography of the places we access physically or through the Internet, of our feelings and psychosocial experiences. They open the door to the possibility of offering personalized psychotherapy treatments focusing on the ecological-environmental analysis of the places frequented by the person on a daily basis

Development of downscaling method using the RBF network assessing the hourly population inflow: A case study of the Sapporo urban area

In Japan in recent years, policies for compact cities have been promoted as the population has decreased, and the use of micro-geo data has attracted attention in urban planning. Therefore, when considering a compact city, it is important to know the relationship between the urban facility layout and the population flow. In this research, we created a data set using demographic data, location information of mobile phones, and detailed building data and used a radial basis function (RBF) network. In short, the purpose of this study was to develop a method to reduce the estimated area of population inflow per hour. Population inflow is expressed as the visiting population, which is defined by the difference in the staying population in the time of two sections. By spatially visualizing the results, we were able to downscale the population flow data on a 500 m grid

Exploring Uncertainty in Geodemographics with Interactive Graphics

Geodemographic classifiers characterise populations by categorising geographical areas according to the demographic and lifestyle characteristics of those who live within them. The dimension-reducing quality of such classifiers provides a simple and effective means of characterising population through a manageable set of categories, but inevitably hides heterogeneity, which varies within and between the demographic categories and geographical areas, sometimes systematically. This may have implications for their use, which is widespread in government and commerce for planning, marketing and related activities. We use novel interactive graphics to delve into OAC – a free and open geodemographic classifier that classifies the UK population in over 200,000 small geographical areas into 7 super-groups, 21 groups and 52 sub-groups. Our graphics provide access to the original 41 demographic variables used in the classification and the uncertainty associated with the classification of each geographical area on-demand. It also supports comparison geographically and by category. This serves the dual purpose of helping understand the classifier itself leading to its more informed use and providing a more comprehensive view of population in a comprehensible manner. We assess the impact of these interactive graphics on experienced OAC users who explored the details of the classification, its uncertainty and the nature of between – and within – class variation and then reflect on their experiences. Visualization of the complexities and subtleties of the classification proved to be a thought-provoking exercise both confirming and challenging users’ understanding of population, the OAC classifier and the way it is used in their organisations. Users identified three contexts for which the techniques were deemed useful in the context of local government, confirming the validity of the proposed methods

Spatial and multidimensional analysis of the Dutch housing market using the Kohonen Map and GIS

In this work the idea is to analyse general spatially identifiable housing market related data on Dutch districts (wijken) with the SOM (Kohonen Map) and a GIS. One of the authors has earlier carried out purely visual SOM analysis of that data, where patterns formed on a larger ‘map’ (the output matrix of the SOM) were used as a basis for classification of the Dutch housing market segments on a nationwide level. This way the SOM was used as a method for exploratory data analysis. Now we attempt a more rigorous method of determining the segmentation using a smaller ‘map’ size, in order to be able to export the SOM-output directly to a GIS-system to analyse it further. Two technical issues interest us: one, the robustness of the results – do the five basic housing market segments found in the earlier analysis prevail (we call these urban, urban periphery, pseudo-rural, traditional, and low-income segments); and two, which classes fit the real situation better and which worse, when using the RMSE for a measure of goodness? We also keep an eye on policy implications and aim at comparing our classifications with the ‘actual’ ones used in official discourse.