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This year marks the 21st anniversary of the International GeoComputation Conference Series. To celebrate the occasion, Environment and Planning B invited some members of the geocomputational community to reflect on its achievements, some of the unrealised potential, and to identify some of the on-going challenges.

The penetration and use of social media services differs from city to city. This paper is aimed to provide a comparison of the use of Twitter between different cities of the world. We present a temporal analysis of activity on Twitter in 15 cities. Our study consists of two parts: First, we created temporal graphs of the activity in the 15 cities, through which hours of high and low activity could be identified. Second, we created heat map visualizations of the Twitter activities during the period of 19 September 2012–25 September 2013. The heat map visualizations make the periods of intense and sparse activity apparent and provide a snapshot of the activity during the whole year.

In recent years a mix of Open Data and commercial sources have been used to build geodemographic classifications of neighbourhoods. In this paper we argue that geodemographics are coming to embody new thinking about the emergent mixed Big Data economy. This has implications for openness and full scientific reproducibility of classifications, as well as the engagement of stakeholders in the process of building classifications. We propose and implement an operational framework for blending open and other data sources that can stimulate development of classifications that are more timely and data rich yet sufficiently open to peer scrutiny. We illustrate these ideas and challenges by describing the creation and content of the London Workplace Zone Classification.

The Royal Geographical Society (with IBG)'s annual Medals and Awards recognise achievements in the research, communication and teaching of a wide range of geographical knowledge. The speeches and citations are a record of the ceremony of 2013. With comments by Michael Palin, and Professors Keith Richards, Kelvyn Jones, Paul Longley and Susan Page, the speeches encompass travel, fluvial geomorphology, quantitative research, geographic information science and tropical peatland conservation.

This paper uses an extended case study of Japan to illustrate how surnames, or family names, can be used as a basis for regionalization. We undertake a comparison between inductively surname regions of Japan with areal geographies based upon both contemporary and historical prefecture (administrative) units. The work is seen as using highly disaggregate framework data to evaluate the integrity of the areal units that are used in regional science. It also is relevant to understanding population distributions, past and present, and the consequences of local, regional and national residential mobility and migration. © 2013 RSAI.

There is a great deal of interest in a fine-scale population structure in the UK, both as a signature of historical immigration events and because of the effect population structure may have on disease association studies. Although population structure appears to have a minor impact on the current generation of genome-wide association studies, it is likely to have a significant part in the next generation of studies designed to search for rare variants. A powerful way of detecting such structure is to control and document carefully the provenance of the samples involved. In this study, we describe the collection of a cohort of rural UK samples (The People of the British Isles), aimed at providing a well-characterised UK-control population that can be used as a resource by the research community, as well as providing a fine-scale genetic information on the British population. So far, some 4000 samples have been collected, the majority of which fit the criteria of coming from a rural area and having all four grandparents from approximately the same area. Analysis of the first 3865 samples that have been geocoded indicates that 75% have a mean distance between grandparental places of birth of 37.3 km, and that about 70% of grandparental places of birth can be classed as rural. Preliminary genotyping of 1057 samples demonstrates the value of these samples for investigating a fine-scale population structure within the UK, and shows how this can be enhanced by the use of surnames. © 2012 Macmillan Publishers Limited All rights reserved.

Following the increasing availability of DNA-sequenced data, the genetic structure of populations can now be inferred and studied in unprecedented detail. Across social science, this innovation is shaping new bio-social research agendas, attracting substantial investment in the collection of genetic, biological and social data for large population samples. Yet genetic samples are special because the precise populations that they represent are uncertain and ill-defined. Unlike most social surveys, a genetic sample's representativeness of the population cannot be established by conventional procedures of statistical inference, and the implications for population-wide generalisations about bio-social phenomena are little understood. In this paper, we seek to address these problems by linking surname data to a censored and geographically uneven sample of DNA scans, collected for the People of the British Isles study. Based on a combination of global and local spatial correspondence measures, we identify eight regions in Great Britain that are most likely to represent the geography of genetic structure of Great Britain's long-settled population. We discuss the implications of this regionalisation for bio-social investigations. We conclude that, as the often highly selective collection of DNA and biomarkers becomes a more common practice, geography is crucial to understanding variation in genetic information within diverse populations.

The UK National Health Service (NHS) is a long-established universal provider of health care. Most primary care is delivered by general practitioner (GP)-run health centers (surgeries) that, subjec...

Surnames (family names) have been overlooked as a valuable source of spatially referenced population data. Presented here is a methodology, based on kernel density estimation, which is used to identify the areas of Great Britain where any surname is most concentrated. This not only indicates a surname's geographic origin in the country but also its current spatial extent and spatial relationship with other surnames and place names. We argue that such analysis can provide baseline and change measures, and an empirical basis to change forecasting. Such analysis offers valuable insights into national, regional and local changes in population structure, and testimony to the relevance of GIScience to population genetics, historical geography and genealogy.

Surnames (family names) show distinctive geographical patterning and in many disciplines remain an underutilized source of information about population origins, migration and identity. This paper investigates the geographical structure of surnames, using a unique individual level database assembled from registers and telephone directories from 16 European countries. We develop a novel combination of methods for exhaustively analyzing this multinational data set, based upon the Lasker Distance, consensus clustering and multidimensional scaling. Our analysis is both data rich and computationally intensive, entailing as it does the aggregation, clustering and mapping of 8 million surnames collected from 152 million individuals. The resulting regionalization has applications in developing our understanding of the social and cultural complexion of Europe, and offers potential insights into the long and short-term dynamics of migration and residential mobility. The research also contributes a range of methodological insights for future studies concerning spatial clustering of surnames and population data more widely. In short, this paper further demonstrates the value of surnames in multinational population studies and also the increasing sophistication of techniques available to analyze them.

This paper studies differential healthcare utilisation by ethnic group. Administrative records of nearly 100,000 users of an Inner London accident and emergency (A&E) facility were analysed using an innovative names-based ethnicity classification. Adult repeated 'light' usage (i.e. with no hospitalisation or follow-up) did not differ according to ethnic group. Users from ethnic minorities had lower GP registration rates than the majority reference group. However, lack of GP registration was not associated with repeated light use of A&E, overall. Therefore, these results challenge common perceptions of differential A&E access rates by ethnicity. (C) 2010 Elsevier Ltd. All rights reserved.

This paper undertakes the largest ever quantitative analysis of the distribution of surnames in Great Britain, in order to identify ‘surname regions’. Our empirical analysis uses hierarchical clustering and multidimensional scaling in a computationally intensive analysis of a near complete individual population register of Great Britain. The outcome of this classification is an inductive partitioning of space which, we suggest, reveals a unique and authoritative regional geography that is of use in improving our understanding of population dynamics, as well as of historic and contemporary migration.

Following the Educational Reform Act of 1988, families in England and Wales have been free to identify a preferred school for their children’s secondary education. However, as part of this open selection, the demand from parents opting to send their children to the best performing schools far outstrips the supply of available places at them, and consequently many schools ration places using entry criteria that favour those pupils domiciled close to the school. Through this geographic selection process, choice is spatially sorted and access to the best schools is often crucially dependent upon where parents live. After illustrating this problem, this paper develops an automated modelling technique that can be used to define and map school catchment areas based on the home locations of pupils attending every publically funded school in England. It then develops this framework to create a web based decision support tool to aid parents seeking secondary school places.

This paper has two main objectives. First, we review and evaluate four different computational methods for measuring the "fractality" of cartographic lines: these are known as the structured walk, the equipaced polygon, the hybrid walk, and the cell count methods. Second, because previous research has restricted the focus of fractal measurement exercises to isolated physical entities, the subject of our empirical study concerns the urban area of Swindon, United Kingdom, that comprises a mosaic of contiguous land-use parcels. In technical terms, the results pinpoint some of the comparative strengths and weaknesses of the four methods, whilst our substantive conclusion is that fractal dimension appears to be a junction of both scale and land-use type in our geographical study.

Geodemographic classifications provide discrete indicators of the social, economic and demographic characteristics of people living within small geographic areas. They have hitherto been regarded as products, which are the final "best" outcome that can be achieved using available data and algorithms. However, reduction in computational cost, increased network bandwidths and increasingly accessible spatial data infrastructures have together created the potential for the creation of classifications in near real time within distributed online environments. Yet paramount to the creation of truly real time geodemographic classifications is the ability for software to process and efficiency cluster large multidimensional spatial databases within a timescale that is consistent with online user interaction. To this end, this article evaluates the computational efficiency of a number of clustering algorithms with a view to creating geodemographic classifications "on the fly" at a range of different geographic scales. © 2010 Blackwell Publishing Ltd.

SummaryParticipation in UK higher education is modelled by using Poisson regression techniques. Models using geodemographic classifications of neighbourhoods of varying levels of detail are compared with those using variables that are directly derived from the census, using a cross-validation approach. Increasing the detail of geodemographic classifiers appears to be justified in general, although the degree of improvement becomes more marginal as the level of detail is increased. The census variable approach performs comparably, although it is argued that this depends heavily on an appropriate choice of predictors. The paper concludes by discussing these results in a broader practice-oriented and pedagogic context.

Geodemographics offers the prospects of integrating, modelling and mapping health care needs and other health indicators that are useful for targeting neighbourhoods in public health campaigns. Yet reports about this application domain has to date been sporadic. The purpose of this paper is to examine the potential of a bespoke geodemographic system for neighbourhood targeting in an inner city public health authority, Southwark Primary Care Trust, London. This system, the London Output Area Classification (LOAC), is compared to six other geodemographic systems from both governmental and commercial sources. The paper proposes two new indicators for assessing the performance of geodemographic systems for neighbourhood targeting based on local hospital demand data. The paper also analyses and discusses the utility of age- and sex standardisation of geodemographic profiles of health care demand.

This paper reports on a cross-cultural outreach activity of the current UK ‘Spatial Literacy in Teaching’ (SPLINT) Centre of Excellence in Teaching and Learning (CETL), a past UK Economic and Social Research Council (ESRC) grant, and shared interests in family names between Japanese and UK academics. It describes a pedagogic programme developed for Japanese postgraduates and advanced undergraduates that entailed quantitative and qualitative analysis of the spatial distributions of Japanese family names. The authors describe some specific semantic, procedural and theoretical issues and, more generally, suggest how names analysis provides a common framework for engaging student interest in GIS.

Please click here to download the map associated with this article. The British Population retains a strong sense of regional identity, epitomized by periodic campaigns for Scottish and Welsh devolution, or for Cornish self-government. There have been few studies into the regionalization of British surnames and none that utilize any register that can claim to be nationally representative. The National Social Map presented in this paper is the first comprehensive attempt to create a regional geography of Great Britain based upon the clustering of surnames. The resulting map illustrates a strong relationship between the populations surnames and geographic location. The homogeneity within each of the surname regions identified is striking given that spatial contiguity constraints were not included within the clustering process. The map will hopefully set a bench-mark for future work by geographers in the field of surname research.

Uncertainty is inherent in the conception and measurement of ethnicity, by both individuals themselves and those who seek to gather evidence of discrimination or inequalities in social and economic outcomes. These issues have received attention in the literature, yet rather little research has been carried out on the uncertainty subsequently created through the analysis of such measurements. We argue that, while general-purpose ethnicity classifications offer a method of standardising results, such groupings are inherently unstable, both in their upward aggregation and in their downward granulation. As such, the results of ethnicity analysis may possess no validity independent of the ethnicity classes upon which it is based. While this conclusion is intuitive, it nevertheless seems to pass unnoticed in the interpretation of research conducted in public policy applications such as education, health and residential segregation. In this paper we use examples based on the standard Census classification of eth...

This paper explores the use of geodemographic classifications to investigate the social, economic and spatial dimensions of participation in Higher Education (HE). Education is a public service that confers very significant and tangible benefits upon receiving individuals: as such, we argue that understanding the geodemography of educational opportunity requires an application-specific classification that exploits under-used educational data sources. We develop a classification for the UK higher education sector, and apply it to the Gospel Oak area of London. We discuss the wider merits of sector specific applications of geodemographics and enumerate the advantages of bespoke classifications for applications in public service provision. Resumen Este articulo explora el uso de clasificaciones geodemograficas para investigar las dimensiones sociales, economicas y espaciales de la participacion en educacion superior. La educacion es un servicio publico que confiere beneficios tangibles y muy significativos a los individuos que la reciben: como tal, argumentamos que entender la geodemografia de las oportunidades educativas requiere una clasificacion especifica para cada aplicacion que explote fuentes de datos de educacion infra utilizados. Desarrollamos una clasificacion para el sector de educacion superior del Reino Unido, y la aplicamos al area de Gospel Oak de Londres. Discutimos en general los meritos de aplicaciones sectoriales especificas de geodemografia y citamos las ventajas de clasificaciones a medida para aplicaciones en la provision de servicios publicos.

This review begins by acknowledging the success of geodemographics as an important area of activity in applied geography. However, it then develops a critique of the conceptual and computational underpinnings of the approach, and argues that changes in data supply and online communication have rendered current practices obsolete. It presents elements of a new perspective, entailing: changes in the specification, estimation and testing of online geodemographic systems; adoption of consultative practices from online folksonomies; automated generation of pen portraits; and ‘on the fly’ visualisation of the outcome of geodemographic classifications.

Although viewed by business and commerce as successful solutions, geodemographic profiling of neighbourhoods has attracted wide-ranging criticism in the academic literature. This paper addresses some specific concerns that arise because the derivation of classifications is rarely transparent and open to scrutiny or challenge. The substantive focus of the research reported in this paper is a nationwide geodemographic classification of how people engage with new information and communication technologies (ICTs). In response to the critique of geodemographics as a 'black box' technology, we describe how the classification was opened up to public scrutiny and how we conducted a major consultation exercise into the reliability of its results. We assess the message of the 50,000+ searches and 3952 responses collected during the consultation exercise, in terms of possible systematic errors in the shape and detail of the classification. Unusually for Internet-based surveys, we also investigate the likely reliability of the response information received and identify ways in which the outcome of consultation might be used to improve the classification. We believe that this is the first-ever large-scale consultation survey of the validity and remit of a geodemographic classification and that it may have wider implications for the creation of geodemographic classifications.

This paper develops a cross-classification of material deprivation and lack of digital engagement, at a far more spatially disaggregated level than has previously been attempted in the UK. This is achieved by matching the 2004 Index of Multiple Deprivation (IMD) with a unique nation-wide geodemographic classification of ICT usage, aggregated to unit postcodes. The results of the cross-classification suggest that lack of digital engagement and material deprivation are linked, with high levels of material deprivation generally associated with low levels of engagement with ICTs and vice versa. However, some neighbourhoods are `digitally unengaged' but not materially deprived and the paper investigates the extent to which this outcome may be linked to factors such as lack of confidence, skills or motivation. As with material deprivation, there are distinctive regional and local geographies of digital unengagement and these have important implications for digital policy implementation.

Information and communication technology are potentially significant tools in strengthening local initiatives towards sustainability. The Science and Technology (S&T) Framework for Sustainable Development provides a context for such development. This article describes a study aimed at examining how the existing mobile technologies of standard messaging service and wireless application protocol can be used to support the activities of an environmental grassroots organisation-London 21 Sustainability Network (henceforth London 21). Following the S&T Framework, it is clear that to realise the potential of these technologies a new mobile service should be effectively embedded into the structure and activity of the network. Using a participatory research approach, an extensive user requirements study with 273 participants was carried out to ensure that the development of the mobile service for London 21 fulfils the purposes, goals and expectations of the organisation. This article describes a Mobile Spatial Messaging Service, called EcoTEXT, which was developed and deployed for London 21. This service allows individuals to receive geographically targeted, action-orientated, time-relevant information via text messages on their mobile phones. The content of the service is information about upcoming local environmental events and activities, which match the interest of the user, when these events occur in close spatial proximity to where that user resides. This type of service represents a powerful new dimension for the provision of data-driven services in comparison to current text-based services. Location is giving the service additional meaning and value. The introduction of such a service into the organisation's communication toolkit offers the potential to create, supplement and strengthen social ties and interactions within the community.

This paper begins by reviewing the ways in which the innovation of Google Maps has transformed our ability to reference and view geographically referenced data. We describe the ways in which the GMap Creator tool developed under the ESRC National Centre for e Social Science (NCeSS) programme enables users to ‘mashup’ thematic choropleth maps using the Google API. We illustrate the application of GMap Creator using the example of www.londonprofiler.org, which presents a repository of choropleth maps across a range of domains including health, education and other socioeconomic datasets against a backcloth of Google Maps data. Our conclusions address the ways in which Google Map mashups developed using GMap Creator facilitate online exploratory cartographic visualisation in a range of areas of policy concern.

It is simplistic to think of the impacts of new information and communication technologies (ICTs) in terms of a single, or even small number of, 'digital divides'. As developments in what has been termed the ?e-society? reach wider and more generalisedaudiences, so it becomes appropriate to think of digital media as having wider-ranging but differentiated impacts upon consumer transactions, information gathering and citizen participation. This paper describes the development of a detailed, nationwide household classification based on levels of awareness of different ICTs; levels of use of ICTs; andtheir perceived impacts upon human capital formation and the quality of life. It discusses how geodemographic classification makes it possible to provide context for detailed case studies, and hence identify how policy might best improve both the quality and degree ofsociety?s access to ICTs. The primary focus of the paper is methodological, but it alsoillustrates how the classification may be used to investigate a range of regional and subregional policy issues. This paper illustrates the potential contribution of bespoke classifications to evidence-based policy, and the likely benefits of combining the most appropriate methods, techniques, datasets and practices that are used in the public and private sectors. It is simplistic to think of the impacts of new information and communication technologies (ICTs) in terms of a single, or even small number of, 'digital divides'. As developments in what has been termed the ?e-society? reach wider and more generalisedaudiences, so it becomes appropriate to think of digital media as having wider-rangingbut differentiated impacts upon consumer transactions, information gathering and citizen participation. This paper describes the development of a detailed, nationwide household classification based on levels of awareness of different ICTs; levels of use of ICTs; and their perceived impacts upon human capital formation and the quality of life. It discusses how geodemographic classification makes it possible to provide context for detailed case studies, and hence identify how policy might best improve both the quality and degree of society?s access to ICTs. The primary focus of the paper is methodological, but it also illustrates how the classification may be used to investigate a range of regional and subregional policy issues. This paper illustrates the potential contribution of bespoke classifications to evidence-based policy, and the likely benefits of combining the most appropriate methods, techniques, datasets and practices that are used in the public and private sectors.

This paper presents a review and interpretation of the apparent inertia and resistance to change that has characterised the last twenty-five years of UK policing. We argue that attempts to introduce New Public Management to policing have not proved as effective as in other public services. Most of the activities of the police have explicitly spatial consequences yet, we argue, the slow diffusion and adoption of geographic information systems (GIS) and other technical innovations has been a particular issue. The current round of political aspirations to reform policing depend in large part on a rapid increase in the efficiency and effectiveness of police management information systems and their deployment at strategic and tactical levels. Generic opportunities and constraints arising in the field of geographic information science are identified and summarised followed by a critical appreciation of current GIS deployment in policing. Direct practical experience in GIS policing applications is used to outline observed barriers to progress and also forms the basis for a number of strategic recommendations.

This article describes the way in which a unique new quantitative data resource and evidence base has been used to relate historic measures of U.K. migration flows to the contemporary socioeconomic patterning of neighborhoods. The resource enables generalized analysis of the regional origins of British and Irish people from their family names, and makes it possible to relate the current regional distribution of names in the United States, Great Britain, and other English-speaking countries to equivalent information from the Great Britain Census of 1881. Illustrative applications may be viewed at http://www.spatial-literacy.org. In this article we develop a number of indices of the historic origins of English and Irish family names, as a prelude to detailed microscale analysis of late twentieth century surname patterns. We illustrate the usefulness of these various indices through case study analysis of Middlesbrough and East Cleveland, an area of the United Kingdom that attracted large numbers of economic migrants during its rapid nineteenth century industrialization. We use our quantitative evidence of the historical distributions of different family names in order to characterize the social mobility of descendants of Scottish, Irish, and Cornish migrants, and to evaluate the practice of ascribing family names to particular localities in historical GIS. The case study thus illustrates the ways in which our data resource may be used to substantiate existing thinking about historic migration and residential structure, as well as to generate and investigate new hypotheses that might guide future work.

Location-Based Services (LBS) are the delivery of information to mobile devices customised to location and context of the user. Some research has focused on data content, while other studies have emphasised the role of multimedia communication. However, very few objective tests have been carried out concerning usage and behaviour. In this paper, a conceptual model and a LBS test environment are presented which aim to study the behaviour and interaction between environments, individuals and mobile devices. The test environment was created, for this purpose, with three main components: urban VR models that allow individuals to 'walk around' at street level, a mobile device as information source which simulates LBS applications, and software for recording participant actions and reactions within the test environment. Multi-source data were collected regarding movement tracking, information accessed through mobile device and participant observations using a combination of automated and semi-automated methods. A case study on pedestrian wayfinding in urban settings is presented. This illustrates how the test environment can be used for LBS applications and how the data collected can be analysed. The research presented in this paper provides a novel approach in studying and understanding the interaction between environments, individuals and mobile devices. © 2006 The Authors Journal compilation © 2006 Blackwell Publishing Ltd.

The UK financial services market has expanded in recent years through the addition of several non-traditional players. We evaluate the extent to which this increased supply of services is best channelled through existing retail locations or whether products are better promoted and managed via direct marketing methods. Using a UK grocer/retailer's lifestyle customer database for an urban store and an out-of-centre location, we analyse a regional sample of customers who have received financial services mail-shots. The use of GIS and logistic regression enables the determination of the extent to which mail respondents have distinctive characteristics in terms of wealth, financial service ownership and proximity to store. Finally, we discuss the implications of our empirical study for in-store financial services support and draw some general conclusions based on our assessment of the usefulness of lifestyles data in such applications.

Airborne laser scanning (ALS) is becoming an increasingly popular data capture technique for a variety of applications in urban surface modeling. Raw ALS data are captured and supplied as a 3D point cloud. Many applications require that these data are interpolated onto a regular grid in order that they may be processed. In this article, we identify and analyze the magnitudes and spatial patterning of residuals from ALS models of urban surfaces, at a range of different scales. Previous research has demonstrated the effects of interpolation method and scale upon the nature of error in digital surface models (DSMs), but the size and spatial patterning of such errors have not hitherto been investigated for urban surfaces. The contribution of this analysis is thus to investigate the ways in which different methods may introduce error, and to understand the uncertainty that characterizes urban surface models that are devised for a wide range of applications. The importance of the research is shown using examples of how the different methods may introduce different amounts of error and how the uncertainty information may benefit users of ALS height models. Our analysis uses a range of validation techniques, including split-sample, cross-validation, and jackknifing, to estimate the error created in DSMs of urban areas.

Issues surrounding the financial benefits of owner occupation and how these are related to a variety of socioeconomic and geographical factors are examined through the development of a microsimulation model of the U.K. housing market. Of particular interest are the ways in which different government subsidies accrue to different types of households over time. The model has been implemented for two U.K. regions and simulations performed over a ten year historic period. Results showing the wide variation in household experience are presented.

The innovation of computer graphics into regional science has already stimulated development of new types of analogue models of city structures. Now, progressive integration of satellite data and socio-economic information within geographical information systems (GIS) is making possible the creation of tailor-made datasets through which such models might be evaluated. This paper begins with a retrospective assessment of Fotheringham, Batty and Longley's (1989) diffusion-limited aggregation (DI.A) analogue model of urban growth. Using satellite imagery and a surface model derived from the UK Census, we develop a dataset which facilitates empirical evaluation of this analogy. Implications of this approach are explored.

The field of geodemographics is one of the most fertile applications areas of geocomputation research. Geodemographic profiles of the characteristics of individuals and small areas are pivotal to tactical and strategic resource management in many areas of business, and are becoming similarly central to efficient and effective deployment of resources by public services. In this context, this paper describes research that has been developed in partnership with the Devon and Cornwall Constabulary and Institute of Criminal Justice Studies (ICJS) at the University of Portsmouth to assess the potential use of geodemographics as a policing tool. Crime, the fear of crime and the efficacy of public services are issues that have moved to the top of the UK political agenda and have long been matters of serious public concern. This paper considers the ways in which police forces might use geodemographics to better deploy resources at a variety of spatial scales in England and Wales.

Developments in the provision and quality of digital data are creating possibilities for spatial and temporal measurement of the properties of socioeconomic systems at finer levels of granularity. In this article, we suggest that the “lifestyles” datasets collected by private sector organizations in the U.K. and the U.S. provide one such prospect for better inferring the structure, composition, and heterogeneity of urban areas. Using a case study of Bristol, U.K., we compare the patterns of spatial dependence and spatial heterogeneity observed for a small-area (“lifestyles”) income measure with those of the census indicators that are commonly used as surrogates for it. This leads first to an exploration of spatial effects using geographically weighted regression (GWR) and then to a specification of spatial dependence using a spatially autoregressive model. This analysis extends our understanding of the determinants of hardship and poverty in urban areas; urban policy has hitherto used aggregate, ...