In This Article Expand or collapse the "in this article" section Spatial Analysis

  • Introduction
  • General Overview of Spatially Informed Sociology
  • Classic Works in Sociology
  • Methodological Issues
  • Qualitative Methods
  • Ethical Issues
  • Journals

Sociology Spatial Analysis
Stephen Matthews, Rachel Bacon, R. L’Heureux Lewis-McCoy, Ellis Logan
  • LAST REVIEWED: 12 September 2018
  • LAST MODIFIED: 30 October 2019
  • DOI: 10.1093/obo/9780199756384-0058


Recent years have seen a rapid growth in interest in the addition of a spatial perspective, especially in the social and health sciences, and in part this growth has been driven by the ready availability of georeferenced or geospatial data, and the tools to analyze them: geographic information science (GIS), spatial analysis, and spatial statistics. Indeed, research on race/ethnic segregation and other forms of social stratification as well as research on human health and behavior problems, such as obesity, mental health, risk-taking behaviors, and crime, depend on the collection and analysis of individual- and contextual-level (geographic area) data across a wide range of spatial and temporal scales. Given all of these considerations, researchers are continuously developing new ways to harness and analyze geo-referenced data. Indeed, a prerequisite for spatial analysis is the availability of information on locations (i.e., places) and the attributes of those locations (e.g., poverty rates, educational attainment, religious participation, or disease prevalence). This Oxford Bibliographies article has two main parts. First, following a general overview of spatial concepts and spatial thinking in sociology, we introduce the field of spatial analysis focusing on easily available textbooks (introductory, handbooks, and advanced), journals, data, and online instructional resources. The second half of this article provides an explicit focus on spatial approaches within specific areas of sociological inquiry, including crime, demography, education, health, inequality, and religion. This section is not meant to be exhaustive but rather to indicate how some concepts, measures, data, and methods have been used by sociologists, criminologists, and demographers during their research. Throughout all sections we have attempted to introduce classic articles as well as contemporary studies. Spatial analysis is a general term to describe an array of statistical techniques that utilize locational information to better understand the pattern of observed attribute values and the processes that generated the observed pattern. The best-known early example of spatial analysis is John Snow’s 1854 cholera map of London, but the origins of spatial analysis can be traced back to France during the 1820s and 1830s and the period of morale statistique, specifically the work of Guerry, d’Angeville, Duplin, and Quetelet. The foundation for current spatial statistical analysis practice is built on methodological development in both statistics and ecology during the 1950s and quantitative geography during the 1960s and 1970s and it is a field that has been greatly enhanced by improvements in computer and information technologies relevant to the collection, and visualization and analysis of geographic or geospatial data. In the early 21st century, four main methodological approaches to spatial analysis can be identified in the literature: exploratory spatial data analysis (ESDA), spatial statistics, spatial econometrics, and geostatistics. The diversity of spatial-analytical methods available to researchers is wide and growing, which is also a function of the different types of analytical units and data types used in formal spatial analysis—specifically, point data (e.g., crime events, disease cases), line data (e.g., networks, routes), spatial continuous or field data (e.g., accessibility surfaces), and area or lattice data (e.g., unemployment and mortality rates). Applications of geospatial data and/or spatial analysis are increasingly found in sociological research, especially in studies of spatial inequality, residential segregation, demography, education, religion, neighborhoods and health, and criminology.

General Overview of Spatially Informed Sociology

Many contemporary social problems require analysis of complex patterns of interrelated social, behavioral, economic, and environmental phenomena. In addressing these problems, it has been argued that both spatial thinking and spatial analytical perspectives play an important role. The role of spatial thinking and analysis is clearly articulated in Goodchild, et al. 2000, a comprehensive review of the emerging interest in space and place in recent social science literatures. Indeed, the authors don’t just provide a review, but rather they develop a vision for a spatially integrated social science, whereby the spatial perspective becomes an incubator for interdisciplinary research. Examples of how spatial analysis informs interdisciplinary research can be found in Goodchild and Janelle 2004, a “best practices” book. This edited collection includes state-of-the-art research on a diverse set of substantive topics, including crime incidence in urban environments, migration, population and environment research, and the diffusion of fertility decline in Third World settings. Two recent overview articles by Logan (Logan, et al. 2010; Logan 2012) both provide concise introductions to the challenges and opportunities of spatial analysis in sociology and especially in the areas of community health, population and environment, residential segregation, land use, fertility, and migration research. Logan argues for substantive questions to be linked to more clear spatial thinking and choice of analytical method. The rediscovery of spatial thinking and spatial perspectives within sociology has been promoted in an excellent article, Gieryn 2000, while Lobao, et al. 2007 focuses explicitly on the need to incorporate spatial perspectives in sociological research, broadening the study of (spatial) inequality. Readers are encouraged to also consult the Oxford Bibliographies article on “Place” by John Anderson. Porter and Howell 2012 provides an account of the historical roots of spatial thinking in sociology as well as introduces the application of spatial regression models and hierarchical or multilevel models. In the field of sociology, several substantive areas have embraced spatial thinking and analytical methods; see Inequality: Spatial Dimensions, Residential Segregation, Demography, Education and Education Policy, Health and Place, and Crime.

  • Gieryn, Thomas F. 2000. A space for place in sociology. Annual Review of Sociology 26:463–495.

    DOI: 10.1146/annurev.soc.26.1.463

    This often-cited article argues that sociologists “have a stake in place no matter what they analyze, or how” (quoted from abstract). Gieryn provides exemplars of place-sensitive sociology in studies of inequality, power, politics, social movements, community, deviance, crime, identity, memory, and history.

  • Goodchild, Michael F., Luc Anselin, Richard Appelbaum, and Barbara Harthorn. 2000. Towards spatially integrated social science. International Regional Science Review 23:139–159.

    This paper synthesizes the vision behind the Center for Spatially Integrated Social Science at UC Santa Barbara, an effort to advance and disseminate geographic tools and concepts—spatial analysis, geographic information science, geolibraries—as integrating themes that cut across the traditional disciplinary boundaries of the social and behavioral sciences.

  • Goodchild, Michael F., and Donald G. Janelle, eds. 2004. Spatially integrated social science. Spatial Information Systems. New York: Oxford Univ. Press.

    This is an outstanding collection of applications of spatial analysis and spatial thinking in the social sciences colloquially referred to as the “Best Practices” book. Chapters are grouped on the basis of four levels of analysis: individual/household, neighborhood, region, and multiscale. Contributors are leading scholars, with sociologists, criminologists, and demographers well represented.

  • Lobao, Linda M., Gregory Hooks, and Ann R. Tickamyer, eds. 2007. The sociology of spatial inequality. Albany: State Univ. of New York Press.

    Based on an American Statistical Association/National Science Foundation (ASA/NSF) workshop, this book reasserts spatial thinking/analysis in inequality research. The book is organized around conceptual and methodological issues, studies of spatial inequality, and future directions in spatial sociology. Sociologists are encouraged to pay attention to the scale of geographic levels at which social processes occur.

  • Logan, John R. 2012. Making a place for space: Spatial thinking in social science. Annual Review of Sociology 38:507–524.

    DOI: 10.1146/annurev-soc-071811-145531

    This is a clear articulation of basic concepts, measures, and methods of spatial thinking and spatial analysis. Throughout Logan argues for more emphasis on spatial thinking and that theoretical and substantive concerns ought to guide the use of spatial analytic methods (e.g., greater attention to what a spatial effect represents).

  • Logan, John R., Weiwei Zhang, and Hongwei Xu. 2010. Applying spatial thinking in social science research. GeoJournal 75.1: 15–27.

    DOI: 10.1007/s10708-010-9343-0

    The theme of this paper is that the appropriate use of spatial tools requires careful thinking about spatial concepts. Key concepts are reviewed and methodological innovations are discussed with exemplars taken from applications of spatial models in community health, population and environment, residential segregation, land use, fertility, and migration research.

  • Porter, Jeremy R., and Frank M. Howell. 2012. Geographical sociology: Theoretical foundations and methodological applications in the sociology of location. New York: Springer.

    DOI: 10.1007/978-94-007-3849-2

    Geo-sociology is presented as a synergy between ecologically centered macro theory and the application of spatially centered research methods in the examination of sociological questions. Strengths of this book include chapters on the historical roots of spatial thinking in sociology. The book closes with chapters on hierarchical linear modeling and spatial regression.

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