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Can we spot a neighborhood from the air? Defining neighborhood structure in Accra, Ghana

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Abstract

Slums are home to a large fraction of urban residents in cities of developing nations, but little attempt has been made to go beyond a simple slum/non-slum dichotomy, nor to identify slums more quantitatively than through local reputation. We use census data from Accra, Ghana, to create an index that applies the UN-Habitat criteria for a place to be a slum. We use this index to identify neighborhoods on a continuum of slum characteristics and on that basis are able to locate the worst slums in Accra. These do include the areas with a local reputation for being slums, lending qualitative validation to the index. We show that slums also have footprints that can be identified from data classified from satellite imagery. However, variability among slums in Accra is also associated with some variability in the land cover characteristics of slums.

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References

  • Agyei-Mensah, S. (forthcoming). Poverty and HIV prevalence in Ghana: A geographical perspective. GeoJournal.

  • Anselin, L. (2003). GeoDa (tools for exploratory spatial data analysis). Available from http://sal.agecon.uiuc.edu/csiss/geoda

  • Diez Roux, A. V. (1998). Bringing context back into epidemiology: Variables and fallacies in multilevel analysis. American Journal of Public Health, 88, 216–222.

    Google Scholar 

  • Diez Roux, A. V. (2001). Investigating neighborhood and area effects on health. American Journal of Public Health, 91, 1783–1789.

    Article  Google Scholar 

  • Duque Cardona, J. C. (2004). Design of homogeneous territorial units: A methodological proposal and applications. PhD Dissertation, Departamento de Econometria Estadistica y Economica Espanola, University of Barcelona, Barcelona.

  • Martin, D. G. (2003). Enacting neighborhood. Urban Geography, 24(5), 361–385.

    Google Scholar 

  • Montgomery, M., & Hewett, P. C. (2005). Urban poverty and health in developing countries: Household and neighborhood effects. Demography, 42(3), 397–425.

    Article  Google Scholar 

  • Neuwirth, R. (2005). Shadow cities: A billion squatters, a new urban world. New York: Routledge.

    Google Scholar 

  • Openshaw, S. (1984). The modifiable area unit problem, CATMOG 38. Norwich: Geoabstracts.

    Google Scholar 

  • Openshaw, S., & Rao, L. (1995). Algorithms for reengineering 1991 Census geography. Environment and Planning A, 27, 425–446.

    Article  Google Scholar 

  • Pellow, D. (2002). Landlords and lodgers: Spatial organization in an accra community. Westport, CT: Praeger Publishers.

    Google Scholar 

  • Rashed, T., & Weeks, J. R. (2003). Assessing vulnerability to earthquake hazards through spatial multicriteria analysis of urban areas. International Journal of Geographical Information Science, 17(6), 549–578.

    Article  Google Scholar 

  • Rashed, T., Weeks, J. R., Gadalla, M. S., & Hill, A. G. (2001). Revealing the anatomy of cities through spectral mixture analysis of multispectral imagery: A case study of the greater Cairo region, Egypt. Geocarto International, 16(4), 5–16.

    Google Scholar 

  • Rashed, T., Weeks, J. R., Roberts, D. A., Rogan, J., & Powell, R. (2003). Measuring the physical composition of urban morphology using multiple endmember spectral mixture analysis. Photogrammetric Engineering and Remote Sensing, 69(9), 1111–1120.

    Google Scholar 

  • Ridd, M. (1995). Exploring a V-I-S (vegetation-imperious surface-soil) model or urban ecosystem analysis through remote sensing: Comparative anatomy of cities. International Journal of Remote Sensing, 16, 2165–2185.

    Article  Google Scholar 

  • Roy, A., & Alsayyad, N. (Eds.). (2004). Urban informality: Transnational perspectives from the Middle East, Latin America, and South Asia. Lanham, MD: Lexington Books.

    Google Scholar 

  • Sampson, R. J. (2003). Neighborhood-level context and health: Lessons from sociology. In I. Kawachi, & L. F. Berkman (Eds.), Neighborhoods and health. New York: Oxford University Press.

    Google Scholar 

  • Sampson, R. J., & Laub, J. H. (1990). Crime and deviance over the life course: The salience of adult social bonds. American Sociological Review, 55, 609–627.

    Article  Google Scholar 

  • Sampson, R. J., & Morenoff, J. D. (2003). Spatial (dis)advantage and homicide in Chicago neighborhoods. In M. F. Goodchild, & D. G. Janelle (Eds.), Spatially integrated social science. New York: Oxford University Press.

    Google Scholar 

  • Songsore, J., & Goldstein, G. (1995). Health and environment analysis for decision-making: Field study in Accra, Ghana. World Health Statistics Quarterly, 48(2), 108–117.

    Google Scholar 

  • Songsore, J., & McGranahan, G. (1998). The political economy of household environmental management: Gender, environment and epidemiology in the greater Accra Metropolitan area. World Development, 26(3), 395–412.

    Article  Google Scholar 

  • Stephens, C., Timaeus, I., Akerman, M., Avie, S., Maia, P. B., Campanario, P., Doe, B., Lush, L., & Tetteh, D. (1994). Environment and health in developing countries: An analysis of intra-urban mortality differentials using existing data. Collaborative Studies in Accra, Ghana and Sao Paolo, Brazil and Analysis of Urban Data of Four Demographic Health Surveys.

  • Taylor, P., Bousson, C. R., Awunyo-Akaba, J., & Nelson, J. (2002). Ghana: Urban health assessment. Washington, DC: Environmental Health Project, US Agency for International Development.

    Google Scholar 

  • Tobler, W. (1970). A computer movie simulating urban growth in the Detroit region. Economic Geography, 26, 234–240.

    Article  Google Scholar 

  • Tobler, W. (2004). On the first law of geography: A reply. Annals of the Association of American Geographers, 94(2), 304–310.

    Article  Google Scholar 

  • UN Habitat. (2006). State of the world’s cities 2006/7. New York: United Nations.

    Google Scholar 

  • United Nations Population Division. (2006a). World urbanization prospects: The 2005 revision. New York: United Nations.

  • United Nations Population Division. (2006b). World urbanization prospects: The 2005 revisions. New York: United Nations.

  • Weeks, J. R. (2004). Using remote sensing and geographic information systems to identify the underlying properties of urban environments. In A. G. Champion, & G. Hugo (Eds.), New forms of urbanization: Conceptualizing and measuring human settlement in the twenty-first century. London: Ashgate.

    Google Scholar 

  • Weeks, J. R., Getis, A., Hill, A. G., Gadalla, M. S., & Rashed, T. (2004). The fertility transition in Egypt: Intra-urban patterns in Cairo. Annals of the Association of American Geographers, 94(1), 74–93.

    Article  Google Scholar 

  • Weeks, J. R., Larson, D., & Fugate, D. (2005). Patterns of urban land use as assessed by satellite imagery: An application to Cairo, Egypt. In B. Entwisle, & P. C. Stern (Eds.), Population, land use, and environment: Research directions (pp. 265–286). Washington, DC: National Academies Press.

    Google Scholar 

  • Wise, S., Haining, R., & Ma, J. (2001). Providing spatial statistical data analysis functionality for the GIS user: The SAGE project. International Journal of Geographical Information Science, 15(3), 239–254.

    Article  Google Scholar 

  • Yankson, P. W., Kofie, R. Y., & Moller-Jensen, L. (forthcoming). Monitorning urban growth: Urbanization of the fringe areas of Accra. Bulletin of the Ghana Geographical Association.

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Acknowledgments

This research was supported by grant number R21 HD046612-01 from the National Institute of Child Health and Human Development. This is a revision of a paper presented at the Annual Meeting of the Association of American Geographers, Chicago, IL, 2006.

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Authors and Affiliations

  1. San Diego State University, 5500 Campanile Drive, San Diego, CA, USA

    John R. Weeks, Douglas Stow, Arthur Getis & Debbie Fugate

  2. Harvard University, Cambridge, MA, USA

    Allan Hill

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  1. John R. Weeks
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  2. Allan Hill
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  3. Douglas Stow
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  4. Arthur Getis
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  5. Debbie Fugate
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Correspondence to John R. Weeks.

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Weeks, J.R., Hill, A., Stow, D. et al. Can we spot a neighborhood from the air? Defining neighborhood structure in Accra, Ghana. GeoJournal 69, 9–22 (2007). https://doi.org/10.1007/s10708-007-9098-4

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