Korean Journal of Remote Sensing (대한원격탐사학회지)

Korean Society of Remote Sensing (대한원격탐사학회)
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Urban Quality of Life Assessment Using Satellite Image and Socioeconomic Data in GIS

  • Jun, Byong-Woon (Department of Social Sciences, Louisiana Tech University)
  • Published : 2006.10.31
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Abstract

This paper evaluates and maps the quality of life in the Atlanta, Georgia metropolitan area in 2000. Three environmental variables from Landsat TM data, four socioeconomic variables from census data, and a hazard-related variable from toxic release inventory (TRI) database were integrated into a geographic information system (GIS) environment for the quality of life assessment. To solve the incompatibility problem in areal units among different data, the four socioeconomic variables aggregated by zonal units were spatially disaggregated into individual pixels. Principal components analysis (PCA) was employed to integrate and transform environmental, socioeconomic, and hazard-related variables into a resultant quality of life score for each pixel. Results indicate that the highest quality of life score was found around Sandy Springs, Roswell, Alphretta, and the northern parts of Fulton County along Georgia 400 whereas the lowest quality of life score was clustered around Smyma of Cobb County, the inner city of Atlanta, and Hartsfield-Jackson International Airport. The results also reveals that normalized difference vegetation index (NDVI) and relative risk from TRI facilities are two versatile indicators of environmental and socioeconomic quality of an urban area in the United States.

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References

  1. Bederman, S. H. and T. A. Hartshorn, 1984. Quality of life in Georgia: the 1980 experience. Southeastern Geographer, 24(2): 78-98 https://doi.org/10.1353/sgo.1984.0008
  2. Cutter, S. L., M. E. Hodgson, and K. Dow, 2001. Subsidized inequities: the spatial patterning of environmental risks and federally assisted housing. Urban Geography, 22(1): 29-53 https://doi.org/10.2747/0272-3638.22.1.29
  3. Jensen, J. R., 1996. Introductory Digital Image Processing: A Remote Sensing Perspective, Prentice Hall, Upper Saddler River, NJ, USA
  4. Forster, B., 1983. Some urban measurements from Landsat data. Photogrammetric Engineering and Remote Sensing, 49(12): 1693-1707
  5. Goodchild, M. F. and N. S-N. Lam, 1980. Areal interpolation: a variant of the traditional spatial problem. Geoprocessing, 1: 297-312
  6. Liu, B. C., 1976. Quality of Life Indicators in U. S. Metropolitan Areas, 1970, Midwest Research Institute, Kansas City, MO, USA
  7. Liu, F., 2001. Environmental Justice Analysis: Theories, Methods, and Practice, Lewis Publishers, New York, NY, USA
  8. Lo, C. P. and B. J. Faber, 1997. Integration of Landsat thematic mapper and census data for quality of life assessment. Remote Sensing of Environment, 62: 143-157 https://doi.org/10.1016/S0034-4257(97)00088-6
  9. Lo, C. P., D. A. Quattrochi, and J. C. Luvall, 1997. Application of high-resolution thermal infrared remote sensing and GIS to assess the urban heat island effect. International Journal of Remote Sensing, 18(2): 287-304 https://doi.org/10.1080/014311697219079
  10. Martin, D. and I. Bracken, 1993. The integration of socioeconomic and physical resource data for applied land management information systems. Applied Geography, 13: 45-53 https://doi.org/10.1016/0143-6228(93)90079-G
  11. Mennis, J., 2003. Generating surface models of population using dasymetric mapping. The Professional Geographer, 55(1): 31-42
  12. Mesev, V. (ed.), 2003. Remotely Sensed Cities, Taylor & Francis, New York, NY, USA
  13. Nichol, J. E., 1994. A GIS-based approach to microclimatic monitoring in Singapore's high-rise housing estates. Photogrammetric Engineering and Remote Sensing, 60(10): 1225-1232
  14. Smith, D. M., 1973. The Geography of Social Wellbeing in the United States, McGraw Hill, New York, NY, USA
  15. Wallace, S., 1971. Quality of life. Journal of Home Economics, 66: 7-8
  16. Weber, C. and J. Hirsh, 1992. Some urban measurements from SPOT data: urban life quality indices. International Journal of Remote Sensing, 13(17): 3251-3261 https://doi.org/10.1080/01431169208904116
  17. Wukelic, G. E., D. E. Gibbons, L. M. Martucci, and H. P. Foote, 1989. Radiometric calibration of Landsat thematic mapper thermal band. Remote Sensing of Environment, 28: 339-347 https://doi.org/10.1016/0034-4257(89)90125-9