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.
| Original language | English |
|---|---|
| Pages (from-to) | 325-335 |
| Journal | Korean Journal of Remote Sensing |
| Volume | 22 |
| Issue number | 5 |
| DOIs | |
| State | Published - 30 Oct 2006 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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SDG 11 Sustainable Cities and Communities
Keywords
- Satellite Image
- Socioeconomic Data
- GIS
- Urban Quality of Life
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Dive into the research topics of 'Urban Quality of Life Assessment Using Satellite Image and Socioeconomic Data in GIS'. Together they form a unique fingerprint.Research output
- 1 Article
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Exploring the Spatial Relationships between Environmental Equity and Urban Quality of Life
Jun, B.-W., 30 Sep 2011, In: Journal of the Korean Association of Geographic Information Studies. 14, 3, p. 223-235Research output: Contribution to journal › Article › peer-review
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