An Analysis of the Relationship between Spatial Patterns of Water Quality and Urban Development in Shanghai, China
- UNCG Author/Contributor (non-UNCG co-authors, if there are any, appear on document)
- Susan M. Walcott, Professor (Creator)
- Institution
- The University of North Carolina at Greensboro (UNCG )
- Web Site: http://library.uncg.edu/
Abstract: Recent urban development in Shanghai, the largest city in China, and its impact on the water environment are examined in this study. The area of built-up surface was obtained from the classification of the Landsat 7 ETM+ images of the year 2000 for Shanghai. The proportion of built-up surface and population density were extracted from buffer zones with radii ranging from 100 to 2000 m, and used in regression analysis against various water quality parameters at 44 water quality monitoring stations across metropolitan Shanghai. Results suggest that in most cases, the pattern of urban land use as represented by the built-up surface was a stronger predictor than population density in explaining spatial patterns of water quality parameters in Shanghai. The best models of most water quality parameters were found for buffer zones of 2000 m radius rather than for smaller buffers, indicating the regional nature of the factors that influence water quality in the study area. Evidence suggests that strong associations between land use, population density, and water quality result from the contribution of untreated domestic wastewater and non-point pollution sources to waterways in Shanghai. Such relationships should remain strong in the near future until measures to increase the capacity of wastewater treatment and control of non-point pollution sources are fully implemented.
An Analysis of the Relationship between Spatial Patterns of Water Quality and Urban Development in Shanghai, China
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Additional Information
- Publication
- Computers, Environment and Urban Systems 29(2): 197-221
- Language: English
- Date: 2005
- Keywords
- Water quality, Shanghai, Urbanization, GIS, Remote Sensing