Abstract
There have been few attempts to map or monitor urban environmental quality (UEQ) at a detailed level, or as a holistic concept comprising multiple parameters. This study examines methods and scales for integrating six parameters of UEQ which are measured in different units and operate at different scales, into a single index for mapping UEQ differences over an urban area, the Kowloon Peninsula, Hong Kong. The parameters comprise vegetation density, heat island intensity, aerosol optical depth, building density, building height, and noise. Two approaches for spatial data integration - principal component analysis (PCA) and GIS overlay - were examined for integrating the datasets at three different levels of detail, namely electoral-district level, and raster datasets at 4 m and 64 m resolution. At all levels of detail mapped, the GIS overlay method was found to be more representative of UEQ as perceived in the field than when parameters were combined by PCA, High (4 m) spatial resolution was more representative than either 64 m resolution or UEQ mapped within electoral districts. The combined parameters vegetation density, building density, and building height gave a better index of UEQ than all six parameters combined, or any individual parameter or combination, and the best single indicator of UEQ was found to be vegetation density. Since vegetation density, building density, and building height are now relatively easy to obtain at detailed level from GIS databases or high-resolution satellite images, planning and environmental authorities may use the derived UEQ index as an objective measure of environmental quality over a whole city, for comparisons between places and cities and for monitoring changes over time.
Original language | English |
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Pages (from-to) | 170-185 |
Number of pages | 16 |
Journal | Environment and Planning B: Planning and Design |
Volume | 36 |
Issue number | 1 |
DOIs | |
Publication status | Published - 1 Jan 2009 |
ASJC Scopus subject areas
- Geography, Planning and Development
- General Environmental Science