Abstract
The United Nations estimates that the global population is going to be double in the coming 40 years, which may cause a negative impact on the environment and human life. Such an impact may instigate increased water demand, overuse of power, anthropogenic noise, etc. Thus, modelling the Urban Environmental Quality (UEQ) becomes indispensable for a better city planning and an efficient urban sprawl control. This study aims to investigate the ability of using remote sensing and Geographic Information System (GIS) techniques to model the UEQ with a case study in the city of Toronto via deriving different environmental, urban and socio-economic parameters. Remote sensing, GIS and census data were first obtained to derive environmental, urban and socio-economic parameters. Two techniques, GIS overlay and Principal Component Analysis (PCA), were used to integrate all of these environmental, urban and socio-economic parameters. Socio-economic parameters including family income, higher education and land value were used as a reference to assess the outcomes derived from the two integration methods. The outcomes were assessed through evaluating the relationship between the extracted UEQ results and the reference layers. Preliminary findings showed that the GIS overlay represents a better precision and accuracy (71% and 65%), respectively, comparing to the PCA technique. The outcomes of the research can serve as a generic indicator to help the authority for better city planning with consideration of all possible social, environmental and urban requirements or constraints.
Highlights
Urban Environmental Quality (UEQ) is defined as an indicator to generically describe the urban, environmental and socio-economic condition of an urban area
Land Surface Temperature (LST) LST is an essential parameter in a variety of disciplines used to study the urban climate [24,25], UEQ [8], urban heat island effect [26], urban expansion [27] and urban waste management [28]
That is mainly because the Geographic Information System (GIS) overlay method uses all of the parameters where some of the parameters may have a negative correlation with the reference layer, which may influence the overall result
Summary
Urban Environmental Quality (UEQ) is defined as an indicator to generically describe the urban, environmental and socio-economic condition of an urban area. Weng and Quattrochi [1] addressed that UEQ has the capability to influence many governing aspects, including urban planning, infrastructure management, economic influence, policy-making and social studies. Satellite remote sensing techniques can help in modelling UEQ through providing continuous Earth observation images of the urban environment at different spatial, spectral and temporal resolutions [2,3,4]. A few preliminary attempts were found using multi-temporal and multi-resolution data to model UEQ [5,6,7,8], since these data can provide a clear vision for visualizing and understanding the land cover, water conditions and vegetation in urban areas [9,10]. A number of representative studies were found in the literature that demonstrated how to use multi-source data to model and assess the UEQ
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