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• W2469155866 abstract "The highly populated coastal cities and towns in Australia are also most vulnerable places to climate change induced by increased greenhouse gas (GHG) emission through anthropogenic activities. It is estimated that urban areas account for 60-80% of the global energy use and emit more than 70% of global greenhouse gases. Since most future population growth is expected to be in urban areas, one main question regarding urban planning is how new urban communities should be developed in order to minimise resource consumption and carbon emissions. This study develops a spatially explicit model to simulate the carbon footprint of a coastal town called Point Cook in Victoria under three development scenarios: 1) the horizontal (the business as usual (BAU)), 2) the vertical (Le Corbusier’s ‘Radiant City’), and 3) the mixed. By using selected neighbourhoods in Melbourne as case study areas, this research will develop a spatially explicit model that integrates geographical characteristics, urban form, street-network structure, housing type, population density, energy supply, etc. to evaluate the carbon footprint associated with different development scenarios. Data for model calibration are collected from VicLand (for land use information including transport, vegetation, hydrology, planning, and elevation) and the Australian Bureau of Statistics (for attributes about population and social development)). The findings will provide timely information relevant to the debate about suburban sprawl and low impact development and to decision-making in the design and development of low carbon communities. It is hoped that this research will improve the capacity to achieve national goals in carbon emission reduction in Australia." @default.
• W2469155866 created "2016-07-22" @default.
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• W2469155866 date "2015-12-11" @default.
• W2469155866 modified "2023-09-27" @default.
• W2469155866 title "Carbon Footprint of an Australian Coastal Town: An Assessment of Three Planning Scenarios at Neighbourhood Level" @default.
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• W2469155866 hasPublicationYear "2015" @default.
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