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Assessing urban sprawl using remote sensing and landscape metrics: A case study of City of Tshwane, South Africa (1984–2015)
Urbanisation is a phenomenon that is of major concern in both developing and developed countries. Uncontrolled urbanisation leads to formal and informal settlements, industrialisation, improvement of transport networks and economic growth. Monitoring, quantifying and mapping urban sprawl as well as establishing the contributors of land cover change are crucial in designing strategies and policies for effective and sustainable land use management. This study determines the spatio-temporal characteristics of urban sprawl in the City of Tshwane (CoT) from 1984 to 2015 using Landsat satellite imagery. Supervised maximum likelihood classification mapped the land cover for the CoT from 1984 to 2015 using archival Landsat TM, ETM+ and OLI datasets. Post-classification change detection techniques coupled with landscape metrics helped to assess and quantify trends and patterns of urban sprawl. Change detection and analysis revealed that over the 31 years of study between 1984 and 2015 there was an increase in built-up areas in the CoT by 109% between 1984 and 2015. Landscape metrics confirmed also the increase in built-up areas in the CoT. Keywords: Built-up areas, GIS, Remote sensing, Landscape metrics, Urban sprawl, CoT
Assessing urban sprawl using remote sensing and landscape metrics: A case study of City of Tshwane, South Africa (1984–2015)
Urbanisation is a phenomenon that is of major concern in both developing and developed countries. Uncontrolled urbanisation leads to formal and informal settlements, industrialisation, improvement of transport networks and economic growth. Monitoring, quantifying and mapping urban sprawl as well as establishing the contributors of land cover change are crucial in designing strategies and policies for effective and sustainable land use management. This study determines the spatio-temporal characteristics of urban sprawl in the City of Tshwane (CoT) from 1984 to 2015 using Landsat satellite imagery. Supervised maximum likelihood classification mapped the land cover for the CoT from 1984 to 2015 using archival Landsat TM, ETM+ and OLI datasets. Post-classification change detection techniques coupled with landscape metrics helped to assess and quantify trends and patterns of urban sprawl. Change detection and analysis revealed that over the 31 years of study between 1984 and 2015 there was an increase in built-up areas in the CoT by 109% between 1984 and 2015. Landscape metrics confirmed also the increase in built-up areas in the CoT. Keywords: Built-up areas, GIS, Remote sensing, Landscape metrics, Urban sprawl, CoT
Assessing urban sprawl using remote sensing and landscape metrics: A case study of City of Tshwane, South Africa (1984–2015)
James Magidi (author) / Fethi Ahmed (author)
2019
Article (Journal)
Electronic Resource
Unknown
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