Urban sprawl and its impact on sustainable urban development: a combination of remote sensing and social media data

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dc.creatorShao, Zhenfeng
dc.creatorSumari, Neema S.
dc.creatorPortnov, Aleksei
dc.creatorUjoh, Fanan
dc.creatorMusakwa, Walter
dc.creatorMandela, Paulo J.
dc.date2021-01-29T07:23:22Z
dc.date2021-01-29T07:23:22Z
dc.date2020-07-28
dc.date.accessioned2022-10-25T08:52:08Z
dc.date.available2022-10-25T08:52:08Z
dc.descriptionUrbanization is one of the most impactful human activities across the world today affecting the quality of urban life and its sustainable development. Urbanization in Africa is occurring at an unprecedented rate and it threatens the attainment of Sustainable Development Goals (SDGs). Urban sprawl has resulted in unsustainable urban development patterns from social, environmental, and economic perspectives. This study is among the first examples of research in Africa to combine remote sensing data with social media data to determine urban sprawl from 2011 to 2017 in Morogoro urban municipality, Tanzania. Random Forest (RF) method was applied to accomplish imagery classification and location-based social media (Twitter usage) data were obtained through a Twitter Application Programming Interface (API). Morogoro urban municipality was classified into built-up, vegetation, agriculture, and water land cover classes while the classification results were validated by the generation of 480 random points. Using the Kernel function, the study measured the location of Twitter users within a 1 km buffer from the center of the city. The results indicate that, expansion of the city (built-up land use), which is primarily driven by population expansion, has negative impacts on ecosystem services because pristine grasslands and forests which provide essential ecosystem services such as carbon sequestration and support for biodiversity have been replaced by built-up land cover. In addition, social media usage data suggest that there is the concentration of Twitter usage within the city center while Twitter usage declines away from the city center with significant spatial and numerical increase in Twitter usage in the study area. The outcome of the study suggests that the combination of remote sensing, social sensing, and population data were useful as a proxy/inference for interpreting urban sprawl and status of access to urban services and infrastructure in Morogoro, and Africa city where data for urban planning is often unavailable, inaccurate, or stale.
dc.formatapplication/pdf
dc.identifierShao, Z., Sumari, N. S., Portnov, A., Ujoh, F., Musakwa, W. & Mandela, J. P. (2020). Urban Sprawl and its impact on sustainable urban development: A combination of remote sensing and social media data, Geo-spatial Information Science: https://doi.org/10.1080/10095020.2020.1787800
dc.identifierhttps://www.suaire.sua.ac.tz/handle/123456789/3371
dc.identifier.urihttp://hdl.handle.net/123456789/92267
dc.languageen_US
dc.publisherGeo-spatial Information Science
dc.subjectUrbanization
dc.subjectecosystem services
dc.subjectsustainable urban development
dc.subjectremote sensing
dc.subjectsocial media data
dc.subjectTwitter
dc.subjectMorogoro
dc.subjectTanzania
dc.titleUrban sprawl and its impact on sustainable urban development: a combination of remote sensing and social media data
dc.typeArticle

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