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You can find the transcript through this link.

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Are you interested in how urban sprawl affects sustainable urban development? 

Summary of the article titled Urban sprawl and its impact on sustainable urban development: a combination of remote sensing and social media data from 2021 by Zhenfeng Shao, Neema S. Sumari, Aleksei Portnov, Fanan Ujoh, Walter Musakwa and Paulo J. Mandela, published in the Geo-Spatial information Science journal. 

Since we are investigating the future of cities, I thought it would be interesting to see how urban sprawl affects urban services. This article presents the case of Morogoro in Africa, and the results that sensing and population data can be useful for interpreting urban sprawl and access to urban services.

As the most important things, I would like to highlight 3 aspects:

1. Urban sprawl generally refers to the unrestricted growth in many urban areas of housing, commercial development and roads over large expanses of land with little concern to urban planning.
2. Urban expansion has had significant impacts on poverty, living conditions and environmental quality within the sprawl areas of the Morogoro urban municipality, and with that, ecosystem services supporting human and natural populations also declined.
3. Planning and regulation need to lead to a planned and sustainable future that will be ecologically sensitive, support conservation and biodiversity and provide a safe habitation for urban dwellers.

You can find the article through this link.

Abstract: Urbanization 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.

Connecting episodes you might be interested in:

• No.005R – Smart cities, big data, and urban policy;
• No.123 – Interview with Alex Louey about urban sustainable development and technological opportunities to make business from sustainability; 

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