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

Journal article


Shao, Z., Sumari, N., Portnov, A., Ujoh, F., Musakwa, W. and Mandela, Paulo J. (2020). Urban sprawl and its impact on sustainable urban development: a combination of remote sensing and social media data. Geo-spatial Information Science. 24 (1), pp. 241-255. https://doi.org/10.1080/10095020.2020.1787800
AuthorsShao, Z., Sumari, N., Portnov, A., Ujoh, F., Musakwa, W. and Mandela, Paulo J.
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and forests which provide essential ecosystem services such as carbon sequestration and support for biodiversity have been replaced by built-up land cover.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.

KeywordsComputers in Earth Sciences; Geography, Planning and Development
Year2020
JournalGeo-spatial Information Science
Journal citation24 (1), pp. 241-255
PublisherInforma UK Limited
ISSN1009-5020
1993-5153
Digital Object Identifier (DOI)https://doi.org/10.1080/10095020.2020.1787800
Funder/ClientNational Natural Science Foundation of China
National key R&D plan on strategic international scientific and technological innovation cooperation special project
Natural Science Fund of Hubei Province in China
Publication dates
Online28 Jul 2020
Publication process dates
Accepted21 Jul 2021
Deposited07 Jun 2021
Publisher's version
License
File Access Level
Open
Licensehttp://creativecommons.org/licenses/by/4.0/
Page range1-15
Permalink -

https://openresearch.lsbu.ac.uk/item/8q41q

  • 195
    total views
  • 506
    total downloads
  • 3
    views this month
  • 12
    downloads this month

Export as

Related outputs

Urban growth dynamics and expansion forms in 11 Tanzanian cities from 1990 to 2020
Sumari, N., Ujoh, F., Samwel Swai, C. and Zheng, M. (2023). Urban growth dynamics and expansion forms in 11 Tanzanian cities from 1990 to 2020. International Journal of Digital Earth. 16 (1), pp. 1985-2001. https://doi.org/10.1080/17538947.2023.2218114
Identification and mitigation of high-risk pregnancy with the Community Maternal Danger Score Mobile Application in Gboko, Nigeria.
Bola, R., Ujoh, F. and Lett, R. (2022). Identification and mitigation of high-risk pregnancy with the Community Maternal Danger Score Mobile Application in Gboko, Nigeria. PLoS ONE. 17 (9), p. e0275442. https://doi.org/10.1371/journal.pone.0275442
Assessment and validation of the Community Maternal Danger Score algorithm.
Bola, R., Ujoh, F., Ukah, U.V. and Lett, R. (2022). Assessment and validation of the Community Maternal Danger Score algorithm. Global health research and policy. 7 (1), p. 6. https://doi.org/10.1186/s41256-022-00240-8
Meteorological Drought Analysis and Return Periods over North and West Africa and Linkage with El Niño−Southern Oscillation (ENSO)
Henchiri, M., Igbawua, T., Javed, T., Bai, Y., Zhang, S., Essifi, B., Ujoh, F. and Zhang, J. (2021). Meteorological Drought Analysis and Return Periods over North and West Africa and Linkage with El Niño−Southern Oscillation (ENSO). Remote Sensing. 13 (23), p. e4730. https://doi.org/10.3390/rs13234730
Suitability mapping for rice cultivation in Benue State, Nigeria using satellite data
Ujoh, F., Igbawua, T. and Ogidi Paul, M. (2019). Suitability mapping for rice cultivation in Benue State, Nigeria using satellite data. Geo-spatial Information Science. 22 (4), pp. 332-344. https://doi.org/10.1080/10095020.2019.1637075