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Assessment of SDG Indicator 11.3.1 and Urban Growth Trends of Major and Small Cities in South Africa

Author

Listed:
  • Naledzani Mudau

    (South African National Space Agency, Pretoria 0087, South Africa)

  • Dennis Mwaniki

    (Data and Analytics Unit, UN-Habitat, P.O. Box 30030, Nairobi 00100, Kenya)

  • Lesiba Tsoeleng

    (South African National Space Agency, Pretoria 0087, South Africa)

  • Morwapula Mashalane

    (South African National Space Agency, Pretoria 0087, South Africa)

  • Donatien Beguy

    (Data and Analytics Unit, UN-Habitat, P.O. Box 30030, Nairobi 00100, Kenya)

  • Robert Ndugwa

    (Data and Analytics Unit, UN-Habitat, P.O. Box 30030, Nairobi 00100, Kenya)

Abstract

Geospatial technologies play an important role in understanding and monitoring of land cover and land use change which is critical in achieving Sustainable Development Goal (SDG) 11 and related goals. In this study, we assessed SDG Indicator 11.3.1, Ratio of Land Consumption Rate to Population Growth Rate (LCRPGR) and other urban growth trends of four cities in South Africa using Landsat 5 TM and SPOT 2&5 satellite images and census data collected in 1996, 2001 and 2011. The 2011 built-up areas were mapped using South Africa’s SPOT 5 Global Human Settlements Layer (GHSL) system whereas the 1996 and 2001 built-up areas were extracted from Landsat 5 and SPOT 2 satellite imagery using a kNN object-based image analysis technique that uses textural and radiometric features. We used the built-up area layer to calculate the land consumption per capita and total urban change for each city, both of which have been identified as being important explanatory indicators for the ratio of LCRPGR. The assessment shows that the two major cities, Johannesburg and Tshwane, recorded a decline in the ratio of LCRPGR between the periods 1996–2001 and 2001–2011. In contrast, the LCRPGR ratios for secondary cities, Polokwane and Rustenburg increased during the same periods. The results further show that Tshwane recorded an increase in land consumption per capita between 1996 and 2001 followed by a decrease between 2001 and 2011. Over the same time, Johannesburg experienced a gradual decrease in land consumption per capita. On the other hand, Polokwane and Rustenburg recorded a unique growth trend, in which the overall increase in LCRPGR was accompanied by a decrease in land consumption per capita. In terms of land consumption, Tshwane experienced the highest urban growth rate between 1996 and 2001, whereas Johannesburg and Polokwane experienced the highest urban growth rates between 2001 and 2011. The information derived in this study shows the significance of Indicator 11.3.1 in understanding the urbanization trends in cities of different sizes in South Africa and creates a baseline for nationwide assessment of SDG 11.3.1.

Suggested Citation

  • Naledzani Mudau & Dennis Mwaniki & Lesiba Tsoeleng & Morwapula Mashalane & Donatien Beguy & Robert Ndugwa, 2020. "Assessment of SDG Indicator 11.3.1 and Urban Growth Trends of Major and Small Cities in South Africa," Sustainability, MDPI, vol. 12(17), pages 1-18, August.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:17:p:7063-:d:406081
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    Citations

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    Cited by:

    1. Abdullah Addas, 2023. "Influence of Urban Green Spaces on Quality of Life and Health with Smart City Design," Land, MDPI, vol. 12(5), pages 1-19, April.
    2. Roshan Bhandari & Wenchao Xue & Salvatore G. P. Virdis & Ekbordin Winijkul & Thi Phuoc Lai Nguyen & Suraj Joshi, 2023. "Monitoring and Assessing Urbanization Progress in Thailand between 2000 and 2020 Using SDG Indicator 11.3.1," Sustainability, MDPI, vol. 15(12), pages 1-13, June.
    3. Francisco J. Tapiador & Andrés Navarro & Josu Mezo & Sergio de la Llave & Jesús Muñoz, 2021. "Urban Vegetation Leveraging Actions," Sustainability, MDPI, vol. 13(9), pages 1-20, April.
    4. Koroso, Nesru H., 2023. "Urban land policy and urban land use efficiency: An analysis based on remote sensing and institutional credibility thesis," Land Use Policy, Elsevier, vol. 132(C).
    5. Yunchen Wang & Boyan Li & Lei Xu, 2022. "Monitoring Land-Use Efficiency in China’s Yangtze River Economic Belt from 2000 to 2018," Land, MDPI, vol. 11(7), pages 1-13, July.
    6. Ziyan Ling & Weiguo Jiang & Yuan Lu & Yurong Ling & Ze Zhang & Chaoming Liao, 2023. "Continuous Long Time Series Monitoring of Urban Construction Land in Supporting the SDG 11.3.1—A Case Study of Nanning, Guangxi, China," Land, MDPI, vol. 12(2), pages 1-18, February.

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