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Continuous Long Time Series Monitoring of Urban Construction Land in Supporting the SDG 11.3.1—A Case Study of Nanning, Guangxi, China

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  • Ziyan Ling

    (Beijing Key Laboratory for Remote Sensing of Environment and Digital Cities, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
    College of Geography and Planning, Nanning Normal University, Nanning 530001, China)

  • Weiguo Jiang

    (Beijing Key Laboratory for Remote Sensing of Environment and Digital Cities, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

  • Yuan Lu

    (College of Geography and Planning, Nanning Normal University, Nanning 530001, China)

  • Yurong Ling

    (College of Geography and Planning, Nanning Normal University, Nanning 530001, China)

  • Ze Zhang

    (Beijing Key Laboratory for Remote Sensing of Environment and Digital Cities, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

  • Chaoming Liao

    (College of Natural Resources and Surveying and Mapping, Nanning Normal University, Nanning 530001, China)

Abstract

Enhancing the spatio-temporal dynamic monitoring of the construction land of emerging major cities provides the basis for understanding the effects of human activities on the earth’s ecological environment changes, which is regarded as an important way to improve human wellbeing and to achieve the UN SDGs. This paper, which uses Nanning as an example, adopts 30 m annual remote sensing land cover datasets from 1990–2021 to elaborately analyze the temporal evolution and spatial expansion of construction land and to evaluate the sustainable development level based on SDG 11.3.1. The conclusions of this paper are as follows: (1) For Nanning City, during 1990–2021, construction land area increased from 54.77 km 2 to 326.33 km 2 —a nearly five-fold increase. Spreading expansion and finger-like expansion along roads played a leading role during the development of the construction land in Nanning. Liangqing and Yongning are the future directions of urban development. The LCRPGR of Nanning declined with one peak period around 1995, and the LCRPGR was relatively stable with a high intensity of land use. (2) For the other emerging major cities, continuous long duration data are more suitable for urban construction land monitoring compared with traditional sparse time-series monitoring. The rich information derived from continuous long duration data can help decision makers to formulate and implement more comprehensive measures. The research paradigm adopted in this study can be applied in other cities. The newly developed urban districts will have foreseeable high sustainable development risks, and urban development strategies at the international, national, and urban levels could reduce those risks and promote the realization of UN SDGs from different angles and with different intensities.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jlands:v:12:y:2023:i:2:p:452-:d:1064078
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    References listed on IDEAS

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    2. Marcello Schiavina & Michele Melchiorri & Christina Corbane & Aneta J. Florczyk & Sergio Freire & Martino Pesaresi & Thomas Kemper, 2019. "Multi-Scale Estimation of Land Use Efficiency (SDG 11.3.1) across 25 Years Using Global Open and Free Data," Sustainability, MDPI, vol. 11(20), pages 1-25, October.
    3. Camagni, Roberto & Gibelli, Maria Cristina & Rigamonti, Paolo, 2002. "Urban mobility and urban form: the social and environmental costs of different patterns of urban expansion," Ecological Economics, Elsevier, vol. 40(2), pages 199-216, February.
    4. 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.
    5. Wei Zhang & Gabriele Villarini & Gabriel A. Vecchi & James A. Smith, 2018. "Urbanization exacerbated the rainfall and flooding caused by hurricane Harvey in Houston," Nature, Nature, vol. 563(7731), pages 384-388, November.
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