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Urban Sustainability: Integrating Socioeconomic and Environmental Data for Multi-Objective Assessment

Author

Listed:
  • Yichun Xie

    (Department of Geography and Geology, Eastern Michigan University, Ypsilanti, MI 48197, USA)

  • Chao Liu

    (School of Spatial Informatics and Geomatics Engineering, Anhui University of Science and Technology, Huainan 232001, China)

  • Shujuan Chang

    (Inner Mongolia Key Laboratory of Remote Sensing of Grassland and Emergency Response Technic, Inner Mongolia Forestry and Grassland Monitoring and Planning Institute, Hohhot 010020, China)

  • Bin Jiang

    (Division of GIScience, Faculty of Engineering and Sustainable Development, University of Gävle, SE-80176 Gävle, Sweden)

Abstract

The large concentration of the world’s population in cities, along with rapid urbanization, have brought numerous environmental and socioeconomic challenges to sustainable urban systems (SUS). However, current SUS studies focus heavily on ecological aspects, rely on SUS indicators that are not supported by available data, lack comprehensive analytical frameworks, and neglect SUS regional differences. This paper develops a novel approach to assessing urban sustainability from regional perspectives using commonly enumerated socioeconomic statistics. It integrates land use and land cover change data and ecosystem service values, applies data mining analytics to derive SUS indicators, and evaluates SUS states as trade-offs among relevant SUS indicators. This synthetic approach is called the integrated socioeconomic and land-use data mining–based multi-objective assessment (ISL-DM-MOA). The paper presents a case study of urban sustainability development in cities and counties in Inner Mongolia, China, which face many environmental and sustainable development problems. The case study identifies two SUS types: (1) several large cities that boast well-developed economies, diversified industrial sectors, vital transportation locations, good living conditions, and cleaner environments; and (2) a few small counties that have a small population, small urban construction areas, extensive natural grasslands, and primary grazing economies. The ISL-DM-MOA framework innovatively synthesizes currently available socioeconomic statistics and environmental data as a unified dataset to assess urban sustainability as a total socio-environmental system. ISL-DM-MOA deviates from the current indicator approach and advocates the notion of a data-mining-driven approach to derive urban sustainability dimensions. Furthermore, ISL-DM-MOA diverges from the concept of a composite score for determining urban sustainability. Instead, it promotes the concept of Pareto Front as a choice set of sustainability candidates, because sustainability varies among nations, regions, and locations and differs between political, economic, environmental, and cultural systems.

Suggested Citation

  • Yichun Xie & Chao Liu & Shujuan Chang & Bin Jiang, 2022. "Urban Sustainability: Integrating Socioeconomic and Environmental Data for Multi-Objective Assessment," Sustainability, MDPI, vol. 14(15), pages 1-21, July.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:15:p:9142-:d:871883
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    References listed on IDEAS

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    1. Shuzhen Mao & Jiyun She & Yi Zhang, 2023. "Spatial-Temporal Evolution of Land Use Change and Eco-Environmental Effects in the Chang-Zhu-Tan Core Area," Sustainability, MDPI, vol. 15(9), pages 1-16, May.
    2. Batara Surya & Patmawaty Taibe & Syahrul Sariman & Hernita Hernita & Agus Salim & Nasrullah Nasrullah & Arie Gunawan Hazairin Zubair, 2023. "Renewable Energy Utilization and Environmental Pollution Control in the New City Area Mamminasata Metropolitan, Indonesia," International Journal of Energy Economics and Policy, Econjournals, vol. 13(1), pages 213-226, January.

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