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Spatiotemporal Evolution and Coupling Pattern Analysis of Urbanization and Ecological Environmental Quality of the Chinese Loess Plateau

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  • Kaizheng Xiang

    (College of Mining and Geomatics, Hebei University of Engineering, Handan 056038, China)

  • Anzhou Zhao

    (College of Mining and Geomatics, Hebei University of Engineering, Handan 056038, China
    State Key Laboratory of Resources and Environmental Information System, Chinese Academy of Sciences, Beijing 100101, China)

  • Haixin Liu

    (College of Mining and Geomatics, Hebei University of Engineering, Handan 056038, China)

  • Xiangrui Zhang

    (College of Mining and Geomatics, Hebei University of Engineering, Handan 056038, China)

  • Anbing Zhang

    (College of Mining and Geomatics, Hebei University of Engineering, Handan 056038, China)

  • Xinle Tian

    (College of Mining and Geomatics, Hebei University of Engineering, Handan 056038, China)

  • Zihan Jin

    (College of Mining and Geomatics, Hebei University of Engineering, Handan 056038, China)

Abstract

Understanding the interactive coupling mechanism between urbanization and eco-environmental quality is crucial to achieve the goal of urban sustainable development. The Chinese Loess Plateau (CLP) was taken as the research object, and the city nighttime light index (CNLI) and remote sensing ecological index with local adaptability (LARSEI) were constructed based on the data from the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS), National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP/VIIRS), and Moderate Resolution Imaging Spectroradiometer (MODIS). Then, trend analysis, standard deviation ellipse (SDE), coupling degree (C), and coupling coordination degree (CCD) models were used to determine the spatiotemporal variation of urbanization and eco-environmental quality and its coupling relationship. The results show that: (1) the urbanization level of the CLP showed a trend of continuous improvement from 2000 to 2019. A significant increasing trend was found from the CNLI (slope CNLI = 0.0030 yr −1 , p < 0.01), and its value rose from 0.07 in 2000 to 0.14 in 2019. In terms of spatial distribution, a multi-core distribution pattern with provincial capital cities as the core was presented in the CLP. The cities expanded at different degrees and presented a gradual concentrated expansion towards the southeast on the whole. (2) The eco-environmental quality in the CLP greatly increased during 2000 to 2019. An area with an increasing trend in the remote sensing ecological index with local adaptability (LARSEI) accounted for 58.82% and was mainly concentrated in the west and central part of the CLP. (3) The C and CCD between urbanization and eco-environmental quality in the CLP presented a trend of significant increase during 2000 to 2019 (slope C = 0.0051 yr −1 , p < 0.01; slope CCD = 0.0040 yr −1 , p < 0.01). The cities with a higher coupling degree were mainly located in the southeastern and northern parts of the CLP, while those with a higher coordination degree were scattered in the marginal parts of the CLP. The research results can provide suggestions for decision-making to achieve high-quality coordinated development of the cities in the CLP.

Suggested Citation

  • Kaizheng Xiang & Anzhou Zhao & Haixin Liu & Xiangrui Zhang & Anbing Zhang & Xinle Tian & Zihan Jin, 2022. "Spatiotemporal Evolution and Coupling Pattern Analysis of Urbanization and Ecological Environmental Quality of the Chinese Loess Plateau," Sustainability, MDPI, vol. 14(12), pages 1-19, June.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:12:p:7236-:d:837786
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    References listed on IDEAS

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    1. Congjian Sun & Xiaoming Li & Wenqiang Zhang & Xingong Li, 2020. "Evolution of Ecological Security in the Tableland Region of the Chinese Loess Plateau Using a Remote-Sensing-Based Index," Sustainability, MDPI, vol. 12(8), pages 1-17, April.
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    3. Jingtao Wang & Haibin Liu & Hao Liu & Hui Huang, 2021. "Spatiotemporal Evolution of Multiscale Urbanization Level in the Beijing-Tianjin-Hebei Region Using the Integration of DMSP/OLS and NPP/VIIRS Night Light Datasets," Sustainability, MDPI, vol. 13(4), pages 1-28, February.
    4. Cheng, Jinhua & Dai, Sheng & Ye, Xinyue, 2016. "Spatiotemporal heterogeneity of industrial pollution in China," China Economic Review, Elsevier, vol. 40(C), pages 179-191.
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    2. Zedong Yang & Hui Sun & Weipeng Yuan & Xuechao Xia, 2022. "The Spatial Pattern of the Prefecture-Level Carbon Emissions and Its Spatial Mismatch in China with the Level of Economic Development," Sustainability, MDPI, vol. 14(16), pages 1-20, August.
    3. Yiting Su & Jing Li & Dongchuan Wang & Jiabao Yue & Xingguang Yan, 2022. "Spatio-Temporal Synergy between Urban Built-Up Areas and Poverty Transformation in Tibet," Sustainability, MDPI, vol. 14(14), pages 1-22, July.
    4. Sishi Wang & Xin Tan & Fenglei Fan, 2023. "Changes in Impervious Surfaces in Lhasa City, a Historical City on the Qinghai–Tibet Plateau," Sustainability, MDPI, vol. 15(6), pages 1-16, March.
    5. Ming Shi & Fei Lin & Xia Jing & Bingyu Li & Yang Shi & Yimin Hu, 2023. "Ecological Environment Quality Assessment of Arid Areas Based on Improved Remote Sensing Ecological Index—A Case Study of the Loess Plateau," Sustainability, MDPI, vol. 15(18), pages 1-25, September.

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