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Selected Environmental Assessment Model and Spatial Analysis Method to Explain Correlations in Environmental and Socio-Economic Data with Possible Application for Explaining the State of the Ecosystem

Author

Listed:
  • Junnan Xiong

    (School of Civil Engineering and Architecture, Southwest Petroleum University, Chengdu 610500, China
    State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China)

  • Wei Li

    (School of Civil Engineering and Architecture, Southwest Petroleum University, Chengdu 610500, China)

  • Hao Zhang

    (School of Civil Engineering and Architecture, Southwest Petroleum University, Chengdu 610500, China
    Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Weiming Cheng

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    University of Chinese Academy of Sciences, Beijing 100049, China
    Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China)

  • Chongchong Ye

    (School of Civil Engineering and Architecture, Southwest Petroleum University, Chengdu 610500, China)

  • Yunliang Zhao

    (School of Civil Engineering and Architecture, Southwest Petroleum University, Chengdu 610500, China)

Abstract

Regional ecosystem health is the basis for regular regional exploration, ecological protection, and sustainable development. This study explored ecosystem health at the southern end of the Hu Line (Sichuan and Yunnan provinces) using the pressure–state–response model and examined the spatial evolution of ecosystem health. The proportion of unhealthy and morbid cities decreased from 45.9% in 2000 to 35.1% in 2016. The imbalance of ecosystem health among cities has gradually increased since 2006, but more high-quality cities have emerged (Z of Moran’s Index < 1.96, p > 0.05). Overall, the regional ecosystem on the southeast side of the Hu Line was healthier than that on the northwest side. Differences in ecosystem health on both sides of the Hu Line showed decreasing trends over time except for the pressure score. The spatial pattern of ecosystem health moved along the Hu Line because the pressure and state scores of ecosystems were mainly determined by the natural environmental conditions. Based on the county-level assessment, the grade of imbalance within cities was divided, and those that were lagging were identified. To correct regional imbalances, a comprehensive and proactive policy framework for a smart development model was put forward in Sichuan and Yunnan.

Suggested Citation

  • Junnan Xiong & Wei Li & Hao Zhang & Weiming Cheng & Chongchong Ye & Yunliang Zhao, 2019. "Selected Environmental Assessment Model and Spatial Analysis Method to Explain Correlations in Environmental and Socio-Economic Data with Possible Application for Explaining the State of the Ecosystem," Sustainability, MDPI, vol. 11(17), pages 1-26, September.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:17:p:4781-:d:263183
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    References listed on IDEAS

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    2. Kaili Zhang & Rongrong Feng & Zhicheng Zhang & Chun Deng & Hongjuan Zhang & Kang Liu, 2022. "Exploring the Driving Factors of Remote Sensing Ecological Index Changes from the Perspective of Geospatial Differentiation: A Case Study of the Weihe River Basin, China," IJERPH, MDPI, vol. 19(17), pages 1-25, September.
    3. Hui Zou & Xiaohua Ma, 2021. "Identifying resource and environmental carrying capacity in the Yangtze River Economic Belt, China: the perspectives of spatial differences and sustainable development," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(10), pages 14775-14798, October.

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