IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2021i1p111-d709304.html
   My bibliography  Save this article

Spatial-Temporal Pattern and Evolution Trend of the Cultivated Land Use Eco-Efficiency in the National Pilot Zone for Ecological Conservation in China

Author

Listed:
  • Zhenggen Fan

    (College of City Construction, Jiangxi Normal University, Nanchang 330022, China)

  • Chao Deng

    (College of City Construction, Jiangxi Normal University, Nanchang 330022, China)

  • Yuqi Fan

    (College of City Construction, Jiangxi Normal University, Nanchang 330022, China)

  • Puwei Zhang

    (College of City Construction, Jiangxi Normal University, Nanchang 330022, China)

  • Hua Lu

    (Institute of Ecological Civilization, Jiangxi University of Finance and Economics, Nanchang 330013, China)

Abstract

The cultivated land use eco-efficiency (CLUE) is an important indicator to evaluate ecological civilization construction in China. Research on the spatial-temporal pattern and evolution trend of the CLUE can help to assess the level of ecological civilization construction and reveal associated demonstration and driving effects on surrounding areas. Based on the perspective of the CLUE, this paper obtains cultivated land use data pertaining to National Pilot Zones for Ecological Conservation in China and neighboring provinces from 2008 to 2018. In this study, the SBM-undesirable, Moran’s I, and Markov chain models are adopted to quantitatively measure and analyze the CLUE and its temporal and spatial patterns and evolution trend. The research results indicate that the CLUE in the whole study area exhibited the characteristics of one growth, two stable, and two decline stages, with a positive spatial autocorrelation that increased year by year, and a spatial spillover effect was observed. Geographical spatial patterns and spatial spillover effects played a major role in the evolution of the CLUE, and there occurred a higher probability of improvement in the vicinity of cities with high CLUE values. In the future, practical construction experience should be disseminated at the provincial level, and policies and measures should be formulated according to local conditions. In addition, a linkage model between prefecture-level cities should be developed at the municipal level to fully manifest the positive spatial spillover effect. Moreover, we should thoroughly evaluate the risk associated with CLUE transition from high to low levels and establish a low-level early warning mechanism.

Suggested Citation

  • Zhenggen Fan & Chao Deng & Yuqi Fan & Puwei Zhang & Hua Lu, 2021. "Spatial-Temporal Pattern and Evolution Trend of the Cultivated Land Use Eco-Efficiency in the National Pilot Zone for Ecological Conservation in China," IJERPH, MDPI, vol. 19(1), pages 1-16, December.
  • Handle: RePEc:gam:jijerp:v:19:y:2021:i:1:p:111-:d:709304
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/1/111/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/19/1/111/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhao, Zhe & Bai, Yuping & Wang, Guofeng & Chen, Jiancheng & Yu, Jiangli & Liu, Wei, 2018. "Land eco-efficiency for new-type urbanization in the Beijing-Tianjin-Hebei Region," Technological Forecasting and Social Change, Elsevier, vol. 137(C), pages 19-26.
    2. Tone, Kaoru & Tsutsui, Miki, 2009. "Network DEA: A slacks-based measure approach," European Journal of Operational Research, Elsevier, vol. 197(1), pages 243-252, August.
    3. Zhou, P. & Ang, B.W. & Poh, K.L., 2006. "Slacks-based efficiency measures for modeling environmental performance," Ecological Economics, Elsevier, vol. 60(1), pages 111-118, November.
    4. Haoran Yang & Qun Wu, 2019. "Land Use Eco-Efficiency and Its Convergence Characteristics Under the Constraint of Carbon Emissions in China," IJERPH, MDPI, vol. 16(17), pages 1-17, August.
    5. Chaozheng Zhang & Yangyue Su & Gangqiao Yang & Danling Chen & Rongxuan Yang, 2020. "Spatial-Temporal Characteristics of Cultivated Land Use Efficiency in Major Function-Oriented Zones: A Case Study of Zhejiang Province, China," Land, MDPI, vol. 9(4), pages 1-20, April.
    6. Zhang, Ren-Long & Liu, Xiao-Hong, 2021. "Evaluating ecological efficiency of Chinese industrial enterprise," Renewable Energy, Elsevier, vol. 178(C), pages 679-691.
    7. Zhang, Xueru & Song, Wei & Lang, Yanqing & Feng, Xiaomiao & Yuan, Quanzhi & Wang, Jingtao, 2020. "Land use changes in the coastal zone of China’s Hebei Province and the corresponding impacts on habitat quality," Land Use Policy, Elsevier, vol. 99(C).
    8. Li, Lan-Bing & Hu, Jin-Li, 2012. "Ecological total-factor energy efficiency of regions in China," Energy Policy, Elsevier, vol. 46(C), pages 216-224.
    9. Kuang, Bing & Lu, Xinhai & Zhou, Min & Chen, Danling, 2020. "Provincial cultivated land use efficiency in China: Empirical analysis based on the SBM-DEA model with carbon emissions considered," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    10. Chen, Lili & Zhao, Hongsheng & Song, Ge & Liu, Ye, 2021. "Optimization of cultivated land pattern for achieving cultivated land system security: A case study in Heilongjiang Province, China," Land Use Policy, Elsevier, vol. 108(C).
    11. Paradi, Joseph C. & Rouatt, Stephen & Zhu, Haiyan, 2011. "Two-stage evaluation of bank branch efficiency using data envelopment analysis," Omega, Elsevier, vol. 39(1), pages 99-109, January.
    12. Bonfiglio, Andrea & Arzeni, Andrea & Bodini, Antonella, 2017. "Assessing eco-efficiency of arable farms in rural areas," Agricultural Systems, Elsevier, vol. 151(C), pages 114-125.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yuling Wu & Pei Zhang & Jia Li & Jiao Hou, 2022. "Spatial Distribution Evolution and Optimization Path of Eco-Efficiency of Cultivated Land Use: A Case Study of Hubei Province, China," Sustainability, MDPI, vol. 14(18), pages 1-18, September.
    2. Yang Zhou & Hankun Wang & Zuqiang Wang & Xiang Dai, 2022. "The Improvement Path for Regionally Coordinated Green Development: Evidence from Social Network Analysis," IJERPH, MDPI, vol. 19(18), pages 1-14, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Qingxian An & Haoxun Chen & Jie Wu & Liang Liang, 2015. "Measuring slacks-based efficiency for commercial banks in China by using a two-stage DEA model with undesirable output," Annals of Operations Research, Springer, vol. 235(1), pages 13-35, December.
    2. Iftikhar, Yaser & Wang, Zhaohua & Zhang, Bin & Wang, Bo, 2018. "Energy and CO2 emissions efficiency of major economies: A network DEA approach," Energy, Elsevier, vol. 147(C), pages 197-207.
    3. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min, 2016. "Research fronts in data envelopment analysis," Omega, Elsevier, vol. 58(C), pages 33-45.
    4. Houtian Tang & Yuanlai Wu & Jinxiu Chen & Liuxin Deng & Minjie Zeng, 2022. "How Does Change in Rural Residential Land Affect Cultivated Land Use Efficiency? An Empirical Study Based on 42 Cities in the Middle Reaches of the Yangtze River," Land, MDPI, vol. 11(12), pages 1-20, December.
    5. Zhen Shi & Fengping Wu & Huinan Huang & Xinrui Sun & Lina Zhang, 2019. "Comparing Economics, Environmental Pollution and Health Efficiency in China," IJERPH, MDPI, vol. 16(23), pages 1-30, December.
    6. N. Avkiran, 2010. "Sensitivity analysis of network DEA illustrated in branch banking," CEPA Working Papers Series WP122010, School of Economics, University of Queensland, Australia.
    7. Yu, Ming-Miin, 2010. "Assessment of airport performance using the SBM-NDEA model," Omega, Elsevier, vol. 38(6), pages 440-452, December.
    8. Shuting Liu & Junsong Jia & Hanzhi Huang & Dilan Chen & Yexi Zhong & Yangming Zhou, 2023. "China’s CO 2 Emissions: A Thorough Analysis of Spatiotemporal Characteristics and Sustainable Policy from the Agricultural Land-Use Perspective during 1995–2020," Land, MDPI, vol. 12(6), pages 1-20, June.
    9. Alperovych, Yan & Amess, Kevin & Wright, Mike, 2013. "Private equity firm experience and buyout vendor source: What is their impact on efficiency?," European Journal of Operational Research, Elsevier, vol. 228(3), pages 601-611.
    10. Ming-Fu Hsu & Ying-Shao Hsin & Fu-Jiing Shiue, 2022. "Business analytics for corporate risk management and performance improvement," Annals of Operations Research, Springer, vol. 315(2), pages 629-669, August.
    11. Xinna Zhao & Li Guo & Zhiyuan Gao & Yu Hao, 2024. "Estimation and Analysis of Carbon Emission Efficiency in Chinese Industry and Its Influencing Factors—Evidence from the Micro Level," Energies, MDPI, vol. 17(4), pages 1-15, February.
    12. Zhang, Han & Zheng, Jinhui & Hunjra, Ahmed Imran & Zhao, Shikuan & Bouri, Elie, 2024. "How does urban land use efficiency improve resource and environment carrying capacity?," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).
    13. Guangyan Ran & Guangyao Wang & Huijuan Du & Mi Lv, 2023. "Relationship of Cooperative Management and Green and Low-Carbon Transition of Agriculture and Its Impacts: A Case Study of the Western Tarim River Basin," Sustainability, MDPI, vol. 15(11), pages 1-18, May.
    14. Lozano, Sebastián, 2016. "Slacks-based inefficiency approach for general networks with bad outputs: An application to the banking sector," Omega, Elsevier, vol. 60(C), pages 73-84.
    15. Haifeng Huang & Tao Wang, 2017. "The Total-Factor Energy Efficiency of Regions in China: Based on Three-Stage SBM Model," Sustainability, MDPI, vol. 9(9), pages 1-20, September.
    16. Mahmoudabadi, Mohammad Zarei & Azar, Adel & Emrouznejad, Ali, 2018. "A novel multilevel network slacks-based measure with an application in electric utility companies," Energy, Elsevier, vol. 158(C), pages 1120-1129.
    17. Nan Ke & Xupeng Zhang & Xinhai Lu & Bing Kuang & Bin Jiang, 2022. "Regional Disparities and Influencing Factors of Eco-Efficiency of Arable Land Utilization in China," Land, MDPI, vol. 11(2), pages 1-17, February.
    18. Li, Jianglong & Lin, Boqiang, 2017. "Ecological total-factor energy efficiency of China's heavy and light industries: Which performs better?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 83-94.
    19. Xiao Lu & Yi Qu & Piling Sun & Wei Yu & Wenlong Peng, 2020. "Green Transition of Cultivated Land Use in the Yellow River Basin: A Perspective of Green Utilization Efficiency Evaluation," Land, MDPI, vol. 9(12), pages 1-22, November.
    20. Honma, Satoshi & Ushifusa, Yoshiaki & Taghizadeh-Hesary, Farhad & Okamura, Soyoka & Vandercammee, Lilu, 2024. "Environmental efficiency of Japanese regions before and after the Great East Japan Earthquake," MPRA Paper 120945, University Library of Munich, Germany.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:19:y:2021:i:1:p:111-:d:709304. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.