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ORIGINAL RESEARCH article

Front. Sustain. Food Syst.
Sec. Land, Livelihoods and Food Security
Volume 8 - 2024 | doi: 10.3389/fsufs.2024.1462031
This article is part of the Research Topic Global Land Use Intensity Change and Its Impact on Food Security View all 5 articles

Spatial-temporal evolution and influencing factors of the eco-efficiency of cultivated land-use in the Beijing-Tianjin-Hebei region in the context of food security

Provisionally accepted
Xinying Jiao Xinying Jiao 1,2,3Jingtao Ma Jingtao Ma 4Guoxiang Liu Guoxiang Liu 1Yancang Li Yancang Li 1Chenggang Li Chenggang Li 5*Xin Wang Xin Wang 6
  • 1 School of Land Science and Space Planning, Hebei GEO University, Shijiazhuang, Hebei Province, China
  • 2 International Science and Technology Cooperation Base of Hebei Province: Hebei International Joint Research Center for Remote Sensing of Agricultural Drought Monitoring, Hebei GEO University,, Shijiazhuang, China
  • 3 Regional Institutions Research Center , Hebei GEO University, Shijiazhuang, China
  • 4 Natural Resources Big Data Application Center, Hebei Geographic Information Group Co., Ltd,, Shijiazhuang, China
  • 5 School of Big Data Application and Economics, Guizhou University of Finance and Economics,, Guiyang, China
  • 6 School of Foreign Languages, Guizhou University of Finance and Economics, Guiyang, China

The final, formatted version of the article will be published soon.

    Improving the eco-efficiency of cultivated land use (ECLU) is important for ensuring food security, promoting social and economic development, and reducing carbon emissions. However, dynamic inter-period comparisons of the ECLU and clarifications of its influencing factors are limited. We calculated the ECLU at the county level in the Beijing-Tianjin-Hebei region, China, based on the super-efficiency slacks-based measure and global Malmquist-Luenberger index and analyzed its influencing factors utilizing a geographically and temporally weighted regression model. From 2000 to 2020, the number of higher counties decreased and that of medium counties increased.Geographically, the ECLU values in the north are higher than those in other districts and counties; counties in Beijing and Tianjin maintained moderate ECLU values, whereas Zhangjiakou and Chengde maintained high ECLU values. The ECLU value in the study area showed a trend of rapid decline-slow rise-continuous rise, with the upward trend of the ECLU value in Beijing-Tianjin-Hebei region being significantly less pronounced than those in most counties of Hebei Province.Resource allocation and scale expansion where initially dominant; however, technological progress and investment eventually prevailed. The ECLU is mainly affected by the multiple cropping index, industrial structure, irrigation index, mechanized farming level, and per capita cultivated land. This study assesses the ECLU in the Beijing-Tianjin-Hebei region, providing a scientific basis for the formulation and implementation of relevant policies for its improvement. Furthermore, this study enriches the theory and methods of research on the ECLU and has practical value and theoretical significance. Overall, the results have important social value as they contribute to ensuring national food security, reducing carbon emissions, promoting regional coordinated and sustainable development.

    Keywords: eco-efficiency of cultivated land use (ECLU), spatial-temporal evolution, Influencing factors, super-efficiency slacks-based measure (Super-SBM), Global Malmquist-Luenberger (GML) index, Geographically and temporally weighted regression (GTWR), Beijing-Tianjin-Hebei region

    Received: 09 Jul 2024; Accepted: 15 Nov 2024.

    Copyright: © 2024 Jiao, Ma, Liu, Li, Li and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Chenggang Li, School of Big Data Application and Economics, Guizhou University of Finance and Economics,, Guiyang, China

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