Evolving Trends and Influencing Factors of the Rural Green Development Level in Chongqing

Author:

Zhu Kangwen12ORCID,Song Dan2ORCID,Zhang Lanxin3,He Yong1,Zhang Sheng2ORCID,Liu Yaqun4ORCID,Tian Xiaosong5

Affiliation:

1. School of Smart City, Chongqing Jiaotong University, Chongqing 400074, China

2. Chongqing Academy of Eco-Environmental Sciences (Southwest Branch of Chinese Academy of Environmental Sciences), Chongqing 401147, China

3. College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China

4. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China

5. School of Resources and Safety Engineering, Chongqing Vocational Institute of Engineering, Chongqing 402260, China

Abstract

Rural green development is a concrete practice of rural revitalization. Currently, research on quantitative evaluation methods for rural green development levels are not well developed. In this study, an evaluation model of the rural green development level in Chongqing City, China was developed based on the parameters of ecology, living, and production. An entropy weight method, Theil index, optimal scale regression model, and GIS were used to analyze the spatio-temporal characteristics, trends, and influencing factors of the rural green development level from 2018 to 2020 in Chongqing City. The results showed that: (1) the overall “ecology, living, and production” dimensions and the comprehensive index of the development level in the city were generally increasing, and the proportion of counties at a high-level increased from 23.68% in 2018 to 81.58% in 2020; (2) the Theil index of the city in was 0.0185, 0.0121, and 0.0114 in 2018, 2019, and 2020 respectively, indicating that the differences in development level among regions decreased as the development level increased; (3) the level of rural green development showed a clear upwards trend, and the proportion of counties with low-speed growth, medium-speed growth, and high-speed growth from 2018 to 2020 was 5.26%, 81.58%, and 13.16%, respectively; and (4) the optimal scale regression analysis showed that the factors with greater impacts on the rural green development level are social security and employment expenditure level of government finance, health expenditure level of government finance, with their contributions is 40.3% and 26%, respectively. The results from this study demonstrate the significance of exploring research methods for rural green development and ways to improve the level of rural green development.

Funder

Chongqing Municipal Bureau of Science and Technolog

Chongqing Municipal Education Commission

Chongqing Academe of Eco-environmental Science

Innovation Center for Green Intelligent Environmental Protection Technology and Equipment Technology in Chongqing

Publisher

MDPI AG

Subject

Nature and Landscape Conservation,Ecology,Global and Planetary Change

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