Spatiotemporal and Multiscale Analysis of the Coupling Coordination Degree between Economic Development Equality and Eco-Environmental Quality in China from 2001 to 2020

Author:

Ji Jianwan1ORCID,Tang Zhanzhong23,Zhang Weiwei1,Liu Wenliang4,Jin Biao5ORCID,Xi Xu1,Wang Futao4,Zhang Rui6,Guo Bing7,Xu Zhiyu8,Shifaw Eshetu9ORCID,Xiong Yibing4ORCID,Wang Jinming4,Xu Saiping10,Wang Zhenqing4

Affiliation:

1. School of Geography Science and Geomatics Engineering, Suzhou University of Science and Technology, Suzhou 215009, China

2. College of Resources and Environment, Xingtai University, Xingtai 054001, China

3. Xingtai Key Laboratory of Geo-information and Remote Sensing Technology Application, Xingtai 054001, China

4. Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

5. College of Mathematics and Informatics, Fujian Normal University, Fuzhou 350108, China

6. Piesat Information Technology Company Limited, Beijing 100195, China

7. School of Civil Architectural Engineering, Shandong University of Technology, Zibo 255000, China

8. College of Urban and Environmental Sciences, Peking University, Beijing 100871, China

9. Department of Geography and Environmental Studies, Wollo University, Dessie, Ethiopia

10. School of Resource and Environment, Hunan University of Technology and Business, Changsha 410205, China

Abstract

Evaluating and exploring regional eco-environmental quality (EEQ), economic development equality (EDE) and the coupling coordination degree (CCD) at multiple scales is important for realizing regional sustainable development goals. The CCD can reflect both the development level and the interaction relationship of two or more systems. However, relevant previous studies have ignored non-statistical data, lacked multiscale analyses, misused the coupling coordination degree model or have not sufficiently considered economic development equality. In response to these problems, this study integrated multisource remote sensing datasets to calculate and analyse the remote sensing ecological index (RSEI) and then used nighttime light data and population density data to calculate the proposed nighttime difference index (NTDI). Next, a modified coupling coordination degree (MCCD) index was proposed to analyse the MCCD between EEQ and EDE. Then, spatiotemporal and multiscale analyses at the county, city, province, urban agglomeration and country levels were performed. Global and local spatial autocorrelation and trend analyses were performed to evaluate the spatial aggregation degree and change trends from 2001 to 2020. The main conclusions are as follows: (1) The EEQ of China displayed a fluctuating upwards trend (0.0048 a−1), with average RSEI values of 0.5950, 0.6277, 0.6164, 0.6311 and 0.6173; the EDE of China showed an upwards trend (0.0298 a−1), with average NTDI values of 0.1271, 0.1635, 0.1642, 0.2181 and 0.2490; and China’s MCCD indicated an upwards trend (0.0220 a−1), with values of 0.4614, 0.5027, 0.4978, 0.5401 and 0.5525. (2) The highest global Moran’s I of NTDI and MCCD was achieved at the city scale, while the highest RSEI was achieved at the county scale. From 2001 to 2020, the spatial agglomeration effect of the RSEI decreased, while that of the NTDI and MCCD increased. (3) A power function relationship occurred between NTDI and MCCD at different scales. Furthermore, the NTDI had a higher contribution to improving the MCCD than the RSEI and the R2 of the fitted curve at different scales ranged from 0.8183 to 0.9915.

Funder

Starting Research Program of Suzhou University of Science and Technology

National Key Research and Development Program of China

Publisher

MDPI AG

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