Open Access
Open access
Remote Sensing, volume 14, issue 3, pages 737

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

Jianwan Ji 1
Zhanzhong Tang 2, 3
Weiwei Zhang 1
Wenliang Liu 4
Biao Jin 5
Xi Xu 1
Futao Wang 4
Rui Zhang 6
Bing Guo 7
Zhiyu Xu 8
Eshetu Shifaw 9
Yibing Xiong 4
Jinming Wang 4
Saiping Xu 10
Zhenqing Wang 4
Show full list: 15 authors
Publication typeJournal Article
Publication date2022-02-04
Journal: Remote Sensing
scimago Q1
wos Q2
SJR1.091
CiteScore8.3
Impact factor4.2
ISSN20724292, 23154632, 23154675
General Earth and Planetary Sciences
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.

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