Spatiotemporal and Multiscale Analysis of the Coupling Coordination Degree between Economic Development Equality and Eco-Environmental Quality in China from 2001 to 2020
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 r...
| Main Authors: | , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-02-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/14/3/737 |
| _version_ | 1827658963799244800 |
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| author | Jianwan Ji Zhanzhong Tang Weiwei Zhang Wenliang Liu Biao Jin Xu Xi Futao Wang Rui Zhang Bing Guo Zhiyu Xu Eshetu Shifaw Yibing Xiong Jinming Wang Saiping Xu Zhenqing Wang |
| author_facet | Jianwan Ji Zhanzhong Tang Weiwei Zhang Wenliang Liu Biao Jin Xu Xi Futao Wang Rui Zhang Bing Guo Zhiyu Xu Eshetu Shifaw Yibing Xiong Jinming Wang Saiping Xu Zhenqing Wang |
| author_sort | Jianwan Ji |
| collection | DOAJ |
| description | 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<sup>−1</sup>), 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<sup>−1</sup>), 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<sup>−1</sup>), with values of 0.4614, 0.5027, 0.4978, 0.5401 and 0.5525. (2) The highest global Moran’s <i>I</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 <i>R</i><sup>2 </sup>of the fitted curve at different scales ranged from 0.8183 to 0.9915. |
| first_indexed | 2024-03-09T23:11:59Z |
| format | Article |
| id | doaj.art-a78a23c57e9f4bbfa42450d1a6f003c5 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T23:11:59Z |
| publishDate | 2022-02-01 |
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| series | Remote Sensing |
| spelling | doaj.art-a78a23c57e9f4bbfa42450d1a6f003c52023-11-23T17:42:41ZengMDPI AGRemote Sensing2072-42922022-02-0114373710.3390/rs14030737Spatiotemporal and Multiscale Analysis of the Coupling Coordination Degree between Economic Development Equality and Eco-Environmental Quality in China from 2001 to 2020Jianwan Ji0Zhanzhong Tang1Weiwei Zhang2Wenliang Liu3Biao Jin4Xu Xi5Futao Wang6Rui Zhang7Bing Guo8Zhiyu Xu9Eshetu Shifaw10Yibing Xiong11Jinming Wang12Saiping Xu13Zhenqing Wang14School of Geography Science and Geomatics Engineering, Suzhou University of Science and Technology, Suzhou 215009, ChinaCollege of Resources and Environment, Xingtai University, Xingtai 054001, ChinaSchool of Geography Science and Geomatics Engineering, Suzhou University of Science and Technology, Suzhou 215009, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaCollege of Mathematics and Informatics, Fujian Normal University, Fuzhou 350108, ChinaSchool of Geography Science and Geomatics Engineering, Suzhou University of Science and Technology, Suzhou 215009, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaPiesat Information Technology Company Limited, Beijing 100195, ChinaSchool of Civil Architectural Engineering, Shandong University of Technology, Zibo 255000, ChinaCollege of Urban and Environmental Sciences, Peking University, Beijing 100871, ChinaDepartment of Geography and Environmental Studies, Wollo University, Dessie, EthiopiaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaSchool of Resource and Environment, Hunan University of Technology and Business, Changsha 410205, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaEvaluating 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<sup>−1</sup>), 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<sup>−1</sup>), 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<sup>−1</sup>), with values of 0.4614, 0.5027, 0.4978, 0.5401 and 0.5525. (2) The highest global Moran’s <i>I</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 <i>R</i><sup>2 </sup>of the fitted curve at different scales ranged from 0.8183 to 0.9915.https://www.mdpi.com/2072-4292/14/3/737modified coupling coordination degreespatiotemporal analysesmultiscale analysesremote sensingtrend analysesChina |
| spellingShingle | Jianwan Ji Zhanzhong Tang Weiwei Zhang Wenliang Liu Biao Jin Xu Xi Futao Wang Rui Zhang Bing Guo Zhiyu Xu Eshetu Shifaw Yibing Xiong Jinming Wang Saiping Xu Zhenqing Wang Spatiotemporal and Multiscale Analysis of the Coupling Coordination Degree between Economic Development Equality and Eco-Environmental Quality in China from 2001 to 2020 Remote Sensing modified coupling coordination degree spatiotemporal analyses multiscale analyses remote sensing trend analyses China |
| title | Spatiotemporal and Multiscale Analysis of the Coupling Coordination Degree between Economic Development Equality and Eco-Environmental Quality in China from 2001 to 2020 |
| title_full | Spatiotemporal and Multiscale Analysis of the Coupling Coordination Degree between Economic Development Equality and Eco-Environmental Quality in China from 2001 to 2020 |
| title_fullStr | Spatiotemporal and Multiscale Analysis of the Coupling Coordination Degree between Economic Development Equality and Eco-Environmental Quality in China from 2001 to 2020 |
| title_full_unstemmed | Spatiotemporal and Multiscale Analysis of the Coupling Coordination Degree between Economic Development Equality and Eco-Environmental Quality in China from 2001 to 2020 |
| title_short | Spatiotemporal and Multiscale Analysis of the Coupling Coordination Degree between Economic Development Equality and Eco-Environmental Quality in China from 2001 to 2020 |
| title_sort | spatiotemporal and multiscale analysis of the coupling coordination degree between economic development equality and eco environmental quality in china from 2001 to 2020 |
| topic | modified coupling coordination degree spatiotemporal analyses multiscale analyses remote sensing trend analyses China |
| url | https://www.mdpi.com/2072-4292/14/3/737 |
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