Assessment and simulation of eco-environmental quality changes in rapid rural urbanization: Xiong’an New Area, China
Xiong'an New Area was established as a state-level new area in 2017 and serves as a typical representative area for studying the ecological evolution of rural areas under rapid urbanization in China. Remote sensing-based ecological index (RSEI) is a regional eco-environmental quality (EEQ) assessment index. Many studies have employed RSEI to achieve rapid, objective, and effective quantitative assessment of the spatio-temporal changes of regional EEQ. However, research that combines RSEI with machine learning algorithms to conduct multi-scenario simulation of EEQ is still relatively scarce. Therefore, this study assessed and simulated EEQ changes in Xiong'an and revealed that: (1) The large-scale construction has led to an overall decline in EEQ, with the RSEI decreasing from 0.648 in 2014 to 0.599 in 2021. (2) Through the multi-scenario simulation, the non-unidirectional evolution of RSEI during the process of urban-rural construction has been revealed, specifically characterized by a significant decline followed by a slight recovery. (3) The marginal effects of urban-rural construction features for simulated RSEI demonstrate an inverted "U-shaped" curve in the relationship between urbanization and EEQ. This indicates that urbanization and EEQ may not be absolute zero-sum. These findings can provide scientific insights for maintaining and improving the regional EEQ in urban-rural construction.
Authors
- Xiong Yao (ORCID: https://orcid.org/0000-0002-3455-5798)
- Hanqiu Xu (ORCID: https://orcid.org/0000-0002-7158-466X)
- Zhongli Lin (ORCID: https://orcid.org/0009-0006-2285-7488)
- Zhipeng Zhu
Institutions
- Fuzhou University (CN)
- Fujian University of Technology (CN)
Publication Details
- Journal
- Scientific Reports
- Published
- 2024-10-04
- DOI
- https://doi.org/10.1038/s41598-024-73487-5
- Citations
- 9
- Primary Topic
- Land Use and Ecosystem Services
- Type
- article
- Field-Weighted Citation Impact
- 2.54
Funders
- National Natural Science Foundation of China