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volume 158 pages 111284

An evaluation framework for urban ecological compensation priority in China based on meta-analysis and fuzzy comprehensive evaluation

Publication typeJournal Article
Publication date2024-01-01
scimago Q1
wos Q1
SJR1.959
CiteScore13.3
Impact factor7.4
ISSN1470160X, 18727034
Ecology, Evolution, Behavior and Systematics
Ecology
General Decision Sciences
Abstract
This initiative seeks to attain a harmonious equilibrium of regional environmental pressures and improve resource utilization efficiency within the context of habitat and environmental preservation. The escalating urban population exposure underscores the significance of restoring human settlements, emerging as a critical concern in urban planning and development. However, a notable deficiency exists in both theoretical foundations and methodologies for identifying cities requiring greater support for environmental restoration. The evaluation of ecological compensation priority has thus become pivotal in accomplishing this objective. Consequently, this study endeavors to elucidate the research paradigm surrounding urban ecological compensation priority and proffer a framework for assessing and analyzing the spatial characteristics of such priority in China. Employing the meta-analysis method, the study established an evaluation index system for ecological protection importance (EPI) to delineate ecological compensation priority. Leveraging data sourced from literature findings and publicly available data from Google Earth Engine, an evaluation of EPI subsystems (HSEQ and ecological sensitivity) ensued via the application of a fuzzy comprehensive evaluation model. Ultimately, the EPI value was computed using a coupling coordination degree model, facilitating the determination of ecological compensation priorities for Chinese cities. The results showed that (1) Most cities displayed both low-grade human settlement environmental quality (HSEQ) and ecological sensitivity, especially about 59.8% cities in lowest grade HSEQ. And they showed aggregated distribution from both the aspects of the HSEQ(Moran’I = 0.16) and the eco-sensitivity(Moran’I = 0.297). (2) 53.5%(n = 53) cities in low compensation priority and 38.4%(n = 36) in medium compensation priority, only 8.1%(n = 8) cities in high compensation priority. (3) 83.75% cities accorded with the feature that cities with obvious population growth could upgrade the compensation priority. It indicates that cities and urban agglomerations with potential for population growth should receive more attention. This study presents an analytical framework for urban ecological compensation, aiming to offer valuable insights for urban HSEQ policy decisions related to urban ecological management.
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GOST Copy
Zhong J. et al. An evaluation framework for urban ecological compensation priority in China based on meta-analysis and fuzzy comprehensive evaluation // Ecological Indicators. 2024. Vol. 158. p. 111284.
GOST all authors (up to 50) Copy
Zhong J., Li Z., Zhang D., Yang J., Zhu J. An evaluation framework for urban ecological compensation priority in China based on meta-analysis and fuzzy comprehensive evaluation // Ecological Indicators. 2024. Vol. 158. p. 111284.
RIS |
Cite this
RIS Copy
TY - JOUR
DO - 10.1016/j.ecolind.2023.111284
UR - https://doi.org/10.1016/j.ecolind.2023.111284
TI - An evaluation framework for urban ecological compensation priority in China based on meta-analysis and fuzzy comprehensive evaluation
T2 - Ecological Indicators
AU - Zhong, Jialong
AU - Li, Zhigang
AU - Zhang, Dong
AU - Yang, Jie
AU - Zhu, Jiaxing
PY - 2024
DA - 2024/01/01
PB - Elsevier
SP - 111284
VL - 158
SN - 1470-160X
SN - 1872-7034
ER -
BibTex
Cite this
BibTex (up to 50 authors) Copy
@article{2024_Zhong,
author = {Jialong Zhong and Zhigang Li and Dong Zhang and Jie Yang and Jiaxing Zhu},
title = {An evaluation framework for urban ecological compensation priority in China based on meta-analysis and fuzzy comprehensive evaluation},
journal = {Ecological Indicators},
year = {2024},
volume = {158},
publisher = {Elsevier},
month = {jan},
url = {https://doi.org/10.1016/j.ecolind.2023.111284},
pages = {111284},
doi = {10.1016/j.ecolind.2023.111284}
}
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