Evaluation of Urban Ecological Environment Quality Based on Improved RSEI and Driving Factors Analysis

被引:23
作者
Chen, Na [1 ]
Cheng, Gang [1 ]
Yang, Jie [1 ]
Ding, Huan [1 ]
He, Shi [1 ]
机构
[1] Henan Polytech Univ, Coll Surveying & Land Informat Engn, Jiaozuo 454000, Peoples R China
关键词
ecological environment quality; RSEI; human factors; Jining City; GWR;
D O I
10.3390/su15118464
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Monitoring the quality of the urban ecological environment has become one of the important elements of promoting a sustainable urban development. The remote sensing ecological index (RSEI) provides a new research direction in urban ecological environment monitoring, combined with remote sensing. However, by using the principal component analysis method in RSEI, the calculation results are complicated and the workload is huge. To effectively assess the urban ecological environment, an improved remote sensing ecological index (IRSEI) was created to improve the ease of data use by using the entropy weighting method with spatiotemporal characteristics and seasonal variations. Furthermore, a geographically weighted regression model was used to quantify the impact of human activities on the urban ecological environment quality. The results showed that the IRSEI could provide a new method for monitoring the urban ecological environment quality, which makes the work easier while ensuring the validity of the results. It was concluded that (1) seasonal differences in the ecological quality of the study area were evident in the IRSEI model and the overall ecological environment quality of Jining City had been on an upward trend in the past 20 years; (2) the ecological quality in the study area was unevenly distributed spatially, with the southwestern part being better than the northeastern part, and the ecological grade being predominantly between moderate and good; and (3) the spatial aggregation effect of the IRSEI was increasing with time. The geographically weighted regression (GWR) revealed the influence of human activities on the ecological environment quality, among which economic level was positively related to ecological improvement, but the population density and night light index were negatively related to improvements in the ecological environment; road network density only showed a negative correlation in 2020. As Jining urbanizes, attention should be paid to protecting the built environment and population distribution.
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页数:18
相关论文
共 36 条
[11]   Analyzing ecological environment change and associated driving factors in China based on NDVI time series data [J].
Jiang, Luguang ;
Liu, Ye ;
Wu, Si ;
Yang, Cheng .
ECOLOGICAL INDICATORS, 2021, 129
[12]  
Krueger H, 2008, PROG EXP TUMOR RES, V40, P1, DOI 10.1159/000151866
[13]   Dynamic analysis of ecological environment combined with land cover and NDVI changes and implications for sustainable urban-rural development: The case of Mu Us Sandy Land, China [J].
Li, Yurui ;
Cao, Zhi ;
Long, Hualou ;
Liu, Yansui ;
Li, Wangjun .
JOURNAL OF CLEANER PRODUCTION, 2017, 142 :697-715
[14]   Comparison between modified remote sensing ecological index and RSEI [J].
Liu Y. ;
Dang C. ;
Yue H. ;
Lyu C. ;
Qian J. ;
Zhu R. .
National Remote Sensing Bulletin, 2022, 26 (04) :683-697
[15]  
Nanjia Lu, 2020, E3S Web of Conferences, V198, DOI [10.1051/e3sconf/202019804024, 10.1051/e3sconf/202019804024]
[16]   基于RSEI模型的昆明市生态环境质量动态监测 [J].
农兰萍 ;
王金亮 .
生态学杂志, 2020, 39 (06) :2042-2050
[17]  
O'Sullivan D, 2003, GEOGR ANAL, V35, P272, DOI 10.1353/geo.2003.0008
[18]  
[排日海·合力力 Pariha Helili], 2021, [干旱区研究, Arid Zone Research], V38, P1484
[19]  
Shan W., 2019, J AGRIC ENG-ITALY, V35, P234
[20]   Ecological environment quality assessment based on remote sensing data for land consolidation [J].
Shan, Wei ;
Jin, Xiaobin ;
Ren, Jie ;
Wang, Yongcai ;
Xu, Zhigang ;
Fan, Yeting ;
Gu, Zhengming ;
Hong, Changqiao ;
Lin, Jinhuang ;
Zhou, Yinkang .
JOURNAL OF CLEANER PRODUCTION, 2019, 239