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

Na Chen, Gang Cheng (), Jie Yang, Huan Ding and Shi He
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Na Chen: College Surveying & Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, China
Gang Cheng: College Surveying & Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, China
Jie Yang: College Surveying & Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, China
Huan Ding: College Surveying & Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, China
Shi He: College Surveying & Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, China

Sustainability, 2023, vol. 15, issue 11, 1-18

Abstract: 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.

Keywords: ecological environment quality; RSEI; human factors; Jining City; GWR (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

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