Detection of spatiotemporal changes in eco-environmental quality based on RSEI and SG filtering and its driving force analysis: a case study in Sichuan Province, China.

Autor: Ma D; School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan, China., Huang Q; School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan, China. 2022160108@stu.sdjzu.edu.cn., Wang Q; School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan, China., Xu H; Institute of International Rivers And Eco-Security, Yunnan University, Kunming, China., Yan Y; Department of Geography, National University of Singapore, Singapore, Singapore.
Jazyk: angličtina
Zdroj: Environmental monitoring and assessment [Environ Monit Assess] 2024 Nov 29; Vol. 196 (12), pp. 1274. Date of Electronic Publication: 2024 Nov 29.
DOI: 10.1007/s10661-024-13378-4
Abstrakt: Landsat images were extracted using Google Earth Engine (GEE) platform and optimized by Savitzky-Golay (SG) filtering. The Remote Sensing Ecological Index (RSEI) method was used to analyze the eco-environmental quality in Sichuan Province in recent 20 years. In addition, Theil-Sen median method and Mann-Kendall (MK) test were used to test the change trend of eco-environmental quality. Furthermore, drivers were evaluated by partial correlation analysis, 2D scatter plots, and t tests. The results showed that (1) in the past 20 years, the eco-environmental quality of Sichuan Province was on the rise, and the eco-environmental quality in the western region was better than that in the eastern region. The eco-environmental quality was positively correlated with forest and grassland types, and negatively correlated with cultivated land and urban and rural construction land types. (2) The eco-environmental quality of Sichuan Province is linearly correlated with the digital elevation model, but poorly correlated with slope and slope direction. In the range of slope 0° ~ 9° and southeast direction, the eco-environmental quality is the worst. (3) The eco-environmental quality of Sichuan Province was most significantly affected by soil moisture and sunshine hours. The study can help us to understand and assess the health of ecosystems in Sichuan Province, provide a scientific basis for protecting and improving the environment, and guide the formulation and implementation of environmental protection policies.
Competing Interests: Declarations. Competing interest: The authors declare no competing interests.
(© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)
Databáze: MEDLINE
Externí odkaz: