Dynamic monitoring of eco-environmental quality in Xi′an based on GEE and adjusted RSEI

Abstract

As the capital city of Shaanxi Province, Xi′an has experienced rapid economic growth and urbanization under the economic globalization background in recent decades and still besets by increasingly prominent ecological problems. Xi′an is also one of the typical cities suffering from severe aerosol pollution in China. Rapidly and comprehensively quantitative monitoring of the spatio-temporal variations of eco-environmental quality in Xi′an is crucial for regional eco-environmental guidance and protection. This study was carried out on Google Earth Engine (GEE), a new cloud-computing platform with the merits of easy access to tremendous public resources and convenient processing of substantially geospatial data. Four-season Landsat images of 2000, 2004, 2010, 2015, 2020 and those previous-successive target years were selected firstly. Then, principal component analysis (PCA) was used to improve the previously developed remote sensing ecological index (RSEI) by adding aerosol optical depth (AOD) to it, and an adjusted RSEI (ARSEI) including greenness (NDVI), heat (LST), dryness (NDSI), humidity (Wet) and AOD was proposed to dynamically monitor the eco-environmental quality in Xi′an from 2000 to 2020. Moreover, Moran index was adopted to explore the spatial autocorrelation of the eco-environmental quality in Xi′an. Using summer, the season with the best principal component effect, as an example, the results showed that: (1) taking the effect of air pollution into account, the first principal component (PC1) contribution of ARSEI proposed in this paper was more than 83%. ARSEI could better concentrate the characteristics of each index and provide a more comprehensive evaluation for the eco-environmental quality of Xi′an. (2) The average ARSEIs of Xi′an from 2000 to 2020 were 0. 565, 0. 521,0. 572, 0. 644 and 0. 695, respectively, indicating that the urban eco-environmental quality degraded from 2000 to 2004 and promoted from 2004 to 2020. In the past 20 years, the areas with poor and very poor eco-environmental quality decreased by 1339.08 km2, which were mainly located in the north of Qinling Mountains. The areas with good and excellent eco-environmental quality increased by 2241. 80 km2 and were concentrated in Qinling areas, southern part of the city. (3) The improved areas were larger than the degraded areas in Xi′an over the past 20 years, and each district has undergone both the improvement and degradation processes. It was worth noting that the city experienced the worst degradation from 2000 to 2004, accounting for 29.41%, and the greatest improvement between 2010 and 2015, accounting for 31.62%. Generally speaking, the eco-environmental quality of Xi′an has been improved in the past 20 years. (4) All the five Global Moran′s I values were above 0.627 in 2000, 2004, 2010, 2015 and 2020, which indicated that the spatial distribution of the urban eco-environmental quality has a strongly positive correlation. The LISA cluster map showed that the aggregation distribution was dominated by high-high and low-low patterns. The low-low areas were mainly located in the northern Qinling Mountains, while the high-high areas were concentrated in the southern part of the city. Based on GEE cloud platform, this study accomplished fast eco-environmental quality monitoring in Xi′ an and will provide method reference and data support for regional eco-environmental monitoring, management and restoration.