Water is an important indicator of ecological quality, but the traditional urban ecological quality evaluation methods often exclude the water body area and ignore the impact of water on ecological quality. This paper is based on Landsat8-OLI image data provided by the Google Earth Engine (GEE) platform in 2013, 2015, 2017, 2019, and 2021. The information entropy weighting method was used to integrate the surface potential water abundance index (SPWI), ratio vegetation index (RVI), normalized difference latent heat index (NDLI), normalized difference soil index (NDSI), and the land-surface temperature (LST) to construct the water-beneficial ecological index (WBEI). The spatiotemporal changes of ecological quality was analyzed based on WBEI in the urban area of Wuxi City, Jiangsu Province from 2013 to 2021. The Moran index was used to calculate the spatial autocorrelation of ecological quality in the urban area of Wuxi City. The results indicated that: (1) The WBEI integrated the impact of water bodies on ecological indices, and compensated for the shortcomings of traditional methods that cannot reflect the ecological quality of water bodies, which could better reflect the urban ecological quality including water bodies; (2) From 2013 to 2021, the average WBEI in the urban area of Wuxi City was 0.4808, 0.4416, 0.5068, 0.4471, and 0.4682, showing the fluctuating changes and a slight overall downward trend of the ecological quality; (3) The area of the urban area of Wuxi with excellent ecological quality decreased by 67.5251 km², and the area of good and general ecological quality increased by 76.8633 km². The area of the improved areas of ecological quality grade was larger than the area of the deteriorated areas. The improved areas were mainly distributed at the urban and rural junction of Xishan District in the east and Binhu District around the Taihu Lake in the south, while the deteriorated area is mainly distributed in Liangxi District and Xinwu District; (4) The overall Moran's I of the five years was 0.6820, 0.7002, 0.6367, 0.7007, and 0.6886, respectively. This indicated that there were significant spatial auto-correlation and clustering of ecological quality in the urban area of Wuxi City. The main spatial clustering types of ecological quality were high-high and low-low clustering. The ecological quality differences in different regions within the urban areas of Wuxi City were significant, with similar spatial clusters mainly manifested as mutual aggregation between high ecological quality regions and mutual aggregation between low ecological quality regions. This paper is based on WBEI to achieve rapid detection of ecological quality in Wuxi urban area. It can provide method reference and data support for ecological protection and environmental monitoring in similar cities.