It is inevitable that urban agglomeration will have a coercive impact on the regional Ecological Environment Quality (EEQ) as a consequence of high-speed urbanization. Balancing the EEQ and urbanization development has become a problem worthy of attention. In order to objectively evaluate the EEQ of the Yangtze River Delta Urban Agglomeration (YRDUA) and explore the impact of the urbanization process on it, this paper is based on the Modified Remote Sensing Ecological Index (MRSEI) and the Comprehensive Night Light Index (CNLI), respectively, and conducts a quantitative assessment of the YRDUA in China from 2000 to 2020. The results show that: (1) From 2000 to 2020, the MRSEI of the YRDUA first decreased and then increased, and the ecological environment quality degraded first and then improved; however, there were significant differences between regions. The ecological environment quality in the south is obviously better than that in the north, and the ecological environment quality in the north changes more drastically, and the low value area of MRSEI will gradually move downstream as time changes; (2) During the study period, the YRDUA formed a hierarchical and progressive urbanization pattern. The inland urbanization process expanded from east to west along the Yangtze River, and the urbanization process of coastal cities expanded from Shanghai as the center to the north and south with high-intensity urbanization cities concentrated in Shanghai and its surrounding cities and low-intensity urbanization cities distributed in the western part of the urban agglomeration; (3) The Coupling Coordination Degree (CCD) between urbanization and EEQ in the YRDUA has continuously improved with an increase of 28.57% in the past 21 years, and the number of cities with high level coupling continues to rise, while the number of medium level coupling cities and low level coupling cities has declined. As a large-scale and long-term analysis of changes in the EEQ and the urbanization process, this study can provide theoretical support for policymakers to formulate mesoscale development planning, EEQ monitoring, and environmental protection policies.

Ecological risk assessment in arid inland river basins is challenging because ecological degradation is jointly controlled by water scarcity, surface exposure, thermal stress, energy exchange, and vegetation buffering. Existing remote sensing indices primarily characterize ecological quality and provide limited representation of risk formation and transmission. This study developed a Dryland Ecological Risk Index (DERI) within the source–pathway–sink framework to assess ecological risks in the Shiyang River Basin from 2000 to 2025. The Bare Soil Index and Temperature Vegetation Dryness Index represented risk sources, land surface temperature and albedo characterized transmission pathways, and the Normalized Difference Vegetation Index and wetness index represented ecological sinks. Principal component analysis, correlation analysis, high-resolution imagery, and comparison with the Remote Sensing Ecological Index were used for model validation, while transition matrices characterized changes among risk classes. The first principal component explained 93.97–97.51% of the total variance, and the directions of indicator loadings were ecologically consistent. DERI was most strongly correlated with drought stress (TVDI, r = 0.58) and effectively identified fine-scale degradation in deserts, bare land, oasis margins, and oasis–desert transition zones. Ecological risk exhibited a pronounced south–north gradient, with lower risks in the Qilian Mountains, oases, and river corridors and higher risks in the northern deserts. Basin-wide risk intensified during 2000–2010, underwent substantial spatial restructuring during 2010–2015, and gradually declined after 2015. The proportion of class V areas decreased from 32.94% in 2000 to 15.35% in 2025; nevertheless, classes IV–V still accounted for 52.40% of the basin in 2025. These findings demonstrate that DERI provides a process-oriented and spatially sensitive tool for identifying ecological risk hotspots and supporting differentiated ecological management in water-limited watersheds.