Remote Sensing Detection of Spatiotemporal Changes in High-Altitude Urban Ecological Environment Quality Based on the Remote Sensing Ecological Index (RSEI)

Abstract

To quantify the spatiotemporal evolution patterns of ecological quality in the core area of the Qinghai-Tibet Plateau and provide a case reference for holistic plateau ecological conservation, this study selected the densely human-activity urban center of Lhasa as the research area. Utilizing Landsat 8 Level 2 remote sensing imagery from 2016 and 2023, and leveraging Google Earth Engine (GEE) for image preprocessing, four ecological indicators—greenness (NDVI), wetness (WET), dryness (NDBSI), and heat (LST)-were employed to construct an RSEI evaluation model. Through principal component analysis, multiple factors were integrated to investigate the spatiotemporal differentiation characteristics and driving mechanisms of ecological quality in the study area from 2016 to 2023. The ecological quality in the study area is generally moderate to good, with the RSEI average increasing from 0.632 in 2016 to 0.664 in 2023, indicating a steady improvement trend. Spatial heterogeneity is pronounced, with the high-vegetation river valleys along the Lhasa River serving as high-quality ecological zones (RSEI > 0.8), accounting for 17.3% to 20.1% of the area. Correlation analysis reveals that NDVI (r=0.78) and WET (r=0.76) are positive drivers of ecological quality, while NDBSI (r=-0.71) and LST (r=-0.68) act as limiting factors. The standard deviation of the RSEI during the study period decreased from 0.118 to 0.106. This provides scientific support for the spatial planning of Lhasa and the implementation of plateau ecological restoration projects, while also offering a typical research paradigm for the construction of an ecological security barrier in the Qinghai-Tibet Plateau.