Spatiotemporal Assessment and Driving Factors Analysis of Eco-Environmental Quality in Xi'an’s Main Urban Area Using the Remote Sensing Ecological Index

Qing Tang^1,2Youqing Wu³Zhigang Lu^1,2*Yu Li¹Rui Wang^1,2Li Fang¹Huineng Yan^1,2

• ¹School of Resources and Civil Engineering, Gannan University of Science and Technology, Ganzhou Jiangxi, 341000, China, Ganzhou, China
• ²Key Laboratory of Intelligent and Green Development of Tungsten & Rare Earth Resources, Jiangxi Provincial Department of Education, Ganzhou Jiangxi, 341000, China, Ganzhou, China
• ³School of Surveying and Geoinformation Engineering, East China University of Technology, Nanchang, China

Rapid urbanization and industrialization in Xi'an have precipitated a sharp conflict between spatial expansion and environmental conservation, necessitating a rigorous spatiotemporal assessment of regional ecological quality. This study evaluates the eco-environmental quality of Xi'an's main urban area from 2021 to 2024 by synergizing the Remote Sensing Ecological Index (RSEI) with advanced spatial statistical models, including Geodetector and spatial autocorrelation algorithms. Specifically, the Coefficient of Variation (CV) is introduced to quantify the temporal stability and volatility intensity of ecological quality under top-down policy interventions. Empirical results indicate that: (1) The region exhibited a generally stable trajectory, with approximately 65% of the study area maintaining a steady state. Notably, the proportion of areas showing slight improvement consistently surpassed those exhibiting degradation, signaling a cessation of historical decline; (2) Spatiotemporal stability analysis identifies a distinct "Matrix-Spot" configuration via the CV metric, characterized by a dominant low-volatility background punctuated by discrete, spatially confined high-volatility anomalies. This structure confirms that anthropogenic perturbations remained localized, preventing the propagation of systemic instability; (3) Pronounced spatial heterogeneity was corroborated by Global Moran’s I indices consistently exceeding 0.79. This distribution is predominantly characterized by high-high (H-H) clusters in ecological barriers and low-low (L-L) agglomerations in central districts, with minimal transitional patterns; (4) Factor detection identified land use change as the primary determinant of ecological differentiation. Furthermore, interaction analysis elucidated a significant "Enhancement Effect" between land use and temperature, highlighting the amplification of climatic sensitivity by urbanization. These findings provide empirical evidence for the "immediate efficacy" of strategic interventions such as the "14th Five-Year Plan" and Ecological Red Lines. The observed "policy-driven resilience" demonstrates that state-led governance has effectively buffered the negative externalities of rapid urban development within a constrained temporal window.