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The scientific evaluation of landscape performance has become a critical focus in promoting landscape architecture and urban quality research. Structural equation modeling (SEM) is widely applied in digital assessments and performance studies, offering robust analytical capabilities. However, further progress requires a systematic review to synthesize past findings and identify emerging opportunities. This study reviews 245 articles that utilize SEM in landscape performance research, analyzing publication trends, research dimensions, methodologies, and data sources. The results indicate that SEM-based studies are predominantly focused on cognitive environmental performance based on subjective evaluation data. SEM can be applied to analyze the correlation mechanisms between landscape performance and influencing factors, examine the mediating effects among multiple factors, and conduct comparative analyses across different sample groups. Future research should prioritize integrating subjective and objective assessments, developing open-source databases, and promoting practical applications of SEM technologies. These efforts will enhance policy-making and improve the precision of performance evaluations, strengthening the scientific foundation of landscape architecture and quality enhancement research.
