Volume 16 Issue 6
Published on June 2025This study takes City S, a mega-city in North China, as the research object. Based on a thorough review of relevant literature and theoretical foundations, it employs the Principal Component Analysis (PCA) method to construct a multidimensional indicator system encompassing population, economy, society, and ecology. Using statistical data from 2013 to 2020, the study quantitatively analyzes the degree of influence exerted by various driving factors on urban landscape changes. The results show that natural factors, population factors, economic development factors, and social policy factors are the primary drivers of landscape change. Social development and ecological constraints also play a role in the adjustment of urban spatial structure to a certain extent. The study further reveals the comprehensive driving mechanism underlying urban landscape evolution and provides a theoretical basis and methodological support for urban land use optimization and landscape planning. PCA demonstrates strong applicability in identifying multifactor coupling mechanisms and can serve as a scientific reference for the formulation of urban sustainable development strategies.
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