Exploring the Spatial and Temporal Characteristics of China’s Four Major Urban Agglomerations in the Luminous Remote Sensing Perspective

This study addresses the knowledge gap regarding spatiotemporal evolution of Chinese urban agglomerations using long time series luminescence remote sensing data. The is great significance for future development and planning cities. Nighttime light data provide a window observing agglomerations’ characteristics on large spatial scale, but they are affected by temporal discontinuity. To solve this problem, proposes ridge-sampling regression-based Hadamard matrix correction method constructs consistent long-term nighttime sequences China’s four major from 1992 to 2018. Using Getis-Ord Gi* hot-cold spot, standard deviation ellipse method, Baidu search index, we comprehensively analyze directional correlations between results show that, after correction, correlation coefficient intensity gross domestic product increased 0.30 0.43. Furthermore, identifies unique features each agglomeration. Yangtze River Delta agglomeration achieved balanced shifting coastal inland areas. Guangdong-Hong Kong-Macao developed earlier grew more slowly in north due topographical barriers. Beijing-Tianjin-Hebei has Beijing Tianjin as its core, southeastern region rapidly, showing an obvious imbalance development. Chengdu-Chongqing area Chengdu Chongqing dual been significantly slower than that other three influence topography, it potential. Overall, provides research framework based explore their offers insights government planning.