Analysis of Spatiotemporal Characteristics and Influencing Factors of Land Urbanization Level in China at Different Scales Based on Nighttime Light Remote Sensing

Abstract

Urbanization is an important symbol of regional economic development and social progress. Studying the urbanization level is greatly important for the scientific development of towns and cities, and for the efficient decision-making of governments. The nighttime light data, which encompasses valuable insights into human activities, economic progress, and social development, effectively addresses the limitations associated with the indicator method in terms of uncertainty and lag issues. Those data can also provide a more intuitive reflection of the level of urbanization and offer novel insights for research on urbanization. In this study, based on the 2000–2020 EANTLI_Like nighttime light remote sensing data, the characteristics of the spatial and temporal dynamic changes in the land urbanization level in China were measured. Results were analyzed at four scales: national, regional, provincial, and municipal. Finally, the main economic indicators affecting urbanization were selected as variables to simply analyze the driving force of land urbanization through spatial autocorrelation and spatiotemporal geographically weighted regression model. Results indicated that China's land urbanization level continued to grow from 2000 to 2020, with an average annual growth rate of 2.51%. The spatial distribution of land urbanization varied significantly across regions. The level of land urbanization in the eastern coastal region was significantly higher than that in the inland and western provinces, at the agricultural and provincial scales. Hong Kong, Macao, and Shanghai ranked high in terms of land urbanization, and the Pearl River Delta and Yangtze River Delta regions in which they were located also belong to the cluster of high land urbanization levels. Meanwhile, the goodness of fit among GDP, the proportion of output of secondary and tertiary industries, freight volume, and land urbanization level were higher than 0.86. Among them, GDP and the output of secondary and tertiary industries had a more obvious role in promoting land urbanization. The freight volume exhibited positive effects on land urbanization level in the western region, Heilongjiang, and Jilin provinces. This study is very important for understanding the law of urban construction land expansion in China, the regional differences in land urbanization level, and the optimization of land use layout.

Keywords

• Nighttime light remote sensing
• scale
• spatiotemporal analysis
• urbanization