An Annual “Urban Core-Suburban-Rural” Triad Structure Dataset for China From 1992 to 2021

Abstract

China has experienced a rapid urbanization over the past three decades, resulting in a prominent “urban core-suburban-rural” (USR) triad structure of human settlements. The USR disparities, which are related to the spatial variations of human activity intensity, have significant impacts on the spatiotemporal variations in various environmental issues such as carbon dioxide (CO2) emissions, carbon storage, water quality, etc. However, there is a lack of national-level, long-term USR dataset compared to the large number of “Urban-Rural” dual-structure datasets. In this study, an annual USR dataset from 1992 to 2021 in China is delineated by using the nighttime light data, which is the first full coverage, long-term USR dataset of China. The consistency with other remote sensing products (global urban boundaries) and socio-economic data (demographic and point of interest data) demonstrates that the USR dataset is reliable for characterizing the spatial extents of human settlements with distinct socio-economic activity intensities. The USR maps have shown that the Chinese urban core area increased 9-fold from 16,500 km2 in 1992 to 165,000 km2 in 2021. The application of USR data in Fossil Fuel Combustion CO2 (ffco2) emissions indicates that ffco2 emissions in urban core, suburban, and rural area increased 1.34, 0.36, and 0.17 billion of tons from 2000 to 2019 in China, respectively. The dataset can be used for other environmental research issues in China, which has not been possible before because of the lack of the long-term USR triad structure of human settlements.

Keywords

• China
• dataset
• nighttime light (NTL)
• urban core-suburban-rural (USR)
• urbanization