Exploring the impact of urbanization on carbon emissions is crucial for formulating effective emission reduction policies. Using nighttime light data and attribute data from 68 Chinese cities (2002–2021), this paper develops an urban development evaluation system with the entropy method. The Lasso method is employed to select key factors affecting carbon emissions, and hierarchical regression models are utilized to analyze these factors across different city types. The results show the following: (1) The extraction of built-up areas using integrated nighttime light data yields an overall accuracy ranging from 70.90% to 98.87%, reflecting high precision. (2) Expanding cities have predominated over the past two decades, indicating a continued upward trend in urbanization in China. (3) Urban development is influenced by internal characteristics and geographic location: contracting cities are mainly inland heavy industrial centers, while expanding cities are located in economically advanced coastal regions. Additionally, it is also impacted by the growth of surrounding cities, exemplified by the imbalance between central cities and their peripheries within metropolitan areas. (4) The expansion of built-up areas is a significant factor affecting carbon emissions across all city types. For expanding cities, managing population growth and promoting tertiary sector development are recommended, while contracting cities should focus on judicious economic planning and virescence area protection.

Urbanization is a dynamic process. At different stages of urbanization, polices of managing car-bon emissions should be adjusted. In this paper, two types of nighttime light data and statistical data of 68 cities in China from 2002 to 2021 are used to establish an urban development evalua-tion system comprising population, economy, construction, and society subsystems. Then, cities were categorized into expanding, contracting, and stable types to understand the uncertainty of urbanization's impact on carbon emissions. The main conclusions are as follows: (1) Integrated nighttime light data is used to extract built-up area boundaries, achieving an overall accuracy ranging from 68.75% to 98.4%, with kappa coefficients ranging between 0.60 and 0.94. (2) Ex-panding cities were concentrated in the eastern coastal regions, while contracting cities were mainly located in inland cities with traditional industries. Urban agglomerations in the Beijing-Tianjin-Hebei region, Yangtze River Delta region, and Chengdu-Chongqing metropolitan demonstrate synchronized characteristic of urbanization development. (3)Economy and con-struction have a greater impact on carbon emissions than population and society. For expanding cities, the focus of carbon emission governance should prioritize rational land use planning. Conversely, for contracting cities, emphasis should be placed on adjusting economic structures.