Nighttime light images are valuable indicators of regional economic development, and nighttime light data are now widely used in town monitoring and evaluation studies. Using the nighttime light data acquired through Luojia1-01 and the geographic information system spatial analysis method, this study analyzed the spatial vitality pattern of 402 characteristic towns in six geographic divisions of China. The average DN (Digital Number) value of Guzhen, having the highest vitality level, was 0.05665221, whereas that of Xin’an, having the lowest vitality level, was 0.00000186. A total of 89.5% of towns have a low level of vitality. The regional differences were significant; high vitality towns are concentrated in economically developed coastal areas, mainly in two large regions of east China and south central. The average lighting densities of the towns in east China and south central were 0.004838 and 0.003190, respectively. The lighting density of the towns in west central was low, and the vitality intensity was generally low. A spatially significant positive correlation of small-town vitality was observed, and “high–high” agglomeration was primarily distributed in the Yangtze River Delta, Pearl River Delta, and Fujian coastal areas in east and south China. The towns with high vitality intensity had similarities in their geographical location, convenient transportation conditions, and profound historical heritage or cultural accumulation along with many industrial enterprises. This research empirically demonstrates the feasibility of using the 130-m-high resolution of the nighttime lighting data of Luojia1-01 to evaluate the vitality at the town scale, and the vitality evaluation focuses on the spatial attributes of the town, which is meaningful to guide the development of the town in each region given the vast area of China and the large differences in the development of different regions.

China suffered from severe economic stagnation and urban decay during the COVID-19 pandemic, even public mental health was threatened. To create a favorable public consumption environment for enhancing the economic development, and meeting the needs of public life, the Chinese government has transformed and built a series of national night cultural and tourism consumption agglomeration areas as a new type of functional area in cities. The present study uses spatial analysis methods such as nearest neighbor index, nuclear density analysis, and coefficient of geographic association to quantitatively analyze the spatial distribution characteristics, equilibrium status, distribution density, and internal influential factors. The results showed the following. 1) The spatial distribution of night agglomeration areas in China is unbalanced, with a “rhombus-shaped structures, regional cluster distributions, and single nucleus aggregation points” combination of spatial distribution characteristics. 2) Eight different types of night agglomeration areas with distinctive features, large differences in spatial density, and significant geographical differentiation were identified. 3) The formation of spatial distribution patterns of night agglomeration areas was the result of the joint influence of five factors: resource endowment, economic level, transportation location, guest market, and policy environment. Understanding the current development of night agglomeration areas in China can lay the foundation for future in-depth studies on the spatiotemporal evolution of China's night tourism economy, as well as provide an urban renewal idea and experience for other global countries and regions that are facing economic crises, low urban land use efficiency, and obstruction in promoting new urbanization.