Abstract: The Corona Virus Disease 2019 (COVID-19) pandemic significantly affected China’s economy. This study investigated China’s five cities that witnessed large-scale COVID-19 outbreaks based on NPP-VIIRS night light (NTL) data. A fitting model between the NTL index and GDP statistics was established. This model can reflect the monthly economic variations, yielding the spatial distribution of GPD. Finally, this study analyzed the trend in the spatial variations of the economy in the five cities during the COVID-19 pandemic by analyzing the differences in monthly GDP density. The results indicate that the GDP predicted using the GDP spatialization based on the NTL index exhibited relatively small errors and can reflect the impacts of the COVID-19 pandemic on the urban economy in an intuitive and clear manner. Under the influence of mobility policies, the marginal areas of most of the cities experienced economic recession in the early and late stages of the pandemic, with economic growth observed in the middle stage of the pandemic. In contrast, the central areas of the cities experienced economic recession in the middle stage of the pandemic, were subjected to minor impacts in its early stage, and witnessed a rapid economic recovery in its late stage. Additionally, the economy in the central areas of the cities was more resistant to the impacts of the pandemic than that in their marginal areas.