Spatiotemporal analysis of economy in China’s primary cities affected by the COVID-19 pandemic based on remote sensing of night light
LI Ruikai1(), ZHAO Zongze1(), TANG Xiaojie2, ZHANG Jiayun1, WANG Guan1, ZHANG Lijuan1
1. School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, China 2. Zhengzhou Technology and Business University, Zhengzhou 451400, China
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.
李睿锴, 赵宗泽, 汤晓洁, 张嘉芸, 王冠, 张丽娟. 夜光遥感新冠疫区主要城市经济时空分析[J]. 自然资源遥感, 2025, 37(1): 243-251.
LI Ruikai, ZHAO Zongze, TANG Xiaojie, ZHANG Jiayun, WANG Guan, ZHANG Lijuan. Spatiotemporal analysis of economy in China’s primary cities affected by the COVID-19 pandemic based on remote sensing of night light. Remote Sensing for Natural Resources, 2025, 37(1): 243-251.
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2025, Vol. 37 
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