Spatiotemporal analysis of economy in China’s primary cities affected by the COVID-19 pandemic based on remote sensing of night light
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摘要: 新型冠状病毒肺炎疫情(下文简称“新冠疫情”)对我国经济产生了重大影响。该研究基于NPP-VIIRS夜间灯光(night time light, NTL)数据, 选取5个曾发生大规模聚集性疫情的国内主要城市, 建立NTL指数与国内生产总值(gross domestic product, GDP)统计值的拟合模型, 反演经济月度变化情况, 得到GDP空间化数据, 并利用月度间GDP密度差值分析经济空间变化趋势。得出主要结论如下: ①利用NTL指数进行GDP空间化得到的GDP预测值相对误差较小, 能够直观清晰地反映出城市经济受疫情影响情况; ②受到人员流动政策影响, 大多数城市边缘区域在疫情初期和后期经济出现衰退, 在疫情中期经济出现增长, 而中心区经济在疫情中期出现衰退, 在疫情初期受影响较小且疫情后期恢复增长迅速; ③城市中心区域经济抵御疫情影响能力强于边缘区域。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.
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