Understanding China's resumption of work and production during the critical period of COVlD‐19 based on multi‐source data

Abstract

Monitoring the resumption of work and production (RWP) is of great significance to the restoration of social order and the economy after the coronavirus disease 2019 (COVID‐19) epidemic. In this study, the most critical period of epidemic prevention and control and economic recovery was divided into four phases according to the changes in emergency response levels during the epidemic in China, and based on VIIRS I‐Band 375‐m active fire data (VNP14IMG), NO2 tropospheric vertical column density (TVCD) data, and intracity travel intensity data, the density‐based spatial clustering of applications with the noise logistic regression industrial heat source identification model, NO2 difference model, and urban relative recovery index were constructed to analyze work resumption at different phases. The results indicate that: (1) the production intensity of China's heat source enterprises decreased first and then exceeded the epidemic period compared with the same period in history. From phases 1 to 3, the heat source enterprise production intensity was lower than the same period in 2019 (the production intensities were 19,562.79, 22,462.57, and 38,466.89, respectively), and the reduction rates of production intensity were 27.5, 26.1, and 22.7%, respectively. In phase 4, enterprise production intensity achieved an increase of 7%. (2) The process of the RWP in China is closely related to NO2 TVCD. In the first three phases, significantly decreased emission sources of NO2 reduced the total value of NO2 by varying degrees in most provinces of the country. Correspondingly, in phase 4, the NO2 TVCD in some provinces recovered to the value of the same period in 2019, including typical industrial bases (Shandong, Hebei, Shanxi, etc.) and economically developed coastal areas (Jiangsu, Guangdong, Zhejiang, etc.). (3) In phase 3, the intracity travel intensity in all cities improved, and the city relative recovery index (RRI) rose across the board. In particular, the western cities were better than the eastern cities. Among them, the RRIs of most cities in southwest China (Sichuan, Yunnan) and northwest China (Gansu) were more than 90%. Notably, the recovery situation exhibited an obvious “siege phenomenon,” and the recovery of core cities required a longer period. Overall, the sudden COVID‐19 epidemic seriously affected the production of Chinese enterprises. However, benefitting from rapid and effective epidemic prevention and control measures, the resumption of work and production has been a success. Our study provides guidance for economic recovery strategies during post‐pandemic stages.

Dynamic Fire Monitoring Analysis and Risk Assessment Based on Multisource Satellite Remote Sensing

“…In this paper, using national MODIS data set of fire trails (MCD45A1) and fire point products (MOD14A2) from 2001 to 2014, we can not only analyze spatial and temporal distribution and occurrence pattern of forest fires in China in past 14 years, which can provide scientific basis for forest fire prevention and decision making in China, but also analyze distribution characteristics of FRP (fire radiative power) in MOD14A2 data, which can provide scientific basis for forest fire prevention and forest change monitoring. e model of remote sensing estimation of forest biomass by forest type can provide scientific decision for forest fire prevention and forest change monitoring; it can also provide a theoretical basis for sustainable development of carbon cycle in China's forest ecosystem, impact of forest fires on atmosphere, global carbon cycle and carbon balance, and estimation of forest carbon sinks [7]. It is also important for the study of global carbon cycle and carbon balance and estimation of forest carbon sink, etc.…”

Visual supervision of large‐scope heat source factories based on knowledge graph

“…It can provide reliable information to support accurate supervision and enforcement. Industrial heat source objects can be updated within a specific time period due to the continuous updating of data, to provide timely and rapid feedback on enterprise production activity information (Lai, Zhu, Xie, et al, 2022). For example, following the outbreak of COVID‐19, many heat source factories in China experienced a production shutdown or reduction.…”

Geographical detector-based assessment of multi-level explanatory powers of determinants on China’s medical-service resumption during the COVID-19 epidemic

“…After fighting the epidemic for 2–3 months since December 2019, China had made a great success to control the large-scale epidemic spread (Kraemer et al, 2020; Tian et al, 2020; Xu et al, 2020a), and then the focus of strategies shifted to control international importations and recover production and life. Scholars began to focus on the assessments of regional resumptions of work, production, and social life on different geographical scales, such as the entire country (Lai et al, 2022; Tao et al, 2020; Tian et al, 2021; Xu et al, 2020b), provinces/municipalities (He et al, 2021; Zhang et al, 2021), and prefecture-level cities (Bai et al, 2021; Shao et al, 2021). Various strategies and measures for the work resumption and the corresponding risks were explicitly evaluated (Bai et al, 2021; Ge et al, 2021; Wang et al, 2020; Zhang et al, 2021).…”

“…Satellite remote sensing data, in particular nighttime light (NTL) images, are beneficial and conducive to evaluating the epidemic impact on human activities, assessing the regional work resumption, and monitoring its spatiotemporal variation in large-scale areas (Liu et al, 2020; Shao et al, 2021; Tao et al, 2020; Tian et al, 2021). Satellite observations can also be combined with other multi-source data (e.g., intracity travel intensity data) to implement the assessment of work resumption (Lai et al, 2022). Nevertheless, the above data sources cannot support the assessment of work resumption in a high-resolution space-time domain.…”