ABSTRACT
Traditional villages are a valuable cultural asset that occupy an important position in Chinese traditional culture. This study focuses on 206 traditional villages in Hebei Province and aims to explore their spatial distribution characteristics and influencing factors using ArcGIS spatial analysis. The analysis shows that traditional villages in Hebei Province were distributed in clusters during different historical periods, and eventually formed three core clusters in Shijiazhuang, Zhangjiakou and Xingtai-Handan after different historical periods. Moreover, the overall distribution of traditional villages in Hebei Province is very uneven, with clear regional differences, and most of them are concentrated in the eastern foothills of the Taihang Mountains. To identify the factors influencing traditional villages, natural environmental factors, socio-economic factors, and historical and cultural factors are considered. The study finds that socio-economic and natural environmental factors alternate in the spatial distribution of traditional villages in Hebei Province. The influence of the interaction of these factors increases significantly, and socio-economic factors have a stronger influence on the spatial distribution. Specifically, the spatial distribution of traditional villages in Hebei Province is influenced by natural environmental factors, while socio-economic factors act as drivers of spatial distribution. Historical and cultural factors act as catalysts of spatial distribution, and policy directions are external forces of spatial distribution. Overall, this study provides valuable insights into the spatial distribution characteristics and influencing factors of traditional villages in Hebei Province, which can be used to develop effective strategies for rural revitalisation in China.
ABSTRACT
The COVID-19 pandemic has presented unprecedented disruptions to human society worldwide since late 2019, and lockdown policies in response to the pandemic have directly and drastically decreased human socioeconomic activities. To quantify and assess the extent of the pandemic's impact on the economy of Hebei Province, China, nighttime light (NTL) data, vegetation information, and provincial quarterly gross domestic product (GDP) data were jointly utilized to estimate the quarterly GDP for prefecture-level cities and county-level cities. Next, an autoregressive integrated moving average model (ARIMA) model was applied to predict the quarterly GDP for 2020 and 2021. Finally, economic recovery intensity (ERI) was used to assess the extent of economic recovery in Hebei Province during the pandemic. The results show that, at the provincial level, the economy of Hebei Province had not yet recovered;at the prefectural and county levels, three prefectures and forty counties were still struggling to restore their economies by the end of 2021, even though these economies, as a whole, were gradually recovering. In addition, the number of new infected cases correlated positively with the urban NTL during the pandemic period, but not during the post-pandemic period. The study results are informative for local government's strategies and policies for allocating financial resources for urban economic recovery in the short- and long-term. © 2022 by the authors.
ABSTRACT
The distributed accounting method of blockchain, together with its decentralized and tamper proof characteristics, can solve the problem of lack of food safety traceability data and low credibility, which enable the traceability requirements of food chain traceability, problem food recall, food circulation information query. It also improves the food flow mode, and establishes a new food safety ecosystem. This paper innovatively integrates the principle of blockchain into the traceability and circulation process of Hebei cold chain food. In order to find the proportion and distribution of various types of commodities in the circulation of imported and domestic cold chain food in Hebei Province, the combination of qualitative and quantitative analysis methods, chi square test, association rules and other analysis methods are used. The results show that the demand for cold chain food in Hebei Province is mainly domestic food and supplemented by imported food. Cold chain poultry is the main need and other cold chain food is supplement. The flow of imported cold chain food is mainly from the surrounding provinces and cities. Furthermore, in the process of tracing the positive commodities, it is found that there are four main modes of commodity circulation in Hebei Province, namely, family model from farmer, wholesale market, new retail and multi-level sales model. The new retail and multi-level sales model fill the gap in the distribution and circulation of cold chain goods in Hebei Province. © 2021 ACM.
ABSTRACT
The outbreak of COVID-19 in 2020 greatly impacted China's transportation industry. This paper aims to analyze this impact and the indispensable role of public transport control measures in preventing the spread of the epidemic. The impact of SARS and COVID-19 was compared. Taking Hebei Province as an example, the impact of the epidemic on the public transport industry was analyzed. The information of Jincheng public transport network and bus IC card data were selected for analysis. The parameters of bus network density and bus line repetition coefficient were calculated. The number of bus departures of each line before and after Jincheng epidemic was counted. Based on the data of bus IC card, the dynamic network of passenger contact was constructed, and the passenger contact network diagram was drawn. The analysis results can inform and enable urban public transport departments to take control measures when public health emergencies occur. © 2021 CICTP 2021: Advanced Transportation, Enhanced Connection - Proceedings of the 21st COTA International Conference of Transportation Professionals. All rights reserved.
ABSTRACT
Hebei Province was affected by two coronavirus disease 2019 (COVID-19) outbreak waves during the period 22 January 2020 through 27 February 2020 (wave 1) and 2 January 2021 through 14 February 2021 (wave 2). To evaluate and compare the epidemiological characteristics, containment delay, cluster events and social activity, as well as non-pharmaceutical interventions of the two COVID-19 outbreak waves, we examined real-time update information on all COVID-19-confirmed cases from a publicly available database. Wave 1 was closely linked with the COVID-19 pandemic in Wuhan, whereas wave 2 was triggered, to a certain extent, by the increasing social activities such as weddings, multi-household gatherings and church events during the slack agricultural period. In wave 2, the epidemic spread undetected in the rural areas, and people living in the rural areas had a higher incidence rate than those living in the urban areas (5.3 vs. 22.0 per 1 000 000). Furthermore, Rt was greater than 1 in the early stage of the two outbreak waves, and decreased substantially after massive non-pharmaceutical interventions were implemented. In China's 'new-normal' situation, development of targeted and effective intervention remains key for COVID-19 control in consideration of the potential threat of new coronavirus strains.