Impact and mechanism of the COVID-19 on the spatio-temporal patterns of Zhangjiajie tourism network attention

Based on the spatial-temporal perspective of geography, this paper quantitatively measures the impact of COVID-19 on the spatial-temporal pattern of tourism network attention in Zhangjiajie, and finally summarizes the influencing factors and mechanisms. The results show as follows. (1) From the perspective of time, the online attention of tourism in Zhangjiajie shows a trend of "decline to rebound, and to stability", which reflects the temporal mobility of the effect of COVID-19 on the tourism. (2) From the spatial dimension, the scale-order of attention to the Zhangjiajie' s tourism network is relatively stable, and the effect of COVID-19 on the tourism shows a trend of "distance decay" on the whole. (3) The adjustment of tourists' perception of tourism risk, destination familiarity and location, tourists' risk tolerance and authority restriction are the influencing factors of tourism net-work attention. These factors interact with each other to drive the spatio-temporal change of tourism network attention.

Spatial Interactions and the Spread of COVID-19: A Network Perspective

We use unique data on the travel history of confirmed patients at a daily frequency across 31 provinces in China to study how spatial interactions influence the geographic spread of pandemic COVID-19. We develop and simultaneously estimate a structural model of dynamic disease transmission network formation and spatial interaction. This allows us to understand what externalities the disease risk associated with a single place may create for the entire country. We find a positive and significant spatial interaction effect that strongly influences the duration and severity of pandemic COVID-19. And there exists heterogeneity in this interaction effect: the spatial spillover effect from the source province is significantly higher than from other provinces. Further counterfactual policy analysis shows that targeting the key province can improve the effectiveness of policy interventions for containing the geographic spread of pandemic COVID-19, and the effect of such targeted policy decreases with an increase in the time of delay.

A Review of Research on Urban Playability from a Social Justice Perspective

Playability is an attribute that refers to the ability to stimulate individual responses or collective action in an immersive activity in an exploratory way. Playability is an important component of the enjoyment and well-being of urban dwellers, has the potential to stimulate urban vitality and is an important expression of the inclusiveness and equity of urban space. The pursuit of economic development and efficiency-oriented urban construction has led to the domination of urban space by overcrowded traffic, economy-oriented commerce and densely populated housing. Moreover, the existence of playable space has become a scarce resource and is seen as a site for the materialisation of social rights. As the haze of the COVID-19 pandemic fades and cities are again exposed to wider and more participatory use, determining how to adapt urban spaces to the playability needs of users of different ages, cultural backgrounds and social classes, and provide them with appropriate site use and experience, is becoming a hot issue of concern for building equitable and high-quality urban spaces. The study of the playability of urban spaces is highly complex, and the related research on social justice is cryptic. In order to better investigate the social equity aspects of urban playability, this paper integrates scientometric and manual methods to review the relevant research. This paper takes 2664 related papers from the Web of Science (WOS) core dataset from 1998 to 2022 as the research object and employs CiteSpace to organise the existing research results of playful urban spaces. Quantitative analysis is used to clarify the theoretical foundations, developments and research hotspots of urban spatial playability, while the manual collation and generalisation of the studies uncover the hidden issues of social justice research. Based on the proposed research method, we summarize the key three research stages related to urban spatial playability and social equity. We also discuss the development of urban spatial playability in the perspective of social justice from three aspects: micro, meso and macro. The results can help readers better understand the current status and development process of research on playful urban space. In particular, we clarify the issues related to social justice under the theme of the playability of urban spaces and provide directions for future research on building playful cities and promoting the development of urban socio-spatial equity.

SAUNet++: an automatic segmentation model of COVID-19 lesion from CT slices

The coronavirus disease 2019 (COVID-19) epidemic has spread worldwide and the healthcare system is in crisis. Accurate, automated and rapid segmentation of COVID-19 lesion in computed tomography (CT) images can help doctors diagnose and provide prognostic information. However, the variety of lesions and small regions of early lesion complicate their segmentation. To solve these problems, we propose a new SAUNet++ model with squeeze excitation residual (SER) module and atrous spatial pyramid pooling (ASPP) module. The SER module can assign more weights to more important channels and mitigate the problem of gradient disappearance;the ASPP module can obtain context information by atrous convolution using various sampling rates. In addition, the generalized dice loss (GDL) can reduce the correlation between lesion size and dice loss, and is introduced to solve the problem of small regions segmentation of COVID-19 lesion. We collected multinational CT scan data from China, Italy and Russia and conducted extensive comparative and ablation studies. The experimental results demonstrated that our method outperforms state-of-the-art models and can effectively improve the accuracy of COVID-19 lesion segmentation on the dice similarity coefficient (our: 87.38% vs. U-Net++: 84.25%), sensitivity (our: 93.28% vs. U-Net++: 89.85%) and Hausdorff distance (our: 19.99 mm vs. U-Net++: 26.79 mm), respectively.

Spatiotemporal Modeling of the Association between Neighborhood Factors and COVID-19 Incidence Rates in Scotland

This study aims to investigate the association between neighborhood-level factors and COVID-19 incidence in Scotland from a spatiotemporal perspective. The outcome variable is the COVID-19 incidence in Scotland. Based on the identification of the wave peaks for COVID-19 cases between 2020 and 2021, confirmed COVID-19 cases in Scotland can be divided into four phases. To model the COVID-19 incidence, sixteen neighborhood factors are chosen as the predictors. Geographical random forest models are used to examine spatiotemporal variation in major determinants of COVID-19 incidence. The spatial analysis indicates that proportion of religious people is the most strongly associated with COVID-19 incidence in southern Scotland, whereas particulate matter is the most strongly associated with COVID-19 incidence in northern Scotland. Also, crowded households, prepandemic emergency admission rates, and health and social workers are the most strongly associated with COVID-19 incidence in eastern and central Scotland, respectively. A possible explanation is that the association between predictors and COVID-19 incidence might be influenced by local context (e.g., people's lifestyles), which is spatially variant across Scotland. The temporal analysis indicates that dominant factors associated with COVID-19 incidence also vary across different phases, suggesting that pandemic-related policy should take spatiotemporal variations into account. © 2023 by American Association of Geographers.

Impact of Particulate Matter on Pre- and Post-Covid Lockdown in the Wards of Urban Jaipur

The impact of air pollutants on human health is a major issue that developing nations are facing in last decade. Effect of particulate matter especially PM2.5 and PM10 has been severely affecting mortality and morbidity in Rajasthan state as per global lead medical journal Lancet recent publication. Twelve air pollutant-monitoring sta tions in Jaipur city are not enough to predict the exact concentration of air pollutants in each of the 91 wards of Jaipur. In absence of accurate concentration at micro level, it becomes a major challenge for urban planners to remedial strategies. In this paper through GIS spatial distribution, a comparative study of particulate matter at each of the 91 wards during pre-lockdown for the year 2019 and post-lockdown 2020 was done. Results for 2020 showed slightly less pollution;similarly, air purity index, an indicator for healthier environment, was determined for each ward. © 2023 Scientific Publishers. All rights reserved.

Spatial Analysis of Socioeconomic Factors Contributing to Food Desert in North Carolina

Food deserts (FD) have attracted attention after the post-COVID-19 pandemic, primarily due to adverse health and other implications of living in areas designated as food deserts. Most studies have focused on various aspects of the impact of food deserts, including the nutritional and health risks of living in FDs. Spatial integration and analysis of the GIS data in food provide a powerful way to expose the issues of creating deserts and how they change over space and time. This study aims to investigate the socioeconomic factors influencing food deserts using geospatial analyses. Guilford, Bladen, and Rutherford Counties in North Carolina were selected as case studies due to their higher percentage of the population with limited healthy food access. This study used open-source data, such as the USDA's Crop Land Layer (CDL) land cover maps, census data, and the Food Access Research Atlas. This research provides a geostatistical analysis of FDs based on income/expenditure, population, vehicle, and food aid. The study results generally showed that geospatial technologies are vital for investigating FDs. The results will assist policy makers and other responsible agencies in formulating appropriate intervention policies tailored to meet the demands of these counties.

Spatial Epidemiology of COVID-19 Pandemic: Disease Risk, Prognosis, and Complications

Why do some populations display a higher attack and mortality rate from the current coronavirus disease 2019 (COVID-19) pandemic than others? Are there geographic, environmental, behavioral, genetic, and comorbidity differences that influence spatial dynamics of COVID-19 transmission and outcomes? Where are the regional and country-level hotspots, and what drives those hotspots? These are some of the questions the current chapter strives to answer. The dynamics of transmission and consequences of COVID-19 are not homogeneous but instead have a geographical and spatial clustering. Population-level genetic, vaccination rates, health care disparities, SARS-CoV-2 variants, and meteorological factors are all underlying determinants of the disease dynamics globally, regionally, nationally, and locally. Disease surveillance frameworks to control, mitigate, and prevent the SARS- CoV-2 infections, particularly in low- and middle-income countries, are critical. Lastly, we highlight the spatial differences in the consequences of the pandemic focusing on behavioral and post-acute sequelae of SARS-CoV-2 infection. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Unraveling the Impact of COVID-19 Pandemic Dynamics on Commercial Water-Use Variation

Water use was impacted significantly by the COVID-19 pandemic. Although previous studies quantitatively investigated the effects of COVID-19 on water use, the relationship between water-use variation and COVID-19 dynamics (i.e., the spatial-temporal characteristics of COVID-19 cases) has received less attention. This study developed a two-step methodology to unravel the impact of COVID-19 pandemic dynamics on water-use variation. First, using a water-use prediction model, the water-use change percentage (WUCP) indicator, which was calculated as the relative difference between modeled and observed water use, i.e., water-use variation, was used to quantify the COVID-19 effects on water use. Second, two indicators, i.e., the number of existing confirmed cases (NECC) and the spatial risk index (SRI), were applied to characterize pandemic dynamics, and the quantitative relationship between WUCP and pandemic dynamics was examined by means of regression analysis. We collected and analyzed 6-year commercial water-use data from smart meters of Zhongshan District in Dalian City, Northeast China. The results indicate that commercial water use decreased significantly, with an average WUCP of 59.4%, 54.4%, and 45.7%during the three pandemic waves, respectively, in Dalian. Regression analysis showed that there was a positive linear relationship between water-use changes (i.e., WUCP) and pandemic dynamics (i.e., NECC and SRI). Both the number of COVID-19 cases and their spatial distribution impacted commercial water use, and the effects were weakened by restriction strategy improvement, and the accumulation of experience and knowledge about COVID-19. This study provides an in-depth understanding of the impact of COVID-19 dynamics on commercial water use. The results can be used to help predict water demand under during future pandemic periods or other types of natural and human-made disturbance.

Impact of COVID-19 on the Territory and Demographic Processes: A View from Spanish Rural and Urban Areas

The current physiognomy and problems of rural and urban territories in Spain are directly related to the demographic processes linked to the rural exodus of the 1960s. In the year 2020, a new problem and/or conditioning factor arose, COVID-19, which has modified dynamics, routines, and aspects of the daily life of the population. The objectives of this research are to check whether there are differences in the effect of COVID-19 between urban and rural municipalities and, in turn, to analyse the demographic dynamics of the population between 2020 and 2022, as well as territorial distribution patterns. To this end, population data were extracted from the Population Register and Residential Variation data for the period 2010 and 2022 and demographic and statistical calculations (Student's t-test and Pearson's correlation) were carried out. Among the main results, it is observed that COVID-19 has less of an effect in Spanish rural areas. Moreover, these areas show a positive demographic trend for the period 2020-2022. Population growth has had a direct influence on the improvement of demographic data, although with differences according to autonomous communities. This fact represents a break in the trend in rural areas, but is beginning to show signs of exhaustion and a return to the pre-pandemic trend.

The immunopathology of COVID-19 placentitis: A multi-omic spatial approach

Problem: COVID-19 placentitis is a rare complication of maternal SARS-CoV-2 respiratory infection associated with serious adverse obstetric outcomes, including intra-uterine death. The precise role of SARS-CoV-2 in COVID-19 placentitis is uncertain, as trophoblast infection is only observed in around one-half of the affected placenta. Method of Study: Through multi-omic spatial profiling, including Nanostring GeoMX digital spatial profiling and Lunaphore COMET multiplex IHC, we provide a deep characterization of the immunopathology of placentitis from obstetrically complicated maternal COVID-19 infection. Result(s):We show that SARS-CoV-2 infection of placental trophoblasts is associated with a distinct innate and adaptive immune cell infiltrate, florid cytokine expression and upregulation of viral restriction factors. Quantitative spatial analyses reveal a unique microenvironment surrounding virus-infected trophoblasts characterizedd by multiple immune evasion mechanisms, including immune checkpoint expression, cytotoxic T-cell exclusion, and interferon blunting. Placental viral loads inversely correlated with the duration of maternal infection consistent with progressive virus clearance, potentially explaining the absence of virus in some cases. Conclusion(s): Our results demonstrate a central role for placental SARS-CoV-2 infection in driving the unique immunopathology of COVID-19 placentitis.

Spatial clustering-based method for Italian marginal areas toward the sustainable regeneration

In Italy, there is a clear disparity between cities and villages located in marginal areas. The progressive depopulation of inland areas and the urban polarization represent consolidated dynamics difficult to adapt to the new paradigm of sustainable development. The post-Covid-19 pandemic scenario offers the opportunity to redefine new parameters of intervention and new visions for the regeneration of villages in accord with the new challenges of decentralization and distancing. The project «Renaissance of villages for the revitalization of marginal areas» (2021) aims to create the conditions to repopulate and rebalance shrinking territories by establishing new centres of attractiveness. This project envisages the active involvement of municipalities to implement multi-sectoral analysis and spatial assessment approaches in planning processes. It intends to develop an interactive web dashboard for local authorities and spatial planners to create both a learning environment and a participative spatial decision support system for future local policy actions toward sustainable local development. This study presents the project's preliminary phase which aims to create the general framework of the web dashboard. A reconstruction of the village definition and the spatial selection of villages throughout Italy are presented as innovative aspects since the absence of an agreed definition of the village in the national and international level documents. Moreover, this study provides a quantitative spatial multivariate analysis cluster that analyzes, and groups Italian territories based on socioeconomic dynamics. The result of this analysis allows us to divide the territory into archetypes and to structure a framework that supports the definition of future scenarios for the regeneration of small urban areas considering the diversified needs and potential of the villages belonging to specific archetypes analyzed in the study.In Italia esiste una netta disparità tra città e borghi situati in aree marginali. Il progressivo spopolamento delle aree interne e la polarizzazione urbana rappresentano dinamiche consolidate poco affini ai paradigmi dello sviluppo sostenibile. Lo scenario post pandemico offre oggi l'opportunità di ridefinire nuovi parametri di inter- vento e nuove visioni per la rigenerazione dei borghi in accordo con le sfide imposte dal decentramento e dal distanziamento fisico. Il progetto «Rinascimento dei borghi per la rivitalizzazione delle aree marginali» (2021) mira a creare le condizioni per ripopolare e rigenerare i territori in contrazione. L'efficacia del progetto si fonda sul coinvolgimento attivo dei comuni nei processi di pianificazione e sull'integrazione in essi di analisi multisettoriali sperimentando un approccio basato sulla va- lutazione territoriale. Nell'ambito del progetto s'intende sviluppare un cruscotto web interattivo indirizzato alla pubblica amministrazione e ai pianificatori territoriali, al fine di creare un sistema partecipativo di supporto alle decisioni spaziali propedeutico allo sviluppo di scenari di sviluppo locale sostenibile. Questo studio presenta la fase preliminare del progetto in cui viene predisposta la struttura generale del cruscotto web. La ricerca e la ricostruzione della definizione di borgo, seguita dalla se- lezione spaziale dei borghi in tutta Italia, sono presentati come aspetti innovativi data l'attuale assenza di una definizione a livello nazionale e internazionale. Inoltre, questo studio fornisce un'analisi spaziale quantitativa multivariata che analizza e riunisce in cluster i territori italiani in base alle dinamiche socioeconomiche. Il risultato di questa analisi permette di suddividere il territorio in archetipi e di strutturare un quadro di riferimento che supporti la definizione di scenari futuri per la rigenerazione delle piccole aree urbane, considerando le esigenze e le potenzialità diversificate di ogni singolo borgo.

Tracking the Transit Divide: A Multilevel Modelling Approach of Urban Inequalities and Train Ridership Disparities in Chicago

Using a multilevel modelling approach, this study investigates the impact of urban inequalities on changes to rail ridership across Chicago's "L” stations during the pandemic, the mass vaccination rollout, and the full reopening of the city. Initially believed to have an equal impact, COVID-19 disproportionally impacted the ability of lower socioeconomic status (SES) neighbourhoods' to adhere to non-pharmaceutical interventions: working-from-home and social distancing. We find that "L” stations in predominately Black or African American and Hispanic or Latino neighbourhoods with high industrial land-use recorded the smallest behavioural change. The maintenance of higher public transport use at these stations is likely to have exacerbated existing health inequalities, worsening disparities in users' risk of exposure, infection rates, and mortality rates. This study also finds that the vaccination rollout and city reopening did not significantly increase the number of users at stations in higher vaccinated, higher private vehicle ownership neighbourhoods, even after a year into the pandemic. A better understanding of the spatial and socioeconomic determinants of changes in ridership behaviour is crucial for policymakers in adjusting service routes and frequencies that will sustain reliant neighbourhoods' access to essential services, and to encourage trips at stations which are the most impacted to revert the trend of declining public transport use.

Earth's magnetic field spatial-temporal changes in relation to the SARS-CoV-2 virus spreading

The results of a study on the possible connection between the spread of the SARS-CoV-2 virus and the Earth's magnetic field based on the analysis of a large array digital data for 95 countries of the world are presented. The dependence of the spatial SARS-CoV-2 virus spread on the magnitude of the BIGRF Earth's main magnetic field modular induction values was established. The maximum diseases number occurs in countries that are located in regions with reduced (25. 0-30. 0 μT) and increased (48. 0-55. 0 μT) values, with a higher correlation for the first case. The spatial dependence of the SARS-CoV-2 virus spreading on geomagnetic field dynamics over the past 70 years was revealed. The maximum diseases number refers to the areas with maximum changes in it, both in decrease direction (up to - 6500 nT) and increase (up to 2500 nT), with a more significant correlation for countries located in regions with increased geomagnetic field. © 2022 EAGE. All Rights Reserved.

Planning cities for pandemics: A review of urban and transport planning lessons from COVID-19

For the past years, the world has been facing one of the worst pandemics of modern times. The COVID-19 outbreak joined a long list of infectious diseases that turned pandemic, and it will most likely leave scars and change how we live, plan, and manage the urban space and its infrastructures. Many fields of science were called into action to mitigate the impacts of this pandemic, including spatial and transport planning. Given the large number of articles recently published in these research areas, it is time to carry out an overview of the knowledge produced, synthesising, systematising, and critically analysing it. This article aims to review how the urban layout, accessibility and mobility influence the spread of a virus in an urban environment and what solutions exist or have been proposed to create a more effective and less intrusive response to pandemics. This review is split into two avenues of research: spatial planning and transport planning, including the direct and indirect impact on the environment and sustainability. © 2023 ICE Publishing: All rights reserved.

The spatial concentration, stability, and specialization of mental health calls for service: Evidence in support of proactive, place-based interventions

For many decades the police have been the de facto responders to persons with perceived mental illness (PwPMI). However, having the police in this role has come with negative repercussions for PwPMI, such as disproportionately experiencing criminalization and use of force. In recognizing these issues, the police-and more recently, the community-have developed responses that either seek to improve interactions between the police and PwPMI or remove the police from this role altogether. However, in either case, these efforts are reactivein nature, responding to crises that arguably could have been prevented had a timelier intervention taken place. Further, evidence on certain police responses to PwPMI, such as Crisis Intervention Teams (CIT) and co-response teams, suggests that they endure deployment-related challenges, thus limiting their reach to PwPMI.Drawing from the Criminology of Place and existing place-based policing strategies, the present dissertation argues that efforts focused on respondingto PwPMI should instead be proactively deployed, targeting areas where interactions between police and PwPMI concentrate spatially. Doing so would not only result in efficient deployment of scarce resources but would permit police- and community-based efforts to have a greater reach to PwPMI and thus prevent future interactions with police. To-date, however, there have been few empirical and theoretical investigations into the spatial patterns of PwPMI calls for service that could inform such proactive, place-based efforts. Specifically, we do not currently understand: (1) the degree to which PwPMI calls for service concentrate within certain geographical contexts (such as a small city);(2) whether the degree of PwPMI call concentration and the location of these calls remain stable over time;and (3) what theoretical frameworks explain why PwPMI calls for service occur where they do. Drawing on seven years (2014-2020) of calls for service data from the Barrie Police Service and data from the 2016 Canadian Census, the present dissertation employs various methods of spatial analysis to fills these specific knowledge gaps.Although the theoretical investigation confirmed the findings of previous work that found no association between social disorganization theory and the spatial patterns of PwPMI calls for service, the present dissertation revealed: (1) PwPMI calls for service are highly concentrated within the context of a small city, even more so than what has previously been uncovered in larger jurisdictions;(2) the degree of PwPMI call concentration is stable over time, falling within a narrow proportional bandwidth of spatial units;and (3) PwPMI calls for service, and their concentrations, occur in the same places over time-even during the COVID-19 pandemic-and are thus spatially stable. As such, though more scholarship is needed on theories that might help explain why PwPMI calls occur where they do, the findings of the present dissertation strongly support the proactive, place-based deployment of resources to PwPMI. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

From the Editors

Since 2022, the journal Izvestiya Rossiiskoi Akademii Nauk. Seriya Geograficheskaya is publishing special issues on important topics in geography. The comprehensive special section offered to readers' attention is another innovation of the journal. This collection has been prepared for the centennial of the International Geographical Union and its congress in Paris (July 2022). It includes seven review articles. Their English translations are simultaneously published in the journal Regional Research of Russia, no. 1 for 2022. These circumstances determine articles' genre and fundamental features. The topics of the articles were chosen so that the special section reflects areas in which the most striking results have been achieved and which are specific to Russia. The authors are leading Russian experts in their respective fields. They have tried, as far as possible, to compare the topics, methodological approaches, and research results with the world mainstream. The main focus is on the last decade, 2010–2021;when necessary, the authors also have referred to earlier publications. The authors of most of the articles pay attention to the peculiarities of spatial development that arose in 2020–2021 due to the COVID-19 pandemic. © 2022 Izvestiya Rossiiskoi Akademii Nauk. Seriya Geograficheskaya. All rights reserved.

Spatial determinants affected maternal mortality of East Java province during the covid-19 pandemic era, in 2020-2021

Background. Every life aspect and group of the community have changed during the COVID-19 pandemic, including the group of pregnant, childbirth, and postpartum woman. COVID-19 Pandemic occurred in 2020-2021. Maternal mortality in East Java Province was the highest in Indonesia during the pandemic. Objective. This study analyzed the effect of spatial determinants that consist of antenatal, childbirth, and post-partum care on maternal mortality in East Java Province during the Pandemic. Methods. This study used a crossectional method with the unit of analysis in this study was all pregnant, childbirth and postpartum women in 38 districts of East Java Province from 2020 until 2021. Data were analyzed with spatial regression by using Geographically Weighted Regression Software. Results. Maternal mortality in East Java had a spreading pat-tern and negative value of the diff criterion, so we concluded that there was a spatial influence. The variables of antenatal care, accessibility of healthcare service, third postpartum visit, and complication service had significant effects on maternal mortality in all regions (P<0,05). There were four groups of districts that showed a similarity of significant factors. This result showed that each region's diversity of the accessibility of health services affects maternal mortality during the COVID-19 era. Antenatal services, access to health facilities and complication services affected maternal mortality in regions with high maternal mortality rate. Conclusion. Every region has its spatial determinants of maternal mortality. The top government should give authority to local government to have programs to reduce maternal mortality according to the condition in their region. r.Copyright © the Author(s), 2023.

GIS-Based Analysis of the Spatial Distribution and Influencing Factors of Traditional Villages in Hebei Province, China

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.

The Influence of Density and Mixed Land Use on The Spread of Covid-19 in Surakarta City

Covid-19 has a significant risk of spreading in urban areas because of the aglomeration of built-up areas and people. It frequently contains a mix of land uses and is accessible to urban amenities. Due to the area's extensive usage of mixed land uses, it is better able to provide internal urban services on its own. Greater use of area lockdown and social separation strategies could result from this situation. The most populous city in the province of Central Java, Surakarta, has a significant risk of contracting COVID-19. The purpose of this study is to evaluate the impact of density and levels of mixed land use on the Covid-19 distribution in Surakarta City.Population density is used to calculate density. The entropy index approach was used to measure the amount of mixed land use. It is a method for calculating the balance between each form of land use. The availability of current land use data being processed by the spatial analysis with the Arc GIS application provided help for the analysis. Additionally, it makes use of information on Covid-19 cases in relation to the general populace that is supplied by the Surakarta Municipality. The relationship between mixed land use and Covid-19 risk was analyzed using a linear regression approach. The study's findings indicated a minor influence between density and the spread of COVID-19. Meanwhile, the level of mixed land use does not influence the spread of the Covid-19 virus in Surakarta City.