The Fruits of Labor: Home Food Procurement and Mental Health in the Time of COVID-19

We examine the relationship of home food procurement (HFP) during COVID-19 to emotional eating and stress using a statewide representative survey (n = 600) in Vermont. Women and people with a job change since COVID-19 were more likely to experience higher stress and emotional eating. Engaging in HFP, especially gardening, is associated with less emotional eating. However, people who fished, hunted, or canned more since the pandemic began were more likely to eat for emotional reasons and experience higher stress. These results suggest that gardening, even during a pandemic, may contribute to stress reduction, more so than other nature-based food production activities.Copyright © 2022 Taylor & Francis Group, LLC.

Farmers' willingness to stabilize the land contract relationship facing the upcoming expiry of land contracts

On the verge of the expiry of land contracts, it is theoretically and practically important to explore the willingness and motivations of farmers to stabilize the land contract relationship, with regards to protecting their land contract rights, addressing potential contradictions during the land contract extension, and maintaining the stability of contracted land. Using China Land Economic Survey Data in 2020, this paper explores the impact of differences in areas per capita of household contracted land on farmers' willingness to stabilize land contract relationship. The findings show that most farmers support the stability of land contract relationship;the smaller areas per capita of contracted land are occupied by households than the average in the village, the weaker of the farmers' willingness to stabilize the land contract relationship. The difference between the areas per capita of contracted land ownership of a household and the average in the village has a greater impact on the willingness to stabilize land contract relationship for middle-and low-income farmers, while the development of land transfer market does not increased the willingness. Affected by the COVID-19 pandemic, the land plays a more important role of employment security, which reduces farmers' willingness to stabilize the land contract relationship. Furthermore, the promotion of socialized agricultural service has also mitigated the willingness of farmers o stabilize the land contract relationship.

Study on Dynamic Change of Land Usage in Hongta District Based on Sentinel-2

This work utilizes Sentinel-2A L1C remote sensing photographs from the years 2018, 2020, and 2022 to identify the different land use categories in the study area using the support vector machine (SVM) technique. The accuracy of categorization is greater than 90%. This research explores four factors of the dynamic change in land use in Hongta District from 2018 to 2022: the proportion of various types of land;the extent of something like the changing land usage;land use transfer;and the dynamic degree of the change in land use. According to the study's results, the proportion of cultivated and grassland land grew, while the quantity of barren and construction land fell by 1.90 percent, 0.03 percent, and 0.69 percent, respectively. The water system land portion of total area increased by 2.58 percent and 0.13 percent, respectively. After comparing the two research periods, the entire dynamic degree of the second stage is determined to be 3.5 percent lower than that of the first stage, and the pace of land use change is quite sluggish, which may be associated with the worldwide COVID-19 outbreak in 2020. The outcomes of the research may give the natural resources department the knowledge it needs to manage land resources properly. © 2023 SPIE.

Geo-Economy of the Future: Sustainable Agriculture and Alternative Energy: Volume II

This book presents an international review of the modern geo-economy and a scientific take on the geo-economy of the future. It identifies the challenges of climate change and their impact on the modern geo-economy. Prospects for the geo-economy of the future are outlined based on sustainable agriculture and alternative energy. Policy implications are put forward to develop a geo-economy of the future in response to the challenges of climate change. The book presents management implications for the development of the geo-economy of the future in response to the challenges of climate change at the regional and global scale. It presents the lessons-learned through the COVID-19 pandemic, and applies experiences of countries with different environmental conditions for agriculture and the development of the energy sector. Based on these results, advanced practical recommendations and ready-made frameworks at the national, regional, and enterprise level are provided. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

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.

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.

Activity-based integrated modelling for assessing COVID-19 impacts on transport operations and emissions

This study combines an integrated transport, land-use, and energy (iTLE) modeling system with traffic microsimulation model and emission simulator for a holistic analysis of COVID-19 pandemic related changes in traffic flows and emissions. An activity-based travel demand model within iTLE informs pandemic traffic operation scenarios for traffic microsimulation modeling. Link-based simulation outputs inform a finer-grained emission estimation process within a MOtor Vehicle Emission Simulator. Results suggest that the overall network performance improves during lockdown as average delays and queue time decrease by 42.04% and 5.9% respectively compared to pre-COVID condition. Emission results reveal that GHG emissions significantly decrease (64%) in lockdown while it starts increasing gradually in post-pandemic period. Link-based emission analysis indicates that major arterial streets achieve a significant reduction in air pollutant emission. The findings of this study will help transportation planners, engineers, and policymakers to devise effective policies for the improvement of transport operations and emissions.

Native Cerrado vegetation is a haven for birds on the current trajectory of climate change

Resumo A mudanca climatica ja e vista como uma das maiores ameacas a biodiversidade no seculo XXI. Poucos estudos direcionam a atencAo para seus efeitos em comunidades inteiras de hotspots ameacados. Neste trabalho, combinamos a modelagem de nicho climatico (ENM) com um futuro cenario climatico de emissoes de gases de efeito estufa para estudar as futuras mudancas na diversidade alfa e beta das aves do bioma Cerrado brasileiro, um hotspot da biodiversidade com alta velocidade de mudanca climatica e expansAo agricola. Esperavamos que o sul do Cerrado (altamente modificado) apresentasse a maioria das mudancas negativas. Em geral, encontramos resultados heterogeneos para mudancas na riqueza de especies, na diversidade beta taxonomica e funcional espacial e temporal, e na diferenciacAo ecologica media. Analisamos 1301 aves, 1115 Menos Preocupantes, 83 Quase Ameacadas, 63 Vulneraveis, 33 Em Perigo, cinco Criticamente em Perigo e duas Extintas na natureza. Ao contrario de um estudo anterior sobre mamiferos do Cerrado, espera-se que a riqueza de especies aumente no norte do Cerrado, onde a homogeneizacAo das comunidades (diminuicAo da rotatividade espacial) tambem deve ocorrer especialmente atraves de invasoes locais. Mostramos que a homogeneizacAo biotica crescente (similaridade entre as comunidades) ocorrera em dois grupos biologicos, mas atraves de subprocessos diferentes: extincoes locais para mamiferos e invasoes locais para aves. Acoes distintas de manejo da conservacAo devem ser direcionadas dependendo dos resultados das analises de diversidade alfa e beta espacial e temporal, por exemplo, controlando invasoes de especies no norte do Cerrado. Tambem mostramos prioridades em nivel de especies para as aves do Cerrado. Os estudos de conservacAo devem continuar estudando o Cerrado no Brasil mesmo durante a pandemia de covid, pois a situacAo ambiental no pais nAo e boa e os incentivos para estudos cientificos sAo quase inexistentes. Tambem consideramos que o norte do Cerrado poderia ser visto como um refugio potencial para outros grupos de organismos (morcegos, borboletas, sapos etc.). Portanto, e crucial que os tomadores de decisAo tomem medidas ambiciosas de conservacAo.

Accounting for the spatial incidence of working from home in an integrated transport and land model system.

The COVID-19 pandemic has resulted in a seismic shift in the way in which work is conducted. Remote working or working from home is becoming a centrepiece of the next normal with strong support from both employers and employees. With reduced commuting activity associated with an expected 1 to 2 days working from home for many occupations and industries, associated with releasing commuting time to spend on other activities including changed levels and patterns on non-commuting travel, it is necessary, indeed essential, to allow for the incidence of working from home in integrated strategic transport and location model systems. In this paper we show the extent of changes in travel behaviour and the performance of the transport network before and after allowing for working from home, which is more impactful than any new infrastructure project. The differences are significant and suggest that even within the existing modelling frameworks used pre-COVID-19, we need to make adjustments in the modal activity overall and by location. Using the MetroScan platform in the Greater Sydney Metropolitan area, we present a number of outputs to illustrate the significant impacts of working from home such as modal activity (total and shares), emissions, government revenues, and generalised cost of travel.

Coupling Random Forest, Allometric Scaling, and Cellular Automata to Predict the Evolution of LULC under Various Shared Socioeconomic Pathways

Accurately estimating land-use demand is essential for urban models to predict the evolution of urban spatial morphology. Due to the uncertainties inherent in socioeconomic development, the accurate forecasting of urban land-use demand remains a daunting challenge. The present study proposes a modeling framework to determine the scaling relationship between the population and urban area and simulates the spatiotemporal dynamics of land use and land cover (LULC). An allometric scaling (AS) law and a Markov (MK) chain are used to predict variations in LULC. Random forest (RF) and cellular automata (CA) serve to calibrate the transition rules of change in LULC and realize its micro-spatial allocation (MKCA(RF-AS)). Furthermore, this research uses several shared socioeconomic pathways (SSPs) as scenario storylines. The MKCA(RF-AS) model is used to predict changes in LULC under various SSP scenarios in Jinjiang City, China, from 2020 to 2065. The results show that the figure of merit (FoM) and the urban FoM of the MKCA(RF-AS) model improve by 3.72% and 4.06%, respectively, compared with the MKCA(ANN) model during the 2005-2010 simulation period. For a 6.28% discrepancy between the predicted urban land-use demand and the actual urban land-use demand over the period 2005-2010, the urban FoM degrades by 21.42%. The growth of the permanent urban population and urban area in Jinjiang City follows an allometric scaling law with an exponent of 0.933 for the period 2005-2020, and the relative residual and R-2 are 0.0076 and 0.9994, respectively. From 2020 to 2065, the urban land demand estimated by the Markov model is 19.4% greater than the urban area predicted under scenario SSP5. At the township scale, the different SSP scenarios produce significantly different spatial distributions of urban expansion rates. By coupling random forest and allometric scaling, the MKCA(RF-AS) model substantially improves the simulation of urban land use.

A QGIS plugin for BONDS project: integrating field data with geographical, remote sensing and health information

Open source Geographic Information System (GIS) have been fostering spatial data research such as Earth observation and environmental monitoring for more than 30 years. More recently, globally available geospatial information combined with web technologies are providing new environments and tools for data handling. Thus, binding the mapping and processing capabilities of traditional GIS to the accessibility and reliability of web-based data providers can bring new opportunities for research. In this paper, we built a QGIS plugin to explore the integration of different public data providers in Brazil along with field data produced by the BONDS project. The biOdiversity conservatioN with Development in Amazon wetlandS project (BONDS) proposes to develop biodiversity scenarios for the Amazonian floodplains aiming to support solutions to preserve biodiversity and ecosystem services. The use of web services enabled dynamic and fast access to several products ranging from remote sensing images, land use and land cover, territorial cartography, water quality, to COVID-19 health data, and more. © 2022 National Institute for Space Research, INPE. All rights reserved.

Global modeling of the socioeconomic, political, and environmental relations of farmer seed systems (FSS): Spatial analysis and insights for sustainable development

Accessible, high-quality seed is vital to the agricultural, food, and nutrition sovereignty needed for justice-based sustainable development. Multiregion, interdisciplinary research on farmers' seed systems (FSS) can complement case-based and thematic approaches.This study's goals are to (1) provide a synthetic overview of current major FSS concepts;(2) design and evaluate a novel social- and political-ecological model of FSS using globally representative data from mountain agricultural areas of Africa, Asia, and Latin America;(3) model and evaluate FSS relations to socioeconomic, political, and environmental factors including main food crops (rice, wheat, maize, potato, and common bean);(4) generate new spatial, geographic, and demographic estimates;and (5) strengthen FSS for justice-based sustainable development of agriculture, land use, and food systems. The conceptual framework of FSS-related factors guided the global modeling of data from 11 countries in Africa, Asia, and Latin America. A multiple regression model explained FSS utilization (R2 1/4 0.53, P < 0.0001), specifying the significant inverse relations to mean farm area (strong), per-capita Gross Domestic Product at the district level (strong), and urban distance (moderate). FSS showed strong positive relations to aridity and topographic ruggedness. FSS were positively related to elevation in a 5-country Andean subsample. Results estimated FSS utilization by 136 million farmers within the 11 countries. Novel insights to strengthen FSS policies and programs are the importance of FSS to extremely small farm-area subgroups and other distinct FSS stakeholders, global-region geopolitical distinctness of FSS-farm area relations, multidistrict FSS concentrations that enable extralocal FSS spatial connectivity, FSS capacities in climate-change hot spots, and high FSS encompassing periurban areas. Policy-relevant results on global geographic and demographic extensiveness of FSS and key spatial, socioeconomic, political, and environment relations demonstrate that globally FSS are key to supporting agrobiodiversity, agroecology, nutrition, and the sustainability of food systems. These advise strengthening FSS through pro-poor and linked urban-rural policies at regional scales in addition to expanding local initiatives.

Planning and the Post-Pandemic City

The Covid-19 pandemic has left society dazed and confused. Self-evidently momentous, its multifaceted impacts upon the functioning and experience of city living have been swift and deep. This has precipitated a range of laudable research in planning, which, among other foci, has sought to examine how the disruption is amplifying inequities (Cole et al., Citation2020), improving urban environmental quality (Sharifi & Khavarian-Garmsir, Citation2020) and generating enhanced demand for public space (Sepe, Citation2021;Ugolini et al., Citation2020). The pandemic has also heightened interest in re-engaging planning with its roots in public health (Lennon, Citation2020;Scott, Citation2020). Here, an emerging strand of research is exploring how to better proof our cities from the ill-effects of future contagions (Bereitschaft & Scheller, Citation2020;Martínez & Short, Citation2021). Yet, there is another dimension to the pandemic that may have impacts which shake the very foundations of how we think cities could and should evolve. This results from the current great experiment in spatial reorganisation that stretches well beyond the requirement of social distancing. Specifically, never before in a time of peace have so many peoples' lives been so comprehensively decoupled from their places of work for such an extensive period of time. Indeed, while the effects of social distancing are immediately apparent in how we have found new ways to negotiate spaces, it is perhaps remote working that will have the longest impact on our cities. This was alluded to but not elaborated on in a recent superb editorial by Jill Grant in this journal (Grant, Citation2020). Hence, I propose in this short comment piece to extend this line of speculation.For centuries cities have pulled people into their orbit in search of employment, education and new experiences. Conventionally conceived as places of opportunity, cities are seen to thrive where a critical threshold of population and capital spawn dynamic and diverse economies and cultures, in which residents flourish in choice and convenience. Yet despite such lofty descriptions, for most cities it is employment that is the magnet and motor of urban land use that heavily influences where people live, shop and recreate. These two cardinal poles of home and work have long dictated how people flow around and use urban spaces: from school runs to restaurants;from retail to recreation. It is this spatial relationship embedded in the daily patterns of life that helps create and carry communities. But if people are no longer limited by their place or time of work, will it follow that they will choose to lumber themselves with the outsized mortgages, additional expenses and stresses of urban living?

The effects of COVID-19 on downtown land use: Evidence from four U.S. cities

This paper investigates trends in downtown real estate and urban responses to real estate demand shifts during the COVID and post-COVID recovery periods for a selection of U.S. downtown areas. It charts the diverging responses of different real estate sectors to the COVID-19 pandemic—and the implications for the spatial allocation of activity across metropolitan areas. Using local data from four major U.S. metro areas, it documents how sustained shifts in rents and vacancy rates are putting pressure on cities to reconsider—and in some cases redefine—the "highest and best use” of much of their downtown real estate assets. After analyzing economic and policy constraints that are hindering responses, it concludes by proposing strategies for how the downtown real estate sector can adapt to the shifting needs of the post-pandemic population. [ FROM AUTHOR] Copyright of Journal of Urban Affairs is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Sustainability assessment of crops' production in India: empirical evidence from ARDL-ECM approach

PurposeThe study aims to evaluate the long- vs short-run relationships between crops' production (output) and crops' significant inputs such as land use, agricultural water use (AWU) and gross irrigated area in India during the period 1981–2018.Design/methodology/approachThe study applied the autoregressive distributed lag (ARDL) bounds testing approach to estimate the co-integration among the variables. The study uses the error correction model (ECM), which integrates the short-run dynamics with the long-run equilibrium.FindingsThe ARDL bounds test of co-integration confirms the strong evidence of the long-run relationship among the variables. Empirical results show the positive and significant relationship of crops' production with land use and gross irrigated area. The statistically significant error correction term (ECT) validates the speed of adjustment of the empirical models in the long-run.Research limitations/implicationsThe study suggests that the decision-makers must understand potential trade-offs between human needs and environmental impacts to ensure food for the growing population in India.Originality/valueFor a clear insight into the impact of climate change on crops' production, the current study incorporates the climate variables such as annual rainfall, maximum temperature and minimum temperature. Further, the study considered agro-chemicals, i.e. fertilizers and pesticides, concerning their negative impacts on increased agricultural production and the environment.

Preface

International Conference on Geospatial Science for Digital Earth Observation (GSDEO 2021)The international conference on "Geospatial Science for Digital Earth Observation” (GSDEO) 2021 was successfully held on a virtual platform of Zoom on March 26th and 27th, 2021. The conference was jointly organized by the Indian Society of Remote Sensing (ISRS), Kolkata chapter, and the Department of Geography, School of Basic and Applied Sciences, Adamas University. Due to the non-predictable behaviour of the COVID-19 second wave, which imposed restrictions on organizing offline events, the GSDEO (2021) organizing committee decided to organize the conference online, instead of postponing the event.Remotely sensed data and geographic information systems have been increasingly used together for a vast range of applications, which include land use/land cover mapping, water resource management, weather forecasting, environmental monitoring, agriculture, disaster management, etc. Currently, intensive research is being carried out using remotely sensed data on the geoinformatics platform. New developments have led to dynamic advances in recent years. The objective of the international conference on Geospatial Science for Digital Earth Observation (GSDEO 2021) was to bring the scientists, academicians, and researchers, in the field of geo-environmental sciences on a common platform to exchange ideas and their recent findings related to the latest advances and applications of geospatial science. The call for papers received an enthusiastic response from the academic community, and over 100+ participants from 50+ colleges, universities, and institutions participated in the conference. In total 50+ research papers had been presented through the virtual Zoom conference platform in GSDEO 2021.The conference witnessed the presentation of research papers from diverse applied fields of geospatial sciences, which include the application of geoinformatics in geomorphology, hydrology, urban science, land use planning, climate, and environmental studies. There were four sessions namely, TS 1: Geomorphology and Hydrology, TS 2: Urban Science, TS 3: Social Sustainability and Land Use Planning, and TS 4: Climate and Environment. Each session was further subdivided, into two parts, namely Technical Session 1-A and 1-B. Each sub-session had been designed with one keynote speech and 5 oral presentations. Oral sessions were organized in two parts and offered through live and pre-recorded components based on the preference of the presenters. The presentation session was followed by a live Q&A session. The session chairs moderated the discussions. Similarly, poster sessions were organized in three parts and offered e-poster, live, and pre-recorded components. The best presenter of each sub-session received the best paper award.Dr. Prithvish Nag, Ex-Director of NATMO & Ex Surveyor General of India delivered the inaugural speech, and Dr. P. Chakrabarti, Former Chief Scientist of the DST&B, Govt. of West Bengal delivered a special lecture after the inaugural session. Eight eminent keynote speakers, Prof. S.P. Agarwal from the Indian Institute of Remote Sensing, Prof. Ashis Kumar Paul from Vidyasagar University, Prof. Soumya Kanti Ghosh from the Indian Institute of Technology, Kharagpur, Prof. L. N. Satpati from the University of Calcutta, Prof. R.B. Singh from the University of Delhi, Dr. A.K. Raha, IFS (Retd), Prof. Gerald Mills from the University College Dublin and Prof. Sugata Hazra from Jadavpur University enriched the knowledge of participants in the field of geoinformatics by their informative lectures. The presentations and discussions widely covered the various spectrums of geoinformatics and its application in monitoring natural resources like vegetation mapping, agricultural resource monitoring, forest health assessment, water, and ocean resource management, disaster management, land resource management, water and climate studies, drought vulnerability assessment, groundwater quality monitoring, accretion mapping and the use of geospatial sci nce in studying morphological, hydrological, and other biophysical characteristics of a region etc. Application of geoinformatics in predicting urban expansion, urban climate, disaster management, healthcare accessibility, anthropogenic resource monitoring, spatial-interaction mapping, and, sustainable regional planning were well-discussed topics of the conference.List of Committees, photos are available in the pdf.

Untangling the Integral Impact of Land Use Change, Economic, Ecological and Social Factors on the Development of Burabay District (Kazakhstan) during the Period 1999–2021

Long-term spatiotemporal Land Use and Land Cover (LULC) analysis is an objective tool for assessing patterns of sustainable development (SD). The basic purpose of this research is to define the Driving Mechanisms (DM) and assess the trend of SD in the Burabay district (Kazakhstan), which includes a city, an agro-industrial complex, and a national natural park, based on the integrated use of spatiotemporal data (STD), economic, environmental, and social (EES) indicators. The research was performed on the GEE platform using Landsat and Random Forest. The DM were studied by Multiple Linear Regression and Principal Component Analysis. SD trend was assessed through sequential transformations, aggregations, and integrations of 36 original STD and EES indicators. The overall classification accuracy was 0.85–0.97. Over the past 23 years, pasture area has changed the most (−16.69%), followed by arable land (+14.72%), forest area increased slightly (+1.81%), and built-up land—only +0.16%. The DM of development of the AOI are mainly economic components. There has been a noticeable drop in the development growth of the study area in 2021, which is apparently a consequence of the COVID-19. The upshots of the research can serve as a foundation for evaluating SD and LULC policy.

Pedestrians and the Built Environment during the COVID-19 Pandemic: Changing Relationships by the Pandemic Phases in Salt Lake County, Utah, U.S.A.

The COVID-19 pandemic has dramatically altered people's travel behavior, in particular outdoor activities, including walking. Their behavior changes may have prolonged effects after the pandemic, and such changes vary by the context and are related to the characteristics of the built environment. But empirical studies about the relationships between pedestrians and the built environment during the pandemic are lacking. This study explores how COVID-19 and related travel restrictions have affected the relationship between pedestrian traffic volume and the built environment. We estimate daily pedestrian volumes for all signalized intersections in Salt Lake County, Utah, U.S.A., from pedestrian push-button log data between January 2019 and October 2020. Multilevel spatial filtering models show that the COVID-19 pandemic has altered the relationship between pedestrian traffic volume and the built environment. During the pandemic, the higher the number of COVID-19 cases, the less (or more negative) the effects of density, street connectivity, and destination accessibility on pedestrian volume being observed. The exception is access to urban parks, as it became more significant in increasing pedestrian activities during the pandemic. The models also highlight the negative impacts of the pandemic in economically disadvantaged areas. Our findings could help urban and transportation planners find effective interventions to promote active transportation and physical activity amid the global pandemic.

Spatio-temporal analysis of COVID-19 incidence rate using GIS: a case study-Tehran metropolitan, Iran.

COVID-19 has been distinguished as a zoonotic coronavirus, like SARS coronavirus and MERS coronavirus. Tehran metropolis, as the capital of Iran, has a high density of residents that experienced a high incidence and mortality rates which daily increase the number of death and cases. In this study, the IDW (Inverse Distance Weight), Hotspots, and GWR (Geography Weighted Regression) Model are used as methods for analyzing big data COVID-19 in Tehran. The results showed that the majority of patients and deaths were men, but the death rate was higher in women than in men; also was observed a direct relationship between the area of the houses, and the infected rate, to COVID-19. Also, the results showed a disproportionate distribution of patients in Tehran, although in the eastern regions the number of infected people is higher than in other districts; the eastern areas have a high population density as well as residential land use, and there is a high relationship between population density in residential districts and administrative-commercial and the number of COVID-19 cases in all regions. The outputs of local R2 were interesting among patients and underlying disorders; the local R2 between hypertension and neurological diseases was 0.91 and 0.79, respectively, which was higher than other disorders. The highest rates of local R2 for diabetes and heart disease were 0.67 and 0.55, respectively. From this study, it can be concluded the restrictions must be considered especially, in areas densely populated for all people.

Changeability of transport behaviour in a large city from the perspective of working days and Sundays: The case of Lodz, Poland

The transport behaviour of Lodz residents with a view to constructing a balanced traffic model to include both private and public transport is examined in this paper. A survey was conducted among 6,000 Lodz citizens using mixed-mode techniques: CAWI and CATI: respondents were asked to complete a travel log for the previous day and the previous Sunday. This served as a basis for further analyses, performed with PTV simulation software, following a four-step model. The main results of the study are presented, including the mobility rate of Lodz residents, the motivations and duration of journeys, and the division of transport tasks into workdays and Sundays, indicating that a higher private carload is typical for home-other and other-home trips on Sundays compared to working days. The number of home to work and work-home trips via private cars is higher for working days compared to Sundays. Furthermore, the simulated traffic load of the public transport system is much higher for working days compared to Sundays. A higher percentage of non-motorised trips and longer trip duration are found to be common for Sundays as well.