Understanding the influencing factors and the evolving trends of the Water-Sediment Regulation System(WSRS)is vital for the protection and management of the Yellow River.Past studies on WSRS have been limited in focus...Understanding the influencing factors and the evolving trends of the Water-Sediment Regulation System(WSRS)is vital for the protection and management of the Yellow River.Past studies on WSRS have been limited in focus and have not fully addressed the complete engineering control system of the basin.This study takes a holistic view,treating sediment management in the Yellow River as a dynamic and ever-evolving complex system.It merges concepts from system science,information theory,and dissipative structure with practical efforts in sediment engineering control.The key findings of this study are as follows:between 1990 and 2019,the average Yellow River Sediment Regulation Index(YSRI)was 55.99,with the lowest being 50.26 in 1990 and the highest being 61.48 in 2019;the result indicates that the WSRS activity decreased,yet it fluctuated,gradually approaching the critical threshold of a dissipative structure.展开更多
Predicting trip purpose from comprehensive and continuous smart card data is beneficial for transport and city planners in investigating travel behaviors and urban mobility.Here,we propose a framework,ActivityNET,usin...Predicting trip purpose from comprehensive and continuous smart card data is beneficial for transport and city planners in investigating travel behaviors and urban mobility.Here,we propose a framework,ActivityNET,using Machine Learning(ML)algorithms to predict passengers’trip purpose from Smart Card(SC)data and Points-of-Interest(POIs)data.The feasibility of the framework is demonstrated in two phases.Phase I focuses on extracting activities from individuals’daily travel patterns from smart card data and combining them with POIs using the proposed“activity-POIs consolidation algorithm”.Phase II feeds the extracted features into an Artificial Neural Network(ANN)with multiple scenarios and predicts trip purpose under primary activities(home and work)and secondary activities(entertainment,eating,shopping,child drop-offs/pick-ups and part-time work)with high accuracy.As a case study,the proposed ActivityNET framework is applied in Greater London and illustrates a robust competence to predict trip purpose.The promising outcomes demonstrate that the cost-effective framework offers high predictive accuracy and valuable insights into transport planning.展开更多
The coronavirus pandemic that started in 2019 has had wide-ranging impacts on many aspects of people’s daily lives.At the peak of the outbreak,lockdown measures and social distancing changed the ways in which cities ...The coronavirus pandemic that started in 2019 has had wide-ranging impacts on many aspects of people’s daily lives.At the peak of the outbreak,lockdown measures and social distancing changed the ways in which cities function.In particular,they had profound impacts on urban transportation systems,with public transport being shut down in many cities.Bike share systems(BSS)were widely reported as having experienced an increase in demand during the early stages of the pandemic before returning to pre-pandemic levels.However,the studies published to date focus mainly on the first year of the pandemic,when various waves saw continual relaxing and reintroductions of restrictions.Therefore,they fall short of exploring the role of BSS as we move to the post-pandemic period.To address this gap,this study uses origin-destination(O-D)flow data from London’s Santander Cycle Hire Scheme from 2019-2021 to analyze the changing use of BSS throughout the first two years of the pandemic,from lockdown to recovery.A Gaussian mixture model(GMM)is used to cluster 2019 BSS trips into three distinct clusters based on their duration and distance.The clusters are used as a reference from which to measure spatial and temporal change in 2020 and 2021.In agreement with previous research,BSS usage was found to have declined by nearly 30%during the first lockdown.Usage then saw a sharp increase as restrictions were lifted,characterized by longer,less direct trips throughout the afternoon rather than typical peak commuting trips.Although the aggregate number of BSS trips appeared to return to normal by October 2020,this was against the backdrop of continuing restrictions on international travel and work from home orders.The period between July and December 2021 was the first period that all government restrictions were lifted.During this time,BSS trips reached higher levels than in 2019.Spatio-temporal analysis indicates a shift away from the traditional morning and evening peak to a more diffuse pattern of working hours.The results indicate that the pandemic may have had sustained impacts on travel behavior,leading to a“new normal”that reflects different ways of working.展开更多
1.Introduction The COVID-19 pandemic has dramatically reshaped human mobility at global,national,regional,and individual levels,as evidenced by many studies(Chang et al.2021;Cheng et al.2022;Chinazzi et al.2020;Hou et...1.Introduction The COVID-19 pandemic has dramatically reshaped human mobility at global,national,regional,and individual levels,as evidenced by many studies(Chang et al.2021;Cheng et al.2022;Chinazzi et al.2020;Hou et al.2021;Santana et al.2023;Xiong et al.2020).Governments around the world have implemented containment measures such as lockdowns,travel restrictions,border closures,public transport reductions,and self-isolation for vulnerable groups.These interventions have led to effects that vary by location,timing,travel modes,and demographic characteristics.展开更多
基金supported by The National Key Research and Development Program of China(2023YFC3208605).
文摘Understanding the influencing factors and the evolving trends of the Water-Sediment Regulation System(WSRS)is vital for the protection and management of the Yellow River.Past studies on WSRS have been limited in focus and have not fully addressed the complete engineering control system of the basin.This study takes a holistic view,treating sediment management in the Yellow River as a dynamic and ever-evolving complex system.It merges concepts from system science,information theory,and dissipative structure with practical efforts in sediment engineering control.The key findings of this study are as follows:between 1990 and 2019,the average Yellow River Sediment Regulation Index(YSRI)was 55.99,with the lowest being 50.26 in 1990 and the highest being 61.48 in 2019;the result indicates that the WSRS activity decreased,yet it fluctuated,gradually approaching the critical threshold of a dissipative structure.
基金This work is part of the Consumer Data Research Centre project(ES/L011840/1)funded by the UK Economic and Social Research Council(grant number 1477365).
文摘Predicting trip purpose from comprehensive and continuous smart card data is beneficial for transport and city planners in investigating travel behaviors and urban mobility.Here,we propose a framework,ActivityNET,using Machine Learning(ML)algorithms to predict passengers’trip purpose from Smart Card(SC)data and Points-of-Interest(POIs)data.The feasibility of the framework is demonstrated in two phases.Phase I focuses on extracting activities from individuals’daily travel patterns from smart card data and combining them with POIs using the proposed“activity-POIs consolidation algorithm”.Phase II feeds the extracted features into an Artificial Neural Network(ANN)with multiple scenarios and predicts trip purpose under primary activities(home and work)and secondary activities(entertainment,eating,shopping,child drop-offs/pick-ups and part-time work)with high accuracy.As a case study,the proposed ActivityNET framework is applied in Greater London and illustrates a robust competence to predict trip purpose.The promising outcomes demonstrate that the cost-effective framework offers high predictive accuracy and valuable insights into transport planning.
文摘The coronavirus pandemic that started in 2019 has had wide-ranging impacts on many aspects of people’s daily lives.At the peak of the outbreak,lockdown measures and social distancing changed the ways in which cities function.In particular,they had profound impacts on urban transportation systems,with public transport being shut down in many cities.Bike share systems(BSS)were widely reported as having experienced an increase in demand during the early stages of the pandemic before returning to pre-pandemic levels.However,the studies published to date focus mainly on the first year of the pandemic,when various waves saw continual relaxing and reintroductions of restrictions.Therefore,they fall short of exploring the role of BSS as we move to the post-pandemic period.To address this gap,this study uses origin-destination(O-D)flow data from London’s Santander Cycle Hire Scheme from 2019-2021 to analyze the changing use of BSS throughout the first two years of the pandemic,from lockdown to recovery.A Gaussian mixture model(GMM)is used to cluster 2019 BSS trips into three distinct clusters based on their duration and distance.The clusters are used as a reference from which to measure spatial and temporal change in 2020 and 2021.In agreement with previous research,BSS usage was found to have declined by nearly 30%during the first lockdown.Usage then saw a sharp increase as restrictions were lifted,characterized by longer,less direct trips throughout the afternoon rather than typical peak commuting trips.Although the aggregate number of BSS trips appeared to return to normal by October 2020,this was against the backdrop of continuing restrictions on international travel and work from home orders.The period between July and December 2021 was the first period that all government restrictions were lifted.During this time,BSS trips reached higher levels than in 2019.Spatio-temporal analysis indicates a shift away from the traditional morning and evening peak to a more diffuse pattern of working hours.The results indicate that the pandemic may have had sustained impacts on travel behavior,leading to a“new normal”that reflects different ways of working.
基金supported by the Economic and Social Research Council[ES/L011840/1]Medical Research Council[MR/V028375/1].
文摘1.Introduction The COVID-19 pandemic has dramatically reshaped human mobility at global,national,regional,and individual levels,as evidenced by many studies(Chang et al.2021;Cheng et al.2022;Chinazzi et al.2020;Hou et al.2021;Santana et al.2023;Xiong et al.2020).Governments around the world have implemented containment measures such as lockdowns,travel restrictions,border closures,public transport reductions,and self-isolation for vulnerable groups.These interventions have led to effects that vary by location,timing,travel modes,and demographic characteristics.
