Computational urban science最新文献

{"title":"How do taxi usage patterns vary and why? A dynamic spatiotemporal analysis in Beijing","authors":"Jiaoe Wang, Fangye Du, Jie Huang, Yu Liu","doi":"10.1007/s43762-023-00087-w","DOIUrl":"https://doi.org/10.1007/s43762-023-00087-w","url":null,"abstract":"","PeriodicalId":72667,"journal":{"name":"Computational urban science","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42583265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Are older adults living in compact development more active? – Evidence from 36 diverse regions of the United States","authors":"Guang Tian, Hannaneh Abdollahzadeh Kalantari, R. Ewing","doi":"10.1007/s43762-023-00086-x","DOIUrl":"https://doi.org/10.1007/s43762-023-00086-x","url":null,"abstract":"","PeriodicalId":72667,"journal":{"name":"Computational urban science","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42937272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Delay in timing and spatial reorganization of rainfall due to urbanization- analysis over India’s smart city Bhubaneswar","authors":"M. Swain, Raghavendra Raju Nadimpalli, U. C. Mohanty, P. Guhathakurta, Akhilesh Gupta, A. Kaginalkar, Fei Chen, D. Niyogi","doi":"10.1007/s43762-023-00081-2","DOIUrl":"https://doi.org/10.1007/s43762-023-00081-2","url":null,"abstract":"","PeriodicalId":72667,"journal":{"name":"Computational urban science","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42082503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Out-of-school hours care places in Xi’an City of China: location choice, spatial relationships, and influencing factors","authors":"Meiling Zhong, Gang Li, Yue Yu, Lanqing Xu, Qifan Nie, Zhuo Yang","doi":"10.1007/s43762-023-00084-z","DOIUrl":"https://doi.org/10.1007/s43762-023-00084-z","url":null,"abstract":"","PeriodicalId":72667,"journal":{"name":"Computational urban science","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42732495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding Policy and Technical Aspects of AI-enabled Smart Video Surveillance to Address Public Safety","authors":"B. R. Ardabili, Armin Danesh Pazho, Ghazal Alinezhad Noghre, Christopher Neff, Sai Datta Bhaskararayuni, Arun K. Ravindran, Shannon Reid, Hamed Tabkhi","doi":"10.1007/s43762-023-00097-8","DOIUrl":"https://doi.org/10.1007/s43762-023-00097-8","url":null,"abstract":"","PeriodicalId":72667,"journal":{"name":"Computational urban science","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48124187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impacts of land cover spatial combination on nighttime light intensity in 2010 and 2020: a case study of Fuzhou, China","authors":"Yongxin Yuan, Zuoqi Chen","doi":"10.1007/s43762-023-00077-y","DOIUrl":"https://doi.org/10.1007/s43762-023-00077-y","url":null,"abstract":"","PeriodicalId":72667,"journal":{"name":"Computational urban science","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41683002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Need for considering urban climate change factors on stroke, neurodegenerative diseases, and mood disorders studies","authors":"Kushagra Tewari, M. Tewari, D. Niyogi","doi":"10.1007/s43762-023-00079-w","DOIUrl":"https://doi.org/10.1007/s43762-023-00079-w","url":null,"abstract":"","PeriodicalId":72667,"journal":{"name":"Computational urban science","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42297780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Urban modification of heavy rainfall: a model case study for Bhubaneswar urban region","authors":"M. Swain, R. Nadimpalli, A. Das, U. Mohanty, D. Niyogi","doi":"10.1007/s43762-023-00080-3","DOIUrl":"https://doi.org/10.1007/s43762-023-00080-3","url":null,"abstract":"","PeriodicalId":72667,"journal":{"name":"Computational urban science","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47815112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial analysis and optimization of self-pickup points of a new retail model in the Post-Epidemic Era: the case of Community-Group-Buying in Xi'an City.","authors":"Zhe Lin,&nbsp;Gang Li,&nbsp;Muhammad Sajid Mehmood,&nbsp;Qifan Nie,&nbsp;Ziwan Zheng","doi":"10.1007/s43762-023-00089-8","DOIUrl":"https://doi.org/10.1007/s43762-023-00089-8","url":null,"abstract":"<p><p>The Community-Group-Buying Points (CGBPs) flourished during COVID-19, safeguarding the daily lives of community residents in community lockdowns, and continuing to serve as a popular daily shopping channel in the Post-Epidemic Era with its advantages of low price, convenience and neighborhood trust. These CGBPs are allocated on location preferences however spatial distribution is not equal. Therefore, in this study, we used point of interest (POI) data of 2,433 CGBPs to analyze spatial distribution, operation mode and accessibility of CGBPs in Xi'an city, China as well as proposed the location optimization model. The results showed that the CGBPs were spatially distributed as clusters at α = 0.01 (<i>Moran's I</i> = 0.44). The CGBPs operation mode was divided into preparation, marketing, transportation, and self-pickup. Further CGBPs were mainly operating in the form of joint ventures, and the relying targets presented the characteristic of 'convenience store-based and multi-type coexistence'. Influenced by urban planning, land use, and cultural relics protection regulations, they showed an elliptic distribution pattern with a small oblateness, and the density showed a low-high-low circular distribution pattern from the Palace of Tang Dynasty outwards. Furthermore, the number of communities, population density, GDP, and housing type were important driving factors of the spatial pattern of CGBPs. Finally, to maximize attendance, it was suggested to add 248 new CGBPs, retain 394 existing CGBPs, and replace the remaining CGBPs with farmers' markets, mobile vendors, and supermarkets. The findings of this study would be beneficial to CGB companies in increasing the efficiency of self-pick-up facilities, to city planners in improving urban community-life cycle planning, and to policymakers in formulating relevant policies to balance the interests of stakeholders: CGB enterprises, residents, and vendors.</p>","PeriodicalId":72667,"journal":{"name":"Computational urban science","volume":"3 1","pages":"13"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10025067/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9246466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of a composite regional vulnerability index and its relationship with the impacts of the COVID-19 pandemic.","authors":"Mengqiu Cao,&nbsp;Qing Yao,&nbsp;Bingsheng Chen,&nbsp;Yantao Ling,&nbsp;Yuping Hu,&nbsp;Guangxi Xu","doi":"10.1007/s43762-023-00078-x","DOIUrl":"https://doi.org/10.1007/s43762-023-00078-x","url":null,"abstract":"<p><p>The interactions between vulnerability and human activities have largely been regarded in terms of the level of risk they pose, both internally and externally, for certain groups of disadvantaged individuals and regions/areas. However, to date, very few studies have attempted to develop a comprehensive composite regional vulnerability index, in relation to travel, housing, and social deprivation, which can be used to measure vulnerability at an aggregated level in the social sciences. Therefore, this research aims to develop a composite regional vulnerability index with which to examine the combined issues of travel, housing and socio-economic vulnerability (THASV index). It also explores the index's relationship with the impacts of the COVID-19 pandemic, reflecting both social and spatial inequality, using Greater London as a case study, with data analysed at the level of Middle Layer Super Output Areas (MSOAs). The findings show that most of the areas with high levels of composite vulnerability are distributed in Outer London, particularly in suburban areas. In addition, it is also found that there is a spatial correlation between the THASV index and the risk of COVID-19 deaths, which further exacerbates the potential implications of social deprivation and spatial inequality. Moreover, the results of the multiscale geographically weighted regression (MGWR) show that the travel and socio-economic indicators in a neighbouring district and the related vulnerability indices are strongly associated with the risk of dying from COVID-19. In terms of policy implications, the findings can be used to inform sustainable city planning and urban development strategies designed to resolve urban socio-spatial inequalities and the potential related impacts of COVID-19, as well as guiding future policy evaluation of urban structural patterns in relation to vulnerable areas.</p>","PeriodicalId":72667,"journal":{"name":"Computational urban science","volume":"3 1","pages":"1"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9841137/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9132371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}