检索结果-南通市图书馆

A spatiotemporal analysis of the impact of lockdown and coronavirus on London’s bicycle hire scheme:from response to recovery to a new normal

引用

Geo-Spatial Information Science 2023年第4期26卷 664-684页

作者： Xiaowei Gao Huanfa Chen james haworth SpaceTimelab Department of CivilEnvironmental and Geomatic EngineeringUniversity College LondonLondonUnited Kingdom Centre for Advanced Spatial Analysis University College LondonLondonUnited Kingdom

The coronavirus pandemic that started in 2019 has had wide-ranging impacts on many aspects of people’s daily *** the peak of the outbreak,lockdown measures and social distancing changed the ways in which cities *** particular,they had profound impacts on urban transportation systems,with public transport being shut down in many *** 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 ***,the studies published to date focus mainly on the first year of the pandemic,when various waves saw continual relaxing and reintroductions of ***,they fall short of exploring the role of BSS as we move to the post-pandemic *** 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 *** clusters are used as a reference from which to measure spatial and temporal change in 2020 and *** agreement with previous research,BSS usage was found to have declined by nearly 30%during the first *** then saw a sharp increase as restrictions were lifted,characterized by longer,less direct trips throughout the afternoon rather than typical peak commuting *** 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 *** period between July and December 2021 was the first period that all government restrictions were *** this time,BSS trips reached higher levels than in ***-temporal analysis indicates a shift away from the traditional morning and evening peak to a more diffuse p

关键词： COVID-19 micro-mobility restrictive measures bicycle share system

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

基于网络和图的时空智能——概念、方法和应用

引用

测绘学报 2022年第7期51卷 1629-1639页

作者：程涛张洋 james haworth 伦敦大学学院土木环境及测绘工程系时空实验室英国伦敦WC1E 6BT

当前时空智能(SpaceTimeAI)和地理空间智能(GeoAI)已是热门的话题,该研究领域旨在将计算机科学的最新方法(如深度学习)应用于地理空间问题。虽然深度学习方法因其对栅格数据的自然适用性而在图像处理中取得了巨大成功,但仍未广泛应用于... 详细信息

当前时空智能(SpaceTimeAI)和地理空间智能(GeoAI)已是热门的话题,该研究领域旨在将计算机科学的最新方法(如深度学习)应用于地理空间问题。虽然深度学习方法因其对栅格数据的自然适用性而在图像处理中取得了巨大成功,但仍未广泛应用于其他空间和时空数据类型。本文提出使用网络和图作为SpaceTimeAI或GeoAI的基本结构的倡议,并将其应用于城市研究中。相比于基于网格的表达,基于网络的结构更加精确和实用。图能实现对点、线、面/多边形/网格和网络等多种空间结构的表达。本文通过时空预测、聚类和时空优化等常用时空分析方法展示基于网络和图的时空智能分析的优势,并介绍其在交通出行、警务和公共卫生等领域的应用。

关键词：时空智能地理空间智能网络图深度学习时空预测

来源：

维普期刊数据库

同方期刊数据库博看期刊评论

在线全文

学校读者我要写书评

暂无评论

Network SpaceTime AI:Concepts,Methods and Applications

引用

Journal of Geodesy and Geoinformation Science 2022年第3期5卷 78-92页

作者： Tao CHENG Yang ZHANG james haworth SpaceTimeLab Department of CivilEnvironmental and Geomatic EngineeringUniversity College LondonLondon WC1E 6BTUK

SpacetimeAI and GeoAI are currently hot topics,applying the latest algorithms in computer science,such as deep learning,to spatiotemporal *** deep learning algorithms have been successfully applied to raster data due to their natural applicability to image processing,their applications in other spatial and space-time data types are still *** paper sets up the proposition of using a network(&graph)-based framework as a generic spatial structure to present space-time processes that are usually represented by the points,polylines,and *** illustrate network and graph-based SpaceTimeAI,from graph-based deep learning for prediction,to space-time clustering and *** applications demonstrate the advantages of network(graph)-based SpacetimeAI in the fields of transport&mobility,crime&policing,and public health.

关键词： spatiotemporal intelligence network graph deep learning spatiotemporal prediction spatiotemporal clustering spatiotemporal optimization

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：