Debayan Mandal,Lei Zou,Abhinav Wadhwa et al.
Debayan Mandal et al.
Communities worldwide increasingly confront flood hazards intensified by climate change, urban expansion, and environmental degradation. Addressing these challenges requires real-time flood analysis, precise flood forecasting, and robust ri...
Physics-Informed Graph Learning for Spatially Contiguous and Capacity-Constrained Hospital Service Area Delineation [0.03%]
基于物理信息的图学习在空间连续且容量受限的医院服务区划分中的应用
Lingbo Liu,Fahui Wang
Lingbo Liu
Delineating Hospital Service Areas (HSAs) is critical for healthcare resource allocation and policymaking. However, existing methods struggle to simultaneously capture patient flow patterns, spatial contiguity, and multiple capacity constra...
Shiran Zhong,Ling Bian
Shiran Zhong
It is often believed that regularities are embedded in mobile behaviors. Highly regular mobile behaviors, such as daily commutes between home and workplace, have been actively investigated in the context of health risks. Less regular mobile...
Causal effects of mobility intervention policies on intracity flows during the COVID-19 pandemic: The moderating role of zonal locations in the transportation networks [0.03%]
新冠肺炎疫情期间城市交通网络分区位置对出行限制政策影响人际接触的调节效应研究
Caicheng Niu,Wenjia Zhang
Caicheng Niu
Many studies have investigated the impact of mobility restriction policies on the change of intercity flows during the outbreak of COVID-19, whereas only a few have highlighted intracity flows. By using the mobile phone trajectory data of a...
Information propagation on cyber, relational and physical spaces about covid-19 vaccine: Using social media and splatial framework [0.03%]
关于新冠疫苗的网络、社会关系和物理空间的信息传播：使用社交媒体和空间框架
Fuzhen Yin,Andrew Crooks,Li Yin
Fuzhen Yin
With the advent of social media, human dynamics studied in purely physical space have been extended to that of a cyber and relational context. However, connections and interactions between these hybrid spaces have not been sufficiently inve...
Imputation of missing time-activity data with long-term gaps: A multi-scale residual CNN-LSTM network model [0.03%]
具有长期缺口的缺失时间活动数据补全：多尺度残差CNN-LSTM网络模型
Youngseob Eum,Eun-Hye Yoo
Youngseob Eum
Despite the increasing availability and spatial granularity of individuals' time-activity (TA) data, the missing data problem, particularly long-term gaps, remains as a major limitation of TA data as a primary source of human mobility studi...
Structural changes in intercity mobility networks of China during the COVID-19 outbreak: A weighted stochastic block modeling analysis [0.03%]
加权随机块模型分析我国疫情期间城际出行网络的变化
Wenjia Zhang,Zhaoya Gong,Caicheng Niu et al.
Wenjia Zhang et al.
This study focuses on a mesoscale perspective to examine the structural and spatial changes in the intercity mobility networks of China from three phases of before, during and after the Wuhan lockdown due to the outbreak of COVID-19. Taking...
Towards the automated large-scale reconstruction of past road networks from historical maps [0.03%]
基于历史地图的大规模道路网络自动重建研究
Johannes H Uhl,Stefan Leyk,Yao-Yi Chiang et al.
Johannes H Uhl et al.
Transportation infrastructure, such as road or railroad networks, represent a fundamental component of our civilization. For sustainable planning and informed decision making, a thorough understanding of the long-term evolution of transport...
Economic and technical assessment of rooftop solar photovoltaic potential in Brownsville, Texas, U.S.A [0.03%]
美国德克萨斯州布朗斯维尔市屋顶太阳能光伏潜力的经济与技术评估
Michael J Mangiante,Pai-Yei Whung,Luxi Zhou et al.
Michael J Mangiante et al.
Localized assessment of solar energy economic feasibility will benefit the structuring of residential solar energy deployment globally. In the U.S. growing interest in rooftop residential solar among city managers has spurred the developmen...
Early warning of COVID-19 hotspots using human mobility and web search query data [0.03%]
基于人类移动性和网络搜索查询数据的新冠肺炎疫情预警系统研究
Takahiro Yabe,Kota Tsubouchi,Yoshihide Sekimoto et al.
Takahiro Yabe et al.
COVID-19 has disrupted the global economy and well-being of people at an unprecedented scale and magnitude. To contain the disease, an effective early warning system that predicts the locations of outbreaks is of crucial importance. Studies...