Mapping COVID-19 in Space and Time: Understanding the Spatial and Temporal Dynamics of a Global Pandemic

Preface: Michael Goodchild.- Chapter 1: Understanding the spatial and temporal dynamics of a global pandemic: Shih-Lung Shaw, Daniel Sui.- Section 1: Conceptual and Theoretical Perspectives: Chapter 2: A Power-Law-Based Approach to Mapping COVID-19 Cases in the United States: Bin Jiang and Chris de Rijke.- Chapter 3: Individual, context, and space: Using spatial approaches for understanding unequal social and psychological fallout of COVID-19: Grant Drawve, Casey Harris, and Kevin Fitzpatrick.- Chapter 4: An encrypted monument in the COVID-19 pandemic: A case study of crypto place on the blockchain: Xu Huang and Bo Zhao.- Chapter 5: Emotional responses through COVID-19 in Singapore: Yingwei Yan, Wei Chien Benny Chin, Chan-Hoong Leong, Yi-Chen Wang, and Chen-Chieh Feng.- Chapter 6: A socio-ecological perspective on COVID-19 spatiotemporal integrated vulnerability in Singapore: Chan-Hoong Leong, Benny Wei-Chien Chin, Yi-Chen Wang, and Chen-Chieh Feng.- Section 2: Data Perspectives: Chapter 7: Assessing connections and tradeoffs between geospatial data ethics, privacy, and the effectiveness of digital contact tracing technologies: Peter Kedron and Andrew B. Trgovac.- Chapter 8: Challenges and limitations of geospatial data in the context of COVID-19: Sean G. Young; Jyotishka Datta; Bandana Kar; Xiao Huang; Malcolm D. Williamson; Jason A. Tullis; and Jackson Cothren.- Chapter 9: Multi-level inter-regional migrant population estimation using multi-source spatiotemporal big data: A case study of migrants in Hubei Province during the outbreak of COVID-19 in Wuhan: Qian Jiale, Liu Zhang, Du Yunyan, Wang Nan, Yi Jiawei, Sun Yeran, Ma Ting, Pei Tao and Zhou Chenghu.- Section 3: Analysis and Modeling Perspectives: Chapter 10: Identifying and characterising active travel corridors for London in response to Covid-19 using shortest path and Streetspace analysis: Nicolas Palominos, Duncan A Smith, and Sam Griffiths.- Chapter 11: Multi-scale CyberGIS analytics for detecting spatiotemporal patterns of COVID-19: Fangzheng Lyu, Jeon-Young Kang, Shaohua Wang, Su Yeon Han, and Shaowen Wang.-Chapter 12: Dynamic spreading of COVID-19 vs community mobility in regions of England: Tao Cheng, Xinchen Zhong, Yang Zhang, and Guanshen Dong.- Chapter 13: Exploring store visit changes during the COVID-19 pandemic using mobile phone location data: Yunlei Liang, Kyle W. McNair, Song Gao, and Asligul Gocmen.- Section 4: Application and Policy Perspectives: Chapter 14: Citizen mobility and the growth of infections during the COVID-19 pandemic with the effects of government restrictions in Western Europe: Mohd Sarim, Qunshan Zhao, and Nick Bailey.- Chapter 15: A mathematical model for evaluating the medical resource availability of COVID-19 in time and space: Fei-Ying Kuo and Tzai-Hung Wen.- Chapter 16: Health resilience against pandemic crisis among European countries: Yijing Li.- Chapter 17: Improving public transportation safety in COVID-19 era through crowdsourcing technique: Qisheng Pan, Zhonghua Jin, and Tao Tao.- Chapter 18: Outlook and next steps: Understanding human dynamics in a post-pandemic world - Beyond mapping COVID-19 in space and time: Daniel Sui and Shih-Lung Shaw.