Human mobility data and analysis for urban resilience: A systematic review

Author:

Haraguchi Masahiko1ORCID,Nishino Akihiko2,Kodaka Akira2,Allaire Maura3,Lall Upmanu4,Kuei-Hsien Liao5,Onda Kaya6,Tsubouchi Kota7,Kohtake Naohiko2

Affiliation:

1. Research Institute for Humanity and Nature, Kyoto, Japan; Columbia Water Center, Columbia University, New York, USA; and Harvard T.H. Chan School of Public Health, Harvard University

2. Keio University, Yokohama, Kanagawa, Japan

3. Department of Urban Planning & Public Policy, University of California, Irvine, Irvine, CA, USA

4. Department of Earth and Environmental Engineering, Columbia University, New York, NY, USA

5. Graduate Institute of Urban Planning, National Taipei University, Sanshia District, New Taipei City 237, Taiwan

6. The Graduate School of System Design & Management, Keio University, Minato-ku, Japan

7. Yahoo Japan Corporation, Yahoo Japan Research, Tokyo, Japan

Abstract

The impacts of disasters are increasing due to climate change and unplanned urbanization. Big and open data offer considerable potential for analyzing and predicting human mobility during disaster events, including the COVID-19 pandemic, leading to better disaster risk reduction (DRR) planning. However, the value of human mobility data and analysis (HMDA) in urban resilience research is poorly understood. This review highlights key opportunities for and challenges hindering the use of HMDA in DRR in urban planning and risk science, as well as insights from practitioners. A gap in research on HMDA for data-driven DRR planning was identified. By examining human mobility studies and their respective analytical and planning tools, this paper offers deeper insights into the challenges that must be addressed to improve the development of effective data-driven DRR planning, from data collection to implementation. In future work on HMDA, (i) the human mobility of vulnerable populations should be targeted, (ii) research should focus on disaster mitigation and prevention, (iii) analytical methods for evidence-based disaster planning should be developed, (iv) different types of data should be integrated into analyses to overcome methodological challenges, and (v) a decision-making framework should be developed for evidence-based urban planning through transdisciplinary knowledge co-production.

Funder

JST Belmont Forum

Research Fellowships of Japan Society for the Promotion of Science for Young Scientists

NSF

US-Japan Foundation

Publisher

SAGE Publications

Subject

Management, Monitoring, Policy and Law,Nature and Landscape Conservation,Urban Studies,Geography, Planning and Development,Architecture

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