Review Article
Disaster resilience through big data: Way to environmental sustainability

https://doi.org/10.1016/j.ijdrr.2020.101769Get rights and content

Highlights

  • Big data driven disaster resilience has been focused.

  • PRISMA approach has been employed to explore most relevant studies dealing with disaster resilience.

  • Big data has a great potential to enhance disaster resilience.

  • Highlights the use of big data technologies for enhancing environmental aspect of sustainability.

Abstract

Disaster management is a growing concern and priority throughout the world and “resilience” is increasingly viewed as a key capacity related to disaster and post-disaster management and development. Recent research highlights how resilience is enhanced through the use of “big data” technologies that improve the speed and effectiveness of linkages between disaster information and systemic response. Summarizing and discussing this research, this study highlights and substantiates the potential of big data strategies to help mitigate the risks and impact of socio-ecological vulnerability. Based on a qualitative desk review and analyses of secondary data, resilience is framed as a function of the adaptive, absorptive and transformative capacity of socio-political systems to withstand and cope with the adverse effects of disaster. In addition, this study emphasizes the major principles and components of effective big data use; e.g., open source tools, strong infrastructure, local skill development, context-specific data sources, ethical data sharing and experiential learning. This study reveals some important big data technologies that can be easily used in the different phases of disaster management and enhancing resilience such as remote sensing imagery, social media data, crowdsourced data, geographic information system (GIS), and mobile metadata. The findings hold major relevancy for policymakers, administrators, and related stakeholders responsible for taking action before, during and after disasters through training, early warning systems, emergency evacuation, relief distribution and other key infrastructural components.

Introduction

Disasters are the outcome of abnormal weather or long term climate change effect that are increasing gradually all over the world. Developed countries can easily manage the harmful effects of climate change but developing countries tend to be less resilient and more prone to suffering [1]. People can see only direct damages but it is very difficult to realize the indirect damages. Various factors are responsible for natural hazards. Climate change is one of the leading factors that causes frequent natural hazards [2] and is now a growing concern throughout the world due to its increasing adverse effect on almost all aspects of life. Though disaster vulnerable communities across the world are trying to manage climate change effects through context-specific adaptation strategies, it remains unclear whether these can effectively protect them from the devastating effects [3]. At the same time, it is increasingly recognized that specific technologies can help improve each stage of disaster management in poorer communities [4].

Resilience is a popular concept frequently used in the disaster literatures [5]. It means “bounce back” and focuses to a process of bounce back to previous condition after facing any disturbance caused by hazards [6]. It also shows the extent of human-environment interactions [7]. According to UNISDR (United Nations International Strategy for Disaster Reduction) [8], “resilience is the ability of a system, community or society exposed to hazards to resist, absorb, accommodate to and recover from the effects of a hazard in a timely and efficient manner, including through the preservation and restoration of its essential basic structures and functions.” Disaster resilience, a key concept in disaster management, refers to the ability of an individual, group or community to revert back to former normal condition after a hazard [9]. Integrating adaptive, absorptive and transformative capacity, resilience focuses on the multi-dimensional capacity of a community unit to face and successfully manage disaster and reduce vulnerability by enhancing adaptive, absorptive and transformative capacity [10]. Resilience addresses various root causes of disasters by building capacity and identifying proper adaptation strategies [11,12]. Disaster resilience also involves network capacities [13], livelihood capitals [14], physical system [15] and governance [16]. Big data technology is an important tool for enhancing resilience in terms of policy making, decision making, leadership, research and administration [17].

Big data is a comparatively new paradigm of technology and approach to disaster resilience [18]. It helps academicians, researchers and administrators to conduct analyses and decision making through the efficient scientific use of large data sets, mobile phones [19], and social media [[9], [10], [11]]. Big data provides a promising opportunity for information and communication to enable susceptible communities to prepare for upcoming threats, challenges, risks and disasters [[12], [13], [14], [15]]. The incidence of hazards is beyond the control of human beings and causes huge damage to lives and assets, with about 60,000 people dying each year due to natural hazards [22]. Technology plays a key role in reducing vulnerability and enhancing disaster resilience. Big data technologies, with its multitude of platform applications, is considered to be a promising tool to develop disaster resilience. This study represents an initial initiative to identify technologies already proven to be effective. Its findings provide a new lens for enhancing community disaster resilience through big data to the academicians, researchers and decision makers. Some research has already been conducted on disaster management [23], disaster resilience [8,18] and big data application in the environmental management field [[19], [20], [21]] but studies related to disaster resilience applications are still lacking. Since disaster risk is related to the effect of natural hazards, vulnerability, and scarcity of natural resources, big data can be an effective approach to enhance resilience. Effective data-driven strategies can be helpful in understanding and responding to the dynamic environmental conditions leading to disaster risk. Considering the practical importance, this study explores the potential of big data for enhancing disaster resilience.

Section snippets

Research design

A systematic desk literature review was conducted covering relevant research over the last 10 years. Recent data was collected from participants in ongoing debate over the potential of big data for disaster resilience. This study focuses on big data approaches aimed at enhancing disaster resilience.

Search strategy

Desk literature review is an indispensable first step toward identifying and developing new paradigms within emerging fields of study. Therefore, recent related studies were extensively searched in

Systematic review results

Systematic Review and Meta-Analysis (PRISMA) recommendations were followed for the systematic literature review [25]. At first, 397 documents were obtained with eight related documents from their bibliographies. Next, 167 documents were detected after abstract screening. A total of 134 documents were then removed due to lack of full text, redundancy or absence of a big data approach to disaster management. Finally, the most relevant 21 documents encompassing journal articles, books, book

Discussion

Based on the examined literature, this section provides a detailed explanation of the potential of big data for improving disaster resilience.

Conclusion

Considering the great importance of leveraging big data for enhancing resilience for disaster management, this study focused on various scholars’ examination of recent technologies that can help people in all stages of disaster management. This study reveals that disaster resilience is a combined function of the adaptive, absorptive and transformative capacity of an individual or society to withstand and cope with the adverse effects of the disaster. This study identifies the effective uses of

Declaration of competing interest

The authors declare that there is no conflict to any matter of the manuscript.

References (63)

  • S. Shan et al.

    Disaster management 2.0: a real-time disaster damage assessment model based on mobile social media data—a case study of Weibo (Chinese Twitter)

    Saf. Sci.

    (2019)
  • K.M. Carley et al.

    Crowd sourcing disaster management: the complex nature of Twitter usage in Padang Indonesia

    Saf. Sci.

    (2016)
  • R.I.I. Ogie et al.

    Crowdsourced social media data for disaster management: lessons from the PetaJakarta.org project

    Comput. Environ. Urban Syst.

    (2019)
  • N. Clark et al.

    Seeing through the clouds: processes and challenges for sharing geospatial data for disaster management in Haiti

    Int. J. Disaster Risk Reduct.

    (2018)
  • T. Schempp et al.

    A framework to integrate social media and authoritative data for disaster relief detection and distribution optimization

    Int. J. Disaster Risk Reduct.

    (2019)
  • A. Gupta et al.

    Big data & analytics for societal impact: recent research and trends

    Inf. Syst. Front

    (2018)
  • F.E.A. Horita et al.

    Bridging the gap between decision-making and emerging big data sources: an application of a model-based framework to disaster management in Brazil

    Decis. Support Syst.

    (2017)
  • D. Contreras et al.

    Measuring the progress of a recovery process after an earthquake: the case of L’aquila, Italy

    Int. J. Disaster Risk Reduct.

    (2018)
  • M.N.I. Sarker et al.

    Livelihood vulnerability of riverine-island dwellers in the face of natural disasters in Bangladesh

    Sustainability

    (2019)
  • S. Fahad et al.

    Climate change, vulnerability, and its impacts in rural Pakistan: a review

    Environ. Sci. Pollut. Res.

    (2020)
  • S.A.P. Kumar et al.

    Flooding disaster resilience information framework for smart and connected communities

    J. Reliab. Intell. Environ.

    (2019)
  • A. Abbas et al.

    Sustainable survival under climatic extremes: linking flood risk mitigation and coping with flood damages in rural Pakistan

    Environ. Sci. Pollut. Res.

    (2018)
  • D.J. Parker

    Disaster resilience – a challenged science

    Environ. Hazards

    (2020)
  • C.L. Pandey

    Making communities disaster resilient, Disaster Prev

    Manag. An Int. J.

    (2019)
  • A. Ostadtaghizadeh et al.

    Community disaster resilience: a qualitative study on Iranian concepts and indicators

    Nat. Hazards

    (2016)
  • UNISDR Terminology on Disaster Risk Reduction

    (2009)
  • W.N. Adger et al.

    Social-ecological resilience to coastal disasters

    Science

    (2005)
  • S. Dhyani et al.

    Ecological engineering for disaster risk reduction and climate change adaptation

    Environ. Sci. Pollut. Res.

    (2016)
  • N. Agrawal

    Disaster resilience

  • G.P. Cimellaro et al.

    SHM role in the Framework of infrastructure resilience

  • C. Yang et al.

    Using big data to enhance crisis response and disaster resilience for a smart city

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