Understanding the provision of multi-agency sensor information in disaster management: A case study on the Australian state of Victoria

https://doi.org/10.1016/j.ijdrr.2016.10.008Get rights and content

Abstract

Excitement about the potential usage of sensor data sourcing to provide near real-time information has spread to the emergency management sector. Despite the advantages that shared sensor-derived situational awareness may provide, research has been limited on the actual utilization of multi-vendor sensor data in disaster management. In consideration of this shortcoming, an empirical case study is conducted in the Australian state of Victoria to understand the current practices and requirements for access, exchange, and usage of multi-agency sensor data amongst participants in flood disaster organizations. First-hand knowledge of sensor data producers and disaster decision-makers is used, disclosing serious technical barriers to interoperable access to the highly disparate organizational sensor data. The findings also uncover the mechanisms in use for integrating multi-agency sensory information in disaster management, revealing the capabilities required of stakeholders to derive disaster information from raw sensor feeds.

Introduction

Facing with disasters of various types and intensity has become a complex environmental management issue [84]. The short response time that obtains for rapid onset disasters (such as floods, storms and bushfires) necessitates fast and coordinated actions of several actors [70]. Numerous agencies that might or might not be established organizations for disaster management are required to contribute and share resources and information during emergency situations [8], [67]. Dealing with challenges associated with the exchange of disaster information in a multi-agency environment is still a main research theme [81], [68], [77], [60], [44], especially those challenges that are related to the interoperability of emergency information [8], [100].

Amongst the various types of disaster information that need to be shared with relevant actors, spatial information plays a pivotal role [41], [54], [61]. In recent years, a new spatial data sourcing technology called in situ sensing [26] has emerged and gained attention in the emergency management sector as a potential solution for providing live disaster information [5]. Currently, an increasing number of sensors are deployed and used by organizations involved in disaster management. However, there is a lack of understanding about how these sensor resources are used in practice within disaster situations. Therefore, there is a need for systematic assessment of the factors affecting sensor utilization in cooperative disaster management.

The goal of this study is to investigate how multi-vendor sensor-derived data is produced and exchanged amongst participants in flood disaster organizations, and how this exchange affects the use of this type of information for emergency decision-making. We chose Australian practice of flood disaster management for our study, since Australia has a long history of flood and consequently has established procedures for cooperative flood management. Also, this country has invested largely in deploying and incorporating state-of-the-art sensor monitoring platforms. Consequently, stakeholders involved in state-wide disaster management currently contribute a variety of sensor resources, aiding the practicality of our sensor utilization investigation. The following research questions are central to this research:

  • What is the current practice for produce, exchange and usage of in situ sensor data within emergency management sector for supporting disaster decision-making?

  • What are the key challenges and requirements for multi-agency sensor information integration from the stakeholders' point of view?

A case study of the emergency management sector in Victoria, Australia provides the context to address these research questions. The innovative contribution of this work is two-folds. First, it contributes to sensor monitoring research by providing a realistic view of how sensors and their data are used in a real-world setting for the decision support of multiple organizations. Second, the paper fills a gap in disaster management research by empirically assessing the interoperability of agencies in regard to critical sensor data exchange during a disaster.

The paper starts by discussing the related work (Section 2), followed by the research approach (Section 3). Then, Section 4 presents the results of case study. Discussions and interpretation of results are provided in Section 4.3.NaN. Finally, the conclusion remarks are described in Section 4.3.NaN.

Section snippets

Multi-agency disaster management

In consideration of the urgency, dynamic nature and uncertainty underlying disaster management [40], [3], [35], [52], it is essential for contributing agencies to have rapid, though coordinated actions based on the situation in the disaster area [84]. Of diverse information types, sharing of spatial data has proven to be critical for the functioning of disaster management [22], [44], [37], [1].

The spatial information that is required in response operations can be classified into static and

Research methods

This research has made use of the case study research method [76] to examine multi-agency disaster management, but in the context of sensor information provision. Case study is often known as an empirical research method that enables investigation of contemporary and real-life phenomena in their context [98]. In light of the case study as a powerful method for conducting applied research [39], this study aimed to obtain an improved understanding of the stakeholders' activities in the context of

Results

In the remainder of the paper, we report the results from analyzing the three RQs and subsequently discuss and interpret the findings.

Summary and discussion of findings

In this research, we present for the first time an empirical case study of the stakeholders' activities in utilizing sensor resources to serve disaster management situations. The next section discusses the summary and interpretations of the results of RQ1 - RQ3 obtained from the focus group interviews with sensor data producers and disaster decision makers.

The results of RQ 1 led to the recognition of sensor systems operating under the administration of participating stakeholders in disaster

Conclusions and future work

We present a case study approach to analyze utilization of multi-agency sensor data in disaster management. The proposed approach consists of qualitative evaluations of stakeholder activities for access, exchange, and usage of multi-vendor sensor data, conducted in the context of large-scale sensor use in the disaster management of an urban flood. The case study covered the stakeholders' roles, level of involvement, protocols and procedures controlling their sensor data use in case of emergency.

Acknowledgements

This paper is part of an ongoing research project on multi-sourced sensor integration for disaster management conducted in the Centre for Disaster Management and Public Safety (CDMPS) and the Centre for Spatial Data Infrastructures and Land Administration at the Department of Infrastructure Engineering, The University of Melbourne. The authors deeply and humbly acknowledge the time, help and support of the participated experts at EMV, VicSES, BoM, DELWP, ESTA, CFA, MFB, PTV, VicRoads, City of

References (100)

  • B. Ramlal et al.

    Developing a GIS based integrated approach to flood management in trinidad, west indies

    J. Environ. Manag.

    (2008)
  • H. Seppänen et al.

    Shared situational awareness and information quality in disaster management

    Saf. Sci.

    (2015)
  • H. Srinivas et al.

    Environmental implications for disaster preparedness lessons learnt from the indian ocean tsunami

    J. Environ. Manag.

    (2008)
  • Z. Wan et al.

    A cloud-based global flood disaster community cyber-infrastructure: development and demonstration

    Environ. Model. Softw.

    (2014)
  • M. Werner et al.

    The Delft-FEWS flow forecasting system

    Environ. Model. Softw.

    (2013)
  • S. Yoon et al.

    Transportation security decision support system for emergency response: a training prototype

    Decis. Support Syst.

    (2008)
  • R. Abdalla, C.V. Tao, J. Li, Challenges for the application of GIS interoperability in emergency management, in:...
  • ABS, 3101.0 - Australian Demographic Statistics, 2014. URL 〈http://www.abs.gov.au/ausstats/[email protected]/mf/3101.0〉(accessed...
  • F. Alamdar, Integrated management of sensor data to facilitate disaster management, in: Modern Topics in Society...
  • F. Alamdar, M. Kalantari, A. Rajabifard, Towards integration of multisourced sensors for natural disaster management –...
  • F. Alamdar et al.

    An evaluation of integrating multisourced sensors for disaster management

    Int. J. Digit. Earth

    (2015)
  • F. Alamdar, M. Kalantari, A. Rajabifard, Development of a sensor web-based disaster decision support system for...
  • D.K. Allen et al.

    Information sharing and interoperability: the case of major incident management

    Eur. J. Inf. Syst.

    (2014)
  • A. Apan, D. Keogh, D. King, M. Thomas, S. Mushtaq, P. Baddiley, The 2008 Floods in Queensland: a Case Study of...
  • Beonic, Traffic Insight Homepage [Online], 2015. URL 〈http://www.beonic.com.au/solutions.html〉(accessed November...
  • P. Biernacki et al.

    Snowball sampling: problems and techniques of chain referral sampling

    Sociol. Methods Res.

    (1981)
  • BOM, Ex-TC Oswald Floods January and February 2013. Australian Bureau of Meteorology,...
  • M. Botts, A. Robin, OGC® Sensorml: Model and xml enCoding Standard. Open Geospatial Consortium: Wayland, MA, USA,...
  • A. Bröring, F. Bache, T. Bartoschek, C. van Elzakker, The SID creator: a visual approach for integrating sensors with...
  • A. Bröring et al.

    OGC Sensor Observation Service interface standard

    Open Geospatial Consort. Interface Stand.

    (2012)
  • I. Burnstein

    Practical software testing: a process-oriented approach

    (2003)
  • CFA, One Source One Message Reference Guide, 2015, URL 〈http://tinyurl.com/nkh8qcf〉(accessed November...
  • N. Comrie, Review of the 2010–11 Flood Warnings & Response. State of Victoria,...
  • S.J.D. Cox, ISO 19156:2011 Geographic Information - Observations and Measurements. International Organization for...
  • S.K. Dakin

    NSW hunter and central coast flood summary April - May 2015

    NSW Public Works Manly Hydraul. Lab.

    (2015)
  • L.C. Degrossi, J. Albuquerque, M.C. Fava, E.M.Mendiondo, Flood citizen observatory: a crowdsourcing-based approach for...
  • DELWP, FloodZoom Homepage [Online], 2015a. URL...
  • DELWP, Noggin Organise, Communicate, Act (oca) Homepage [Online] 2015b. URL 〈http://www.noggin.io/〉. (accessed November...
  • DELWP-CFA, E-Map Homepage [Online] 2015. URL 〈http://geoplex.com.au/work/depi-emap/〉. (accessed November...
  • A. Dilo et al.

    A data model for operational and situational information in emergency response

    Appl. Geomat.

    (2011)
  • M. Duckham

    Decentralized Spatial Computing: Foundation of Geosensor Networks

    (2013)
  • N. Dufty, Review of the Gippsland November 2007 Flood Response (Report), 2008...
  • EMV, Emergency Management Victoria Homepage [Online], 2014a. URL 〈http://www.emv.vic.gov.au/〉. (accessed November...
  • EMV, VicEmergency Website [Online], 2014b. URL 〈http://emergency.vic.gov.au/map#now〉. (accessed November...
  • EMV, EM-COP Homepage [Online], 2015. URL...
  • EMV, State Control Centre Homepage [Online], 2016. URL...
  • G. Evans et al.

    The maitland flood of 2007 operation of the hunter valley flood mitigation scheme and the maitland city local flood plan

    State Emerg. Serv.

    (2008)
  • J. Fohringer, D. Dransch, H. Kreibich, K. Schröter, Social Media as an Information Source for Rapid Flood Inundation...
  • S. Fuhrmann, A. MacEachren, G. Cai, Geoinformation technologies to support collaborative emergency management, in:...
  • S.M. George et al.

    DistressNet: a wireless ad hoc and sensor network architecture for situation management in disaster response

    IEEE Commun. Mag.

    (2010)
  • Cited by (0)

    View full text