Leveraging Information Systems for Disaster Management

Introduction

In today's digital age, both natural and man-made disaster management has become a more tractable challenge. Several information technology (IT) features are at our disposal, capable of supporting prevention and recovery alike. Advances such as satellite communication, the Internet, remote sensing, and geographic information systems (GIS) have proven extremely valuable in hazard reduction planning and execution (Vyas & Desai, 2007). IT has been employed across fields including business disaster recovery, continuity planning, risk management, and continuous monitoring.

Risk Management and GIS Applications

Generally, activities in emergency and risk management are separated into two categories: (1) pre-event activities, such as preparation and mitigation, and (2) post-event activities, such as recovery and response. In the preparation stage, simulation and modeling exercises are crucial and can facilitate prevention, mitigation, and adaptation. In the field of geographic information systems, applications in water-resource management have most effectively utilized GIS's analytical capabilities for developing simulation runs and biophysical models, such as Hydraulic and Hydrological Models (HEC-RAS and MIKE11). When integrated, these systems can forecast flood behavior by deriving inputs from different terrain, hydro-meteorological datasets, and land use or land cover data — functioning, in effect, as Spatial Decision Support Systems (SDSS) (Zlatanova, Ghawana, Kaur & Neuvel, 2014).

The planning stage is generally initiated by locating and identifying possible disaster sites — that is, at-risk places. Via GIS, threats are recognized and evaluation of potential disaster or emergency consequences is begun. Hazard mapping — covering flood zones, earthquake faults, avalanche paths, landslide areas, and so on — is conducted with reference to key infrastructure at risk, including residential areas, hospitals, schools, streets, storage facilities, power lines, and pipelines. This is followed by the formulation of preparedness, response, mitigation, and potential recovery requirements by the relevant authorities. The process makes clear which lives, environmental values, and properties face the greatest risk. Public safety authorities can thus identify and concentrate on areas where mitigation will be needed, where response should be reinforced, and where preparedness and recovery efforts must be focused. GIS eases this process by enabling planners to examine suitable combinations of spatial data through computer-generated mapping (Stephenson & Peter, 1997).

At the response stage, the information described above — combined with both spatial and non-spatial infrastructural data — may be utilized to improve response efficiency. Optimizing response units' routes on the basis of real-time information about disaster-affected regions can save both time and resources. Satellite images of disaster-hit territories offer information regarding the area and extent of impact. In the case of floods, depth and volume data from earlier simulations can be utilized by the agencies concerned to ascertain possible water depth or volume in flood regions, as well as the likelihood of adjacent regions being impacted as water reaches them (Zlatanova et al., 2014).

Continuous Monitoring and Early Warning Systems

In the last decade, nations and regions have significantly advanced in the development and implementation of Early Warning Systems (EWS). Much of this improvement is attributable to better information and communication technology (ICT), improved monitoring and observational systems, and greater public awareness of the importance of emergency risk reduction. A compelling example of the value of extending EWS coverage is Bangladesh, which now maintains a two-day cyclone warning system that enables individuals to evacuate their homes and move to storm shelters hours before cyclones make landfall, appreciably decreasing the death toll. Three hundred thousand people lost their lives to Cyclone Bhola in 1970, compared to 3,000 deaths from Cyclone Sidr in 2007; authorities reported both events to be of similar magnitude. Even for risks that involve greater complexity and longer development times — such as droughts — EWS helps keep death tolls low across regions such as Sub-Saharan Africa (Carabine & Jones, 2015).

Weather forecasting is one prominent EWS technology: a large number of nations now have early warning techniques grounded in weather forecasts, which deliver important details days, weeks, or even months in advance and communicate warnings to relevant local stakeholders. These systems rely on high-technology weather models and are particularly valuable in preparing for extreme climate events.

With the rapid worldwide spread of mobile networks and cell phones, mobile technology has become another progressively adopted means for providing warnings and coordinating preparedness activities. SMS (Short Message Service) is used extensively for disseminating mass messages. Japan offers one example of SMS integration into disaster warning systems: upon detecting early earthquake signs, Japanese agencies disseminate SMS warnings to every registered cell phone user in the country. Crowd-sourced data also finds increasing use as greater numbers of people gain access to the internet and ICTs such as mobile phones. This technique was employed on a large scale in response to the 2010 earthquake in Haiti, enabling mapping specialists, local residents, and other relevant stakeholders to transmit information about what they witnessed at the disaster site and generate data useful to humanitarian workers (Carabine & Jones, 2015).

Personal multimedia recorders and surveillance methods can offer a much richer and more contextually applicable data source for disaster scientists than large-scale sensors alone. Personal recording devices provide a proximal account of events, without the errors introduced by the alteration and fading of witnesses' memories over time. Moreover, the data procured from them may be more relevant to social research than the quantitative sensor records of physical phenomena. Surveillance cameras played an important role in reconstructing numerous events of 9/11, including the evacuation timeline and the structural failures of the World Trade Center. Following the great tsunami in the Indian Ocean in December 2004, University of Buffalo teams were able to quickly capture perishable data about building and lifeline damage characteristics using a compact surveying mechanism that integrated GPS (global positioning satellite), personal videography, and satellite photography. Informal disaster recordings thus constitute a highly important alternate information source (Moss & Townsend, 2006).

References

Carabine, E. & Jones, L. (February 2015). Early warning systems and disaster risk information. Overseas Development Institute.

Kaviani, A. & Rajabifard, A. (2014). VGS-based framework for disaster response. Coordinates, Volume X, October 2014.

Moss, M. L. & Townsend, A. M. (May 2006). Disaster forensics: Leveraging crisis information systems for social science. New Technologies and the Future of Disaster Research.

Stephenson, R. & Peter, S. A. (1997). Disasters and the information technology revolution. Disasters, 21(4), 305–334.

Vyas, T. & Desai, A. (February 2007). Information technology for disaster management. Proceedings of National Conference; INDIACom-2007.

Yodmani, S. & Hollister, D. (May 2001). Disasters and communication technology: Perspectives from Asia. Presented at the Second Tampere Conference on Disaster Communications.

Zlatanova, S., Ghawana, T., Kaur, A. & Neuvel, J. M. M. (2014). Integrated flood disaster management and spatial information: Case studies of Netherlands and India. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-8.