Presenting the scope of managing the disaster using different technologies. Focusing and comparing disaster management in past, present and future

1. Subject: Disaster Management
Prepared By: Rutvik Patel 170050106046
Parth Patel 170050106045

2. Disaster management
Past
Present
Future

3. Disaster management or Emergency
management
• Disaster Management can be defined as the organization and
management of resources and responsibilities for dealing with all
humanitarian aspects of emergencies, in particular preparedness,
response and recovery in order to lessen the impact of disasters.

4. Disaster management

5. Disaster management in past
• In the past scientists relied on the statistical methods to predict
natural disasters.
• These statistical methods were not that efficient.

6. Fractals analysis of disaster

7. Disaster management at present
• Using GIS
• Remote Sensing

8. GIS (Geographic Information System) in
Disaster management

9. Role of GIS in Disaster management
• All disasters are spatial in nature.
• GIS techniques act as a decision support tool.
• GIS, RS & GPS is useful in disaster management applications & for
decision making.
• Evolution of computer technology and availability of hardware is
helpful for rapid expansion of GIS in both disaster research and
practice.
• GIS and RS much beneficial in mitigation strategies and preparedness
plans.

10. Usefulness of GIS

11. Remote sensing (RS)
• Remote sensing is the acquisition of information about an object or
phenomenon without making physical contact with the object and
thus in contrast to on-site observation, especially the Earth.

12. Application of RS in Disaster Management
• RS can be used as an early warning system to aware people about the
disaster.
• RS can be helpful in many disasters like cyclone, earthquake, floods,
drought, volcano, fire, landslide.
• We will be getting a little brief about how RS is useful in above all
disasters.

13. Role of RS in cyclone
MITIGATION PREPAREDNESS RESCUE RECOVERY SATELLITIES USED
Risk modelling,
Vulnerability
analysis
Early warning,
Long range climate
modelling
Identifying escape
routes, crisis
management,
impact assessment
Spatial planning,
Damage assessment
KALPANA 1, INSAT
3A, Meteosat

14. Role of RS in Earthquakes
MITIGATION PREPAREDNESS RESCUE RECOVERY SATELLITES USED
Hazard mapping Measuring strain
accumulation
Deformation
mapping,
evacuation
planning, damage
assessment
Identifying sites for
rehabilitation
PALSAR, IKONOS 2,
SPOT, IRS

15. Role of RS in other Disasters
DISASTER MITIGATION PREPAREDNESS RECOVERY RESCUE SATELLITES
USED
DROUGHT Risk
vulnerability
analysis, land
and water
management
planning
Weather
forecasting,
vegetation
monitoring,
early warning
Monitoring
vegetation,
damage
assessment
Informing
drought
mitigation
FEWS NET,
AVHRR, MODIS,
SPOT
VOLCANO Risk modelling,
digital elevation
models
Emissions
monitoring
thermal alerts
Mapping lava
flows,
evacuation
planning
Spatial planning MODIS &
AVHRR,
Hyperion
FIRE Mapping fire
prone areas, risk
modelling
Fire detection
predicting, early
warning
Coordinating fire
fighting efforts
Damage
assessment
MODIS, SERVIR,
AFIS, Sentinel
Asia

16. Disaster management in future
• Before going for the future planning let us have a glance into the past
disasters for a moment.
• Recently, the regions around the Dead Sea in Jordan were flooded,
causing the death of 21 children who were on a school trip, and
injuring 35 more.
• Such disasters affect millions of people every year and cause property
damage worth hundreds of billions. In 2017 alone, almost 335 natural
disasters have affected more than 95.6 million people, and killed
9,697, costing around US $335 billion.

17. How AI can and will help predict disasters
• The impact of these phenomena can be reduced if we were able to
predict their occurrence.
• Researchers are applying artificial intelligence to accurately predict
natural disasters.
• By predicting the occurrence of natural disasters, we can save
thousands of lives and take appropriate measures to reduce property
damage.

18. Using AI to predict natural disasters
• With enormous amounts of good quality datasets, AI can predict the
occurrence of numerous natural disasters, which can be the
difference between life and death for thousands of people.

19. Natural disasters predicted by AI
• Earthquake
• Floods
• Volcanic eruptions
• Hurricanes

20. Prediction of earthquakes using AI
• Artificial intelligence can use the seismic data to analyze the
magnitude and patterns of earthquakes.
• Google and Harvard are developing an AI system that can predict the
aftershocks of an earthquake.
• In the future, we may be able to foresee earthquakes and authorities
can start evacuation operations accordingly.
• Artificial intelligence systems can detect deformations in structures,
which can be used to reduce the damage caused by collapsing
buildings and bridges, or subsiding roads.

21. Prediction of Floods using AI
• Google is building an AI platform to predict floods in India and warn
users via Google Maps and Google Search.
• Similarly, researchers are developing AI-based systems that can learn
from rainfall and climate records and tested with flood simulations,
which can predict floods better than the traditional systems.
• Researchers at the University of Dundee in the United Kingdom are
monitoring urban flooding by collecting crowd-sourced data with
Twitter and other mobile apps.
• Likewise, applications based on artificial intelligence and deep
learning is useful for disaster management.

22. THANK YOU