CeBIT Spatial@gov 2012 - Alan Dormer, Science Leader, Government and Commercial Services, CSIRO

Big Spatial Data for Disaster ManagementNovember 21st 2012

DIGITAL PRODUCTIVITY AND SERVICES FLAGSHIP

Agenda

1. Introduction

2. All Hazards/End-to-End Initiative

3. Case Studies

• Social Protection

• Enhanced Situational Awareness

• Dynamic Flood Modelling

4. Conclusion

Big Spatial Data for Disaster Management | November

Digital Productivity & Services Flagship

Help business and government deliver new, faster, better services:

• Efficiently and effectively

• Doing old things in new ways

• Doing new things in completely new ways

What we doEvidence based policy and decision support

– Analytics

– Optimisation

Service delivery transformation

– Services innovation

– Business process and business rules

optimisation

Customer centric services

– Wrapping the service provider

around the customer

– Services personalisation

... Information is very directly about saving lives. If

we take the wrong decisions, make the wrong

choices about where we put our money and our

effort because our knowledge is poor, we are

condemning some of the most deserving to death

or destitution.

John Holmes UN Emergency Relief Coordinator and Under-

Secretary-General for Humanitarian Affairs (Amin and Goldstein

Impact Depends on Co-Location

Severity

Vulnerability

& protection

Probability

/ Frequency

People &

Property

Agenda

1. Introduction

3. Case Studies

4. Conclusion

Hazard Probability Impact Response

Storm Surge

/Tsunami

Bushfire

Cyclone

Earthquake

Research Activities Matrix in Flagship

Existing

Known gaps in all areas: opportunities for

collaboration

Partial

• Maximum foreseeable loss – ETSA

• Estimating Extreme Risk - Suncorp

• Social Media Monitoring – Queensland DCS and Victoria ESTA

• Social Protection in Indonesia – UN/AusAID

• Emergency Response Intelligence Capability – Dept Human Services

• Flood Modelling – BSMG

• Bushfire Modelling – Victorian Government

• Impacts Framework – Fire & Rescue NSW

• Urban Monitor - DSEWPAC

Current Activities

Need: Disaster

Management

Response

Emergency Response/Decision Support

Social Impact AnalysisBush fire AnalysisIntegrated Science

Domains/Systems

Landscape

ModellingFuel

Climate/We

Modelling

Financial

Scenarios

Models

Applications: Specific

Science Domains

Landscape

Characteristics

Fuels Climate/

WeatherFinance Urban Data (pop.

Density etc)

Virtual

Libraries/Inputs:

Knowledge Bases

(Services)

Processing

Services

DataMiddleware

Processing

Services

DataMiddleware Processing

Services

DataMiddleware

Models & analytic

Integrated Disaster Management Decision Support Platform

Prepared by Ryan Fraser, adapted from work by Lesley Wyborn (Geoscience Australia), 2012

Applications

Business Need

Policy

Agenda

1. Introduction

3. Case Studies

4. Conclusion

AusAID Project

12 | CSIRO – Information Sharing for Emergency Management

•Gazetteer framework

• Infrastructure to bring data together

•Traditional Data Sources

• Income (240M people)

• Crops, etc

•Unconventional Data Sources

• Phone records (2Bn calls/day)

• Social media, etc

•Analytics

• Where are vulnerable populations?

• Getting worse or better?

• Exposure to natural hazards?

Social Protection

Discover Access Understand Extract, Transform, Load

Time and effort

achieve fundamental, systemic improvement in information integration capability that enables more effective and cost-efficient sustained service delivery

Discover Access,

Understand

Extract Transform Load Use

Gazetteer framework - enable place names used

in different systems to be registered and used to

reference and integrate other information

Multi-sectoral information for Social Protection

• Accurate

• Up to date

• Timely

• Integrated

• Presented in meaningful ways

Social Protection

“preventing, managing, and overcoming situations that adversely affect people’s well being.[1] “

- policies and programs to reduce poverty and vulnerability

-reducing exposure, enhancing capacity to manage risks

Project drivers

1United Nations Research Institute For Social Development

Example Use Case – Tsunami in Japan

30 km exclusion zone:

• How many people are inside?

• How many schools inside?

• Where are the exit roads; which ones are open?

• How many schools, hospitals, aged care homes inside?

• Which local governments areas?

• Which rivers flow through?

• Where are the nearest hospitals?

Presentation title | Presenter name | Page 16

Australian Application – Intensive Support

Agenda

1. Introduction

3. Case Studies

4. Conclusion

19 | CSIRO – Australian Science, Australia's Future | Living in a Broadband World | Oppermann

The explosion of highly personalised social media is creating a wealth of rich data sources..

0 20 40 60 80

Send a text message to a response agency asking for

Ask people to help you reach a response agency

through a social network like facebook or Twitter to

get help

Post a request for help on a response agency's

Facebook page

Send a direct message via Twitter to a response

agency requesting help

% extremely/very likely

Current study American Red Cross

Social Media in Disasters and EmergenciesIf you needed help and 000 was busy...

Taylor M, Howell G, Raphael B. (2011). Use of social media. Presentation to the Joint Australia/US (DSTO/DHS) Technical Working Group. Melbourne, Victoria, 8th September 2011.

The US study was based on 1000 people – cross section of the general public (i.e. all ages over 18, and not necessarily social media users), Taylor et. a;l. data is based on 1170

people, with a more uncontrolled sample sent out via social media (so predominantly, if not entirely, based on people who use social media)

CSIRO’s Enhanced Situation Awareness

Capture

Detection and Alerting

Problem : Crisis coordinators need tools to manage issues arising from Tweet deluge

Solution : Alerts generated by our system are shown as a tag cloud. Alert colour and

size indicates deviation from expected.

Alerts are linked to clusters. Mouse click on alert tag to see cluster content.

Alert words are added to a tracking list. Tracking list can be clustered and displayed. Alerts can be tracked over time.

Detecting and Alerting - Earthquakes

• When you don't know what to look for, such as with unexpected incidents, our Alert Monitor can provide some clues as to what is going on in Twitter Australia-wide within 3 minutes of the event.

• Moe earthquake as reported by our Melbourne Alert Monitor (last Friday 20th July 2012 19:13:08)

Christchurch 2011

Condensing and Summarising

Forensic AnalysisComparing alerts with other knowledge

Agenda

1. Introduction

3. Case Studies

4. Conclusion

Mundaring Dam History

Concrete Gravity Dam

Built between 1898 and 1902

Height: 42 m (originally 32 m)

Extended by 10 m in 1940’s

Length: 308 m

Capacity: 64 GL

The weir leaks showing consistent

moisture stains where water moves

through the structure. This could be a

potential cause of dam failure.

Mundaring Dam Location

PERTH CBDDam Wall

Perth CBD Inundation

The water is coloured by velocity with blue 0 m/s and red 15 m/s

Much of the convention centre and the region around it are affected. Peak

flooding occurs at around 5.6 hours after the dam break event.

Perth CBD Inundation

The water is coloured by velocity with blue 0 m/s and red 15 m/s

Much of the convention centre and the region around it are affected. Peak

flooding occurs at around 5.6 hours after the dam break event.

tsunami approach to Fremantle harbour

The approach of the tsunami towards Fremantle harbour is simulated

using the SW solver. A wave train with a maximum amplitude of 3 m is used as

the tsunami source approximately 50 km offshore. The wave originates from

an earthquake source close to Sumatra.

tsunami approach to Fremantle harbour

The approach of the tsunami towards Fremantle harbour is simulated

using the SW solver. A wave train with a maximum amplitude of 3 m is used as

the tsunami source approximately 50 km offshore. The wave originates from

an earthquake source close to Sumatra.

tsunami run-up and inundation

The tsunami run-up and inundation into the Fremantle harbour is simulated

using SPH. The initial wave is setup 2 km off-shore by using the SW solution as

the basis.

Terrain resolution = 5 m

Fluid resolution = 2 m

Terrain particles = 800K

Fluid particles = 2 milion

Wave height = 7 m

Wave speed = 10 m/s

Run-up distance = 1.5 km

tsunami run-up and inundation

The tsunami run-up and inundation into the Fremantle harbour is simulated

using SPH. The initial wave is setup 2 km off-shore by using the SW solution as

the basis.

Terrain resolution = 5 m

Fluid resolution = 2 m

Terrain particles = 800K

Fluid particles = 2 milion

Wave height = 7 m

Wave speed = 10 m/s

Run-up distance = 1.5 km

Agenda

1. Introduction

3. Case Studies

4. Conclusion

Conclusions

Disaster management is a spatio-temporal, big data problem

CSIRO sees value in the all hazards, end-to-end approach

A robust spatial data infrastructure is essential

CSIRO is keen to collaborate with other organisations using common

data and decision support frameworks

New developments such as crowd sourcing add value and can be

incorporated

Today we have released a report available at:

http://www.csiro.au/disaster-management-report

Any Questions

CeBIT Spatial@gov 2012 - Alan Dormer, Science Leader, Government and Commercial Services, CSIRO

Documents

Cebit m krzyzanowski_atm_poland

CeBIT Spatial@gov 2012 - Paul Box, Research Team Leader, CSIRO

Sinadura Cebit 2012

LAMAR & SHERI CARTER...SHED DORMER SECOND FLOOR PLAN OPEN TO AREA BELOW 8'-0" GABLE DORMER 8'-0" GABLE DORMER FLAT CEILING OVER DRESSING AREA 12'-0" GABLE DORMER SECOND FLOOR JOISTS

ASRock CeBIT 2010

brocas 338 dormer

Jane Dormer Duchess of Feria

Hitachi Rail - Alistair Dormer

Dormer bungalow beside our school

Brasscomm Brasil @CeBIT

Creativu Cebit Crs4

Homesickness Buhay Dormer

B P S010 Dormer 091907

Precision Dormer Main Cat

Mysterious Dormer Chronology

Cebit joanna kowalska_geoportal

TURNING CHIPBREAKER GUIDE - Dormer Pramet

Cebit m krzyzanowski_atm_vs3

Alan Dormer - CSIRO as given by Dr Andreas Ernst - Improving reliability and capacity in heavy haul operations – Technology trends in supply chain optimisation

Final Sir Cecil Fj Dormer