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

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

  • Big Spatial Data for Disaster ManagementNovember 21st 2012DIGITAL PRODUCTIVITY AND SERVICES FLAGSHIP
  • Agenda1. Introduction2. All Hazards/End-to-End Initiative3. Case Studies • Social Protection • Enhanced Situational Awareness • Dynamic Flood Modelling4. ConclusionBig Spatial Data for Disaster Management | November2012
  • Digital Productivity & Services FlagshipHelp 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 – OptimisationService delivery transformation – Services innovation – Business process and business rules optimisationCustomer 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 2008)
  • Impact Depends on Co-Location Probability Severity / Frequency Vulnerability People & & protection Property
  • Agenda1. Introduction2. All Hazards/End-to-End Initiative3. Case Studies • Social Protection • Enhanced Situational Awareness • Dynamic Flood Modelling4. ConclusionBig Spatial Data for Disaster Management | November2012
  • Research Activities Matrix in FlagshipHazard Probability Impact ResponseFloodStorm Surge/TsunamiBushfireStormCycloneEarthquake Existing Partial Known gaps in all areas: opportunities for collaboration None
  • Current Activities• 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
  • Integrated Disaster Management Decision Support Platform Need: Disaster Emergency Response/Decision Support Management ResponsePolicy Integrated Science Bush fire Analysis Social Impact Analysis Domains/SystemsBusiness Need Climate/We Applications: Specific Landscape Financial Urban Fuel ather Modelling Scenarios Models Science Domains ModellingApplicationsS Models & analyticY Processing Processing e Processing e Processing e Processing e tools Services ar e Services ar Services ar Services ar Services arS l ew le w le w le w le w dd dd dd dd d d Mi Data Mi Data Mi Data Mi Mi Data VirtualT Data Libraries/Inputs:E Knowledge BasesM Landscape Fuels Climate/ Finance Urban Data (pop. (Services) Characteristics Weather Density etc)S Prepared by Ryan Fraser, adapted from work by Lesley Wyborn (Geoscience Australia), 2012
  • Agenda1. Introduction2. All Hazards/End-to-End Initiative3. Case Studies • Social Protection • Enhanced Situational Awareness • Dynamic Flood Modelling4. ConclusionBig Spatial Data for Disaster Management | November2012
  • AusAID Project 12 | CSIRO – Information Sharing for Emergency Management
  • Social Protection•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?
  • Goals achieve fundamental, systemic improvement in information integration capability that enables more effective and cost-efficient sustained service delivery Use Discover Access, Extract Transform Load Use Discover Access Extract, Transform, Load Understand Time and effort Understand Gazetteer framework - enable place names used in different systems to be registered and used to reference and integrate other information 14 | CSIRO – Information Sharing for Emergency Management
  • Project driversMulti-sectoral information for Social Protection• Accurate• Up to date• Timely• Integrated• Presented in meaningful waysSocial Protection“preventing, managing, and overcoming situations that adverselyaffect people’s well being.[1] “- policies and programs to reduce poverty and vulnerability-reducing exposure, enhancing capacity to manage risks 1United Nations Research Institute For Social Development
  • Example Use Case – Tsunami in Japan30 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 .17 | CSIRO – Information Sharing for Emergency Management
  • Agenda1. Introduction2. All Hazards/End-to-End Initiative3. Case Studies • Social Protection • Enhanced Situational Awareness • Dynamic Flood Modelling4. ConclusionBig Spatial Data for Disaster Management | November2012
  • The explosion of highly personalised social media is creating a wealth of rich data sources.. .19 | CSIRO – Australian Science, Australias Future | Living in a Broadband World | Oppermann
  • Social Media in Disasters and EmergenciesIf you needed help and 000 was busy... Current study American Red Cross Send a text message to a response agency asking for 59 help 52 Ask people to help you reach a response agency 73 through a social network like facebook or Twitter to 44 get help Post a request for help on a response agencys 52 Facebook page 35 Send a direct message via Twitter to a response 18 agency requesting help 28 0 20 40 60 80 % extremely/very likelyTaylor 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 1170people, with a more uncontrolled sample sent out via social media (so predominantly, if not entirely, based on people who use social media) 20 | CSIRO – Information Sharing for Emergency Management
  • CSIRO’s Enhanced Situation Awareness 21 | CSIRO – Information Sharing for Emergency Management
  • Capture22 | CSIRO – Information Sharing for Emergency Management
  • Capture23 | CSIRO – Information Sharing for Emergency Management
  • Detection and AlertingProblem : Crisis coordinators need tools tomanage issues arising from Tweet delugeSolution : Alerts generated by our systemare shown as a tag cloud. Alert colour andsize indicates deviation from expected.Alerts are linked to clusters. Mouse click onalert 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. 24 | CSIRO – Information Sharing for Emergency Management
  • Detecting and Alerting - Earthquakes• When you dont 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 26 | CSIRO – Information Sharing for Emergency Management
  • Condensing and Summarising27 | CSIRO – Information Sharing for Emergency Management
  • Forensic Analysis Comparing alerts with other knowledge 28 | CSIRO – Information Sharing for Emergency Management
  • Agenda1. Introduction2. All Hazards/End-to-End Initiative3. Case Studies • Social Protection • Enhanced Situational Awareness • Dynamic Flood Modelling4. ConclusionBig Spatial Data for Disaster Management | November2012
  • 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 Dam Wall PERTH CBD 39 km
  • 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 harbourThe approach of the tsunami towards Fremantle harbour is simulatedusing the SW solver. A wave train with a maximum amplitude of 3 m is used asthe tsunami source approximately 50 km offshore. The wave originates froman earthquake source close to Sumatra.
  • tsunami approach to Fremantle harbourThe approach of the tsunami towards Fremantle harbour is simulatedusing the SW solver. A wave train with a maximum amplitude of 3 m is used asthe tsunami source approximately 50 km offshore. The wave originates froman earthquake source close to Sumatra.
  • tsunami run-up and inundationTerrain resolution = 5 mFluid resolution = 2 mTerrain particles = 800KFluid particles = 2 milionWave height = 7 mWave speed = 10 m/sRun-up distance = 1.5 km 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.
  • tsunami run-up and inundationTerrain resolution = 5 mFluid resolution = 2 mTerrain particles = 800KFluid particles = 2 milionWave height = 7 mWave speed = 10 m/sRun-up distance = 1.5 km 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.
  • Agenda1. Introduction2. All Hazards/End-to-End Initiative3. Case Studies • Social Protection • Enhanced Situational Awareness • Dynamic Flood Modelling4. ConclusionBig Spatial Data for Disaster Management | November2012
  • ConclusionsDisaster management is a spatio-temporal, big data problemCSIRO sees value in the all hazards, end-to-end approachA robust spatial data infrastructure is essentialCSIRO is keen to collaborate with other organisations using commondata and decision support frameworksNew developments such as crowd sourcing add value and can beincorporatedToday we have released a report available at:http://www.csiro.au/disaster-management-report
  • Any Questions