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Natural Disaster Monitoring and Alert System

Natural Disaster Monitoring and Alert System. Using Sensors to Save Lives Laércio M. Namikawa – Eymar Lopes Bilateral Research Workshop INPE – ifgi March 2009. Natural Disaster Monitoring and Alert System. SIStema de Monitoramento e Alerta de DEsastres Naturais. www.dpi.inpe.br/sismaden.

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Natural Disaster Monitoring and Alert System

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  1. Natural Disaster Monitoring and Alert System Using Sensors to Save Lives Laércio M. Namikawa – Eymar Lopes Bilateral Research Workshop INPE – ifgi March 2009

  2. Natural Disaster Monitoring and Alert System SIStema de Monitoramento e Alerta de DEsastres Naturais www.dpi.inpe.br/sismaden Version 1.0 Version 2.0 Released July/11/2008 July/2009

  3. Natural Disasters in Brazil Forest fires Flooding Droughts Landslides Forest fires Flooding Flooding Landslides Flooding High winds Hail storms 12 Oil refineries 4 Petrochemical Complexes reference: Adapted from GEO BRASIL 2002 - Perspectivas do Meio Ambiente no Brasil – Edições Ibama, 2002.

  4. Natural Disasters in BrazilSanta Catarina – Nov. 2009

  5. Natural Disasters in BrazilSanta Catarina – Nov. 2009

  6. Natural Disasters in BrazilSanta Catarina – Nov. 2009

  7. Natural Disasters in Brazil Extreme temperature High winds Droughts Floods Epidemic Landslides Source (adpated): Vulnerabilidade Ambiental / Rozely Ferreira dos Santos, organizadora. – Brasilia: MMA, 2007. 192 p. : il. color. ; 29 cm.

  8. Center for Weather Forecast and Climate Studies www.cptec.inpe.br

  9. CPTEC Weather Forecasts

  10. CPTEC Weather Forecasts

  11. CPTEC ObservationsSatellite

  12. CPTEC ObservationsRadar

  13. CPTEC ObservationsData Collection Platforms

  14. CPTECAlerts Civil Defense is notified when forecast indicates that intense or long lasting rain has potential to trigger natural disastres National Secretariat for Civil Defense Emergency Actions For Preparation and Mitigation in States and Municipalities State Coordination for Civil Defense- SP CPTEC Regional and Municipalities Civil Defenses

  15. Technological Support Geographical database and spatial operation by TerraLib: www.terralib.org

  16. Automatically Generated Alerts Natural Disasters Risks Hidrology and Meteorology Observations and Forecasts Risk Areas Spatial Analysis Extreme Event Alerts Additional Information

  17. SIStema de Monitoramento e Alerta de DEsastres NaturaisNatural Disaster Monitoring and Alert System Open Source Computational System based on service oriented architecture Provides technological infrastructure to develop operational systems to manage alerts of environmental risks Services: Data gathering and formatting Analysis by comparison with risk layers or by executing models Risk model edition for alerts Alert handling and management

  18. Natural Disasters Monitoring and Alert System

  19. Configuration Interface Register data servers and sources Register risk maps and base maps Program analysis Register users and permissions

  20. Configuration Interface Main Menu Climate data Risk Maps Base Maps Analyses Users Add Server

  21. Configuration Interface Data from CPTEC CPTEC Server DCP Satellite/Radar Models ETA 40, 20, 5 Km Ensemble 40 Km Total rain 72h 72 files ASCII grid file Rain total Fixed time and irregular – alert Point data One file per DCP Grid 4km Total rain 1h Total rain 24h Current (mm/h) Binary file

  22. Configuration Interface Hidrometeorological Servers ftp://150.163.133.245/ c:\data\grids FTP File Rain/bingrd

  23. Configuration Interface Hydrometeorological Data Series • Grids • Hydroestimator • Lightning • Radar • Forecast Models • Points • DCPs (data collection platforms)

  24. Configuration Interface Hydrometeorological Grid Data Series Forecasted Total Others ASCII-GRID PCD TIFF GrADS Radar.%a%M%d.%h%m.tif

  25. Configuration Interface Hydrometeorological Grid Data SeriesNew Version Extreme event threshold Save storage and analysis Area clipping Storage strategy Delete unnecessary data New formats Cumulative data. Ex: File with rain for every hour during forecast period (72 hours)

  26. Configuration Interface Point Data Series - DCPs DCP Pre calculation of data series DCPs Location

  27. DCPs Point Data Series Configuration Interface Collect Rules by Luawww.lua.org Pre calculation of new value to be used in the analysis

  28. Configuration Interface Register risk maps and base maps Risk layers Areas (polygons) + attributes describing the risk Base map layers - Vector or grid layers supporting visualization in alert situations Included in database through www.dpi.inpe.br/terralib

  29. Configuration Interface Risk Maps Polygons with attributes that specify risk levels

  30. Configuration Interface Programming the Analysis User analysis and risk model programming by Luawww.lua.org

  31. Configuration Interface Risk Analyses Analysis

  32. Configuration Interface Analysis Types Using risk maps Executes analyses by areas in risk maps overlaid on hidrometeorological creating alerts in these areas. Model based Ex: SINMAP (Stability INdex MAPping) c – Coesion; β- Slope angle; φ- Soil internal friction; R/T- Reload/transmissivity ratio; a- Watershed area

  33. Configuration Interface Analysis Based on Risk Maps Risk Layers Climate Data

  34. Configuration Interface Analysis Based on Risk Maps • LUA programming language • LUA operators: arithmetic: + - * / ^ relational: == ~= < > <= >= logical: and or notmathematical: math.abs math.acos math.asin math.atan …. • TerraLib operators: • zonals: maximo minimo media conta_amostras • historical: operador_historico • grid: amostra

  35. Configuration Interface Example - Risk Model Using Hydrometeorological Data in a Grid local ca = maximo(‘total rain')if ca < limiar_cathenreturn 0 -- Okelseif ca < limiar_ca * 1.2 thenreturn 2 – Attention levelelsereturn 4 – Maximum Alert levelend

  36. Configuration Interface Example - Risk Model Using Point Data (DCPs) local rain = media(‘dcp_data’,'pluvio')if rain == nil then rain = media('rain_grid')end if rain < threshold thenreturn 0 -- Okelseif rain < threshold * 1.2 thenreturn 2 – Attention levelelsereturn 4 – Maximum alert levelend

  37. Configuration Interface Model Based Analysis Output Grid Climate Data

  38. Configuration Interface Model Based Analysis local slope = amostra('slope_grid')local rain = amostra(‘rain_grid') local c= 0.37, B= 34, T=0.00034 return FS = (c*cos^2.slope(1-(rain*a)/T *sin.slope)r )tan.B)/ sin.slope amostra – value at evaluation location on grid

  39. Configuration Interface Risk AnalysesNew Version Use grids in addition to polygons to define risk areas Define influence areas of DCPs Classify analyses as active, inactive, and conditional (activated by another analysis)

  40. Configuration Interface Risk AnalysesStretched Version Functions to validate DCPs data External simulation activated by a risk analysis TerraME program, FORTRAN program, Hidrological modeling Integration with TerraME, TerraHidro TerraHidro – Process Models on generalized flows

  41. Configuration Interface Alert and Base Map Overlay

  42. Configuration Interface Register Users and Analysis Based Permissions

  43. Configuration Interface Register Users for Each Analysis Analysis based Permissions

  44. Presentation Interface Users access alerts on internet through login (password required) Visualize current analysis Visualize risk polygons attributes Visualize a polygon risk history

  45. Presentation Interface WEB Main Interface - TerraPHP

  46. Presentation Interface Alert Information

  47. Presentation Interface Alert Events per Region

  48. Conclusions Processes extremes captured by risk analyses Vulnerabilities Processes values captured by images and DCPs Easy programming (non-experts) of input processing and risk analysis Data availability, censorship

  49. Future Developments Capturing processes relevant changes Validation of DCPs data for a given process Finding and filling gaps in data Using randomly available data Collaborative data: Mobile phone (GPS, images, videos), web cam Use of OGC Sensor Observation Service standard

  50. DCPs Errors

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