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Databases and Global Environmental Change

Databases and Global Environmental Change. Gilberto Câmara Diretor, INPE. The fundamental question of our time. How is the Earth’s environment changing, and what are the consequences for human civilization?. source: IGBP. Earth is a system of systems.

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Databases and Global Environmental Change

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  1. Databases and Global EnvironmentalChange Gilberto Câmara Diretor, INPE

  2. The fundamental question of our time How is the Earth’s environment changing, and what are the consequences for human civilization? source: IGBP

  3. Earth is a system of systems Humanactions are changingthe balance!

  4. Earth as a system

  5. Impacts of global environmental change By 2020 in Africa, agriculture yields could be cut by up to 50% sources: IPCC and WMO

  6. Precipitation anomalies [(2071-2100)- (1961-90)] in mm/day Seco Seco Seco Seco B2 A2 Climate change scenarios in Brazil Quente Quente B2 A2 Temperature anomalies [(2071-2100)- (1961-90)] in oC

  7. Averagetempraised 0,7 C in 50 years in Brazil Tmin up 1 C! Source: (Obregón e Marengo, 2007)

  8. ImpactsonAgriculture Fonte: Eduardo Assad, Embrapa

  9. Collapse of Amazon Rain Forest? 2100 2000 savanna pastures forest caatinga desert Is there a tipping point for Amazonia? source: Oyama and Nobre, 2003

  10. ImpactsonWaterAvailability in NE Brazil Hidrological Balance – NE Brazil 1961-1990 LessWater for Agriculture! 2071-2100 Source: Marengo and Salati, 2007

  11. Amazônia in 2005 source: Greenpeace

  12. Amazônia in 2015? fonte: Aguiar et al., 2004

  13. Great challenge:Database support for earth system science source: NASA

  14. Global Change Where are changes taking place? How much change is happening? Who is being impacted by the change?

  15. Global Land Project • What are the drivers and dynamics of variability and change in terrestrial human-environment systems? • How is the provision of environmental goods and services affected by changes in terrestrial human-environment systems? • What are the characteristics and dynamics of vulnerability in terrestrial human-environment systems?

  16. Data chain in Earth System Science fonte: NASA

  17. INPE´s supercomputersandworld´s TOP 500 #1 trend Sum top 500 150 TF #500 trend 5 TF 2 TF 40 GF INPE (MPP equivalent peak performance) 8 GF

  18. CO2 Emissions B1-low Earth System Science Data Handling PetaFlop Centres LargeScale Data Megascenarios Índice de Vegetação Regional Centers Regional Scenarios PolicyOptions

  19. Global Earth Observation System of Systems Capabilities Vantage Points L1/HEO/GEO TDRSS & Commercial Satellites Far-Space Permanent LEO/MEO Commercial Satellites and Manned Spacecraft Near-Space Aircraft/Balloon Event Tracking and Campaigns Airborne Deployable Terrestrial User Community Forecasts & Predictions

  20. 11,000 land stations (3000 automated) 900 radiosondes, 3000 aircraft 6000 ships, 1300 buoys 5 polar, 6 geostationary satellites Weather and climate source: WMO

  21. ARGOS Data Collection System (16000 plats) 650,000 messages processed daily

  22. Data collection services Tracking Positions collected over a fixed period of time Monitoring Data from remote stations, fixed or mobile

  23. Argo bouy network

  24. I amtheWalrus

  25. Models: From Global to Local Athmosphere, ocean, chemistryclimatemodel (resolution 200 x 200 km) Atmosphereonlyclimatemodel (resolution 50 x 50 km) Regional climatemodel (resolutione.g 10 x 10 km) Hydrology, Vegetation SoilTopography (e.g, 1 x 1 km) Regional land use change Socio-economicchanges Adaptativeresponses (e.g., 10 x 10 m)

  26. Data integration enables crucial links between nature and society Nature: Physical equations Describe processes Society: Decisions on how to Use Earth´s resources

  27. mobiledevices augmented reality ST DBMS-21 Data-centered, mobile-enabled, contribution-based, field-basedmodelling sensor networks ubiquitousimagesandmaps

  28. source: USGS Slides from LANDSAT Databases and Change: A Research Programme Understanding how humans use space Predicting changes resulting from human actions Modeling the interaction between society and nature Aral Sea 1973 1987 2000 Bolivia 1975 1992 2000

  29. How can DBMS technology handle Earth System Science data? What algebra is needed for spatio-temporal data? How can this algebra be handled in an object-relational DBMS?

  30. Identityconditionson ST data Averagetemp for IPCC scenarios Continuousfields (x,y,z,t) Continuousfields (x,y,z,t)

  31. Identityconditionson ST data land_covercells in 1985 land_covercells in 2000 Individual objects (id, {t,{(x,y,z)}})

  32. Identityconditionson ST data: Images M. Silva, G.Câmara, M.I. Escada, R.C.M. Souza, “RemoteSensingImageMining: DetectingAgentsofLand Use Change in Tropical Forest Areas”. International Journal of Remote Sensing, vol 29 (16): 4803 – 4822, 2008. “Remotely sensed images are ontologically instruments for capturing landscape dynamics”

  33. Identity conditions on ST data: Images LandsatImage 13/Ago/2003

  34. Identity conditions on ST data: Images Deforestation 13/Ago/2003 until 07/Mai/2004 Deforestation in 13/Aug/2003 (yellow) + deforestation from 13/Aug/2003 until 07/mai/2004 (red)

  35. Identity conditions on ST data: Images Deforestation on21/May/2004 Deforestation in 13/Aug/2003 (yellow) + deforestation from 13/Aug/2003 until 07/May/2004 (red)+ deforestation on 21/May/2004 (orange)

  36. Identityconditionshaveuncertain cases! Furacão Catarina (março/2004) Imagem NASA

  37. Modelling change…from practice to theory Outiline of a theory for change modelling in spatio-temporal data

  38. What is a geo-sensor? What is a geo-sensor? Basic spatio-temporal types S: set of locations (space) T: set of intervals (time) I: set of identifiers (objects) V: set of values (attributes) measure (s,t) = v s ⋲ S - set of locations in space t ⋲ T - is the set of times. v ⋲ V - set of values

  39. What is a geo-sensor? What is a geo-sensor? Field (static) field : SV The function field gives the value of every location of a space measure (s,t) = v s ⋲ S - set of locations in space t ⋲ T - is the set of times. v ⋲ V - set of values

  40. snap (1973) snap (1987) snap (2000) Aral Sea Slides from LANDSAT Time-varying fields are modelled by snapshots snap : T  Field snap : T  (S  V) The function snap produces a field with the state of the space at each time. Bolivia snap (1975) snap (1992) snap (2000)

  41. Sensors: sources of continuous information

  42. Sensors: water monitoring in Brazilian Cerrado • Wells observation • 50 points • 50 semimonthly time series • (11/10/03 – 06/03/2007) Rodrigo Manzione, Gilberto Câmara, Martin Knotters

  43. Fixed sensors: time series (histories) Well 30 Well 40 Well 56 Well 57 hist: S (T  V) each sensor (fixed location) produces a time series

  44. Evolving (modifiable) object life: I  (T  (S,V)) The function life produces the evolution of a modifiable object

  45. A life´s trajectory life : I ⟶(T⟶(S,V)) The life of the object is also a trajectory

  46. Which objects are alive at time T and where are they? exist : T ⟶ (I⟶(S,V))

  47. Models: From Global to Local snap: T  (S  V) evolution of a landscape hist: S  (T  V) History of a location exist: T (I  (S,V)) objects alive in a time T life : I  (T  (S,V)) the life of an object in space-time

  48. A model for time-varying geospatial data.... set Temporal entity is-a is-a T-field (coverage set) T-object hist(oi) (feature) has-a snap(t) (coverage [t]) has-a Feature instance[t] has-a location T-fields have snapshots T-objects have histories

  49. ST DBMS as a basis for data integration Visualization (TerraView) Modelling (TerraME) Spatio-temporal Database (TerraLib) Statistics (aRT) Data Mining(GeoDMA)

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