2. N EW TRENDS IN G EOINFORMATICS IN A CHANGING WORLD Gilberto Câmara National Institute for Space Research, Brazil

3. We need cooperation at a global level… By 2050... 8,5 billion people: 6 billion tons of GHG and 60 million tons of urban pollutants. Resource-hungry: We will withdraw 30% of available fresh water. Risky living: 80% urban areas, 25% near earthquake faults, 2% in coast lines less than 1 m above sea level. source: Guy Brasseur

4. Global Change Where are changes taking place? How much change is happening? Who is being impacted by the change? Global Change: How is the Earth’s environment changing, and what are the consequences for human civilization?

5. source: Global Land Project Science Plan (IGBP)

6. From land cover to land use Soybeans Pasture Abandoned Land

7. Land change is crucial for the world

8. Changes in dietary patterns: Meat consumption FAOSTAT 2007

9. Productivity and prices: the challenge source: The Economist

10. The food challenge source: Nature

11. The food challenge: technology gaps source: The Economist

12. Forests and food production: potential conflicts

13. Slides from LANDSAT 197319872000 images: USGS Modelling Human-Environment Interactions How do we decide on the use of natural resources? What are the conditions favoring success in resource mgnt? Can we anticipate changes resulting from human decisions? What techniques and tools are needed to model human- environment decision making?

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

15. Why GI Engineering? Chemistry Chemical Eng. Physics Electrical Eng. Computer Computer Eng. Science GI Science GI Engineering GI Engineering= “The discipline of systematic construction of GIS and associated technology, drawing on scientific principles”

16. Scientists and Engineers Photo 51(Franklin, 1952) Scientists build in order to study Engineers study in order to build

17. What set of concepts drove GIS -20? Map-based (cartography) User-centered (user interfaces) Toblerian spaces (regionalized data analysis) Object-based modelling and spatial reasoning

18. GIS-20: Object-oriented modelling Egenhofer, M. and A. Frank (1992). "Object-Oriented Modeling for GIS." URISA Journal 4(2): 3-19. SPRING´s object-oriented data model (1995) ARCGIS´s object-centred data model (2002) Geo-object Cadastral Coverage Spatial database Categorical Geo-field Numerical Is-a contains

19. GIS-20: Topological Spatial Reasoning Egenhofer, M. and R. Franzosa (1991). "Point-Set Topological Spatial Relations." IJGIS 5(2): 161-174 OGC´s 9-intersection dimension-extended Open source implementations (GEOS)

20. GIS-20: User interfaces Jackson, J. (1990) Visualization of metaphors for interaction with GIS. M.S. thesis, University of Maine. Geographer´s desktop (1992) ArcView (1995)

21. GIS -20: Region-based spatial analysis SPRING´s Geostatistics Module GeoDA: Spatial data analysis

22. 166-112 116-113 116-112 TerraAmazon – open source software for large-scale land change monitoring Spatial database (PostgreSQL with vectors and images) 2004-2008: 5 million polygons, 500 GB images

23. shared analysis sensor networks mobile devices GIS-21 ubiquitous images Data-centered, mobile-enabled, contribution- based, field-based modelling

24. Data is coming... are we ready? Sentinel-2A 2012 Amazônia-1 2013 20142015 2011 Landsat-8 CBERS-3 ResourceSat-2 ResourceSat-3 Sentinel-2B CBERS-4

25. Data Access Hitting a Wall Current science practice based on data download How do you download a petabyte?

26. Data Access Hitting a Wall Current science practice based on data download How do you download a petabyte? You don’t! Move the software to the archive

27. 26 Virtual Observatory If data is online, internet is the world ’ s best telescope Scientific Data Management in the Coming Decade (Jim Gray)

28. Tracking Positions collected over a fixed period of time Monitoring Data from remote stations, fixed or mobile Sensor Webs source: ARGOS

29. Earth observation satellites and geosensor webs provide key information about global change… …but that information needs to be modelled and extracted

30. What´s in an Image? “Remote sensing images provide data for describing landscape dynamics” (Câmara, Egenhofer et al., COSIT 2001).

31. GIS-21: Spatio-temporal semantics Different types of ST-objects (source: JP Cheylan)

32. GIS-21: Discovering the history of land change objects Reconstructing the history of a landscape

33. 32 Land Use Change by Sugarcane expansion source: INPE

34. Sugarcane expansion source: Rudorff et al, Remote Sensing Journal (2010)

35. f ( I t+n ). FF f (I t )f (I t+1 )f (I t+2 ) GIS-21: Spatio-temporal modelling “A dynamical spatial model is a computational representation of a real-world process where a location on the earth’s surface changes in response to variations on external and internal dynamics on the landscape” (Peter Burrough) Dynamic Spatial Models need good conceptual models

36. Spatially-explicit LUCC models  Explain past changes, through the identification of determining factors of land use change;  Envision which changes will happen, and their intensity, location and time;  Assess how choices in public policy can influence change, by building different scenarios considering different policy options.

37. Resilience Concepts for spatial dynamical models Events and processes

38. degradation Concepts for spatial dynamical models vulnerability

39. Human-environmental models need to describe complex concepts (and store their attributes in a database) and much more… biodiversity Concepts for spatial dynamical models sustainability

40. Clocks, clouds or ants? Clocks: deterministic equations Clouds: statistical distributions Ants: emerging behaviour

41. Models: From Global to Local Athmosphere, ocean, chemistry climate model (200 x 200 km) Atmosphere only global climate model (50 x 50 km) Regional climate model (10 x 10 km) Hydrology, Vegetation Soil Topography (1 x 1 km) Regional land use change Socio-economic adaptation (e.g., 100 x 100 m)

42. 25 x 25 km 2 1 x 1 km 2 Human-enviroment models should be multi- scale, multi-approach [Moreira et al., 2008]

43. Multi-scale modelling using explicit relationships Express explicit spatial relationships between individual objects in different scales [Moreira et al., 2008] [Carneiro et al., 2008]

44. How can we express behavioural changes in human societies? Small Farmers Medium-Sized Farmers photos: Isabel Escada When a small farmer becomes a medium-sized one, his behaviour changes

45. Old Settlements (more than 20 years) Recent Settlements (less than 4 years) Farms Settlements 10 to 20 anos Societal systems undergo phase transitions Isabel Escada, 2003 [Escada, 2003]

46. Networks as enablers of human actions Bus traffic volume in São PauloInnovation network in Silicon Valley

47. Consolidated area GIS-21: Network-based analysis Emergent area Modelling beef chains in Amazonia

48. TerraME: Computational environment for developing human-environment models Cell Spaces Support for cellular automata and agents http://www.terrame.org [Carneiro, 2006]

49. TerraLib: spatio-temporal database as a basis for innovation Visualization (TerraView) Spatio-temporal Database (TerraLib) Modelling (TerraME) Data Mining(GeoDMA) Statistics (aRT)

50. RgeoR R data from geoR package. Loaded into a TerraLib database, and visualized with TerraView. R-Terralib interface

51. Managing change is a major challenge for the scientific community Images are a major source of new data Move the software, not the data We need new algebras, data representations and algorithms to handle spatio-temporal data Conclusions