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

Slides:



Advertisements
Similar presentations
INPE - National Institute for Space Research OBT - Earth Observation Coordination São José dos Campos - SP - Brazil.
Advertisements

DS-01 Disaster Risk Reduction and Early Warning Definition
May 9, Subgroup 4: Management of forests and forest-influenced landscapes Konstantin von Teuffel and Hubert Sterba.
From GIS-20 to GIS-21: The New Generation Gilberto Câmara, INPE, Brazil Master Class at ITC, September 2008.
We now have a Geo-Linux. What’s next? Gilberto Câmara National Institute for Space Research (INPE), Brazil Institute for Geoinformatics, University of.
Modelling Human-Environment Interactions with TerraME Gilberto Câmara (INPE) Tiago Carneiro (UFOP) Pedro Andrade Neto (INPE) Licence: Creative Commons.
Spatial Data Analysis: Course Outline Ifgi, Muenster, Fall School 2005 Gilberto Câmara INPE, Brazil.
Gilberto Camara, Max J. Egenhofer, Karine Ferreira, Pedro Andrade, Gilberto Queiroz, Alber Sanchez, Jim Jones, and Lubia Vinhas image: INPE Fields as a.
Are we ready for REDD? Multidimensional policies for reducing Amazon deforestation: Gilberto Câmara Director, National Institute for Space Research.
Biofuel production in Brazil: challenges for land use policy Gilberto Câmara Dialogo Brasil-Alemanha de Ciencia e Inovação Licence: Creative Commons ̶̶̶̶
1 EnviroGrids: Building Capacity for a Black Sea Catchment Observation and Assessment System supporting Sustainable Development Nicolas.
CPSC 695 Future of GIS Marina L. Gavrilova. The future of GIS.
C ONTRIBUTIONS TO A THEORY OF GEOGRAPHICAL INFORMATION ENGINEERING Scientific colloquium in honour of Prof. Andre U. Frank Vienna, 2008 Gilberto Câmara.
What is Health Geomatics? Dr. Bob Maher Senior Research Scientist Applied Geomatics Research Group Nova Scotia Community College Middleton, NS October.
Working at a global scale: challenges for a worldwide tropical forest monitoring system Gilberto Câmara General Director National Institute for Space Research.
ABCD-GIS and ABCD-WWW combined meeting Survey of Web Mapping Projects January 19 th, 2011.
Introduction to the course January 9, Points to Cover  What is GIS?  GIS and Geographic Information Science  Components of GIS Spatial data.
Gilberto Câmara National Institute for Space Research (INPE), Brazil
Studying Geography The Big Idea
Tips and Tricks for Using GIS in the Classroom Teaching with New Geoscience Tools Visualizations, Models, and Online Data Feb 10-12, 2008 University of.
Foundation for Space Science, Technology and Applications Vanildes Ribeiro - System Analyst – FUNCATE -
Modelling Human-Environment Interactions: Theories and Tools Gilberto Câmara Licence: Creative Commons ̶̶̶̶ By Attribution ̶̶̶̶ Non Commercial ̶̶̶̶ Share.
Databases and Global Environmental Change: Information Technology for Sustainable Development Gilberto Câmara INPE, Instituto Nacional de Pesquisas Espaciais.
How to include Human Actions in Earth System Science Modelling? Gilberto Câmara Earth System Science Centre, INPE Workshop.
I’ve found the data; it’s free and open access. Now what? Gilberto Câmara National Institute for Space Research (INPE) Brazil.
INPE´s contribution to REDD Capacity Building: data, applications, and software Gilberto Câmara Director General National Institute for Space Research.
MNV/RL 1 Developing historic land cover databases The BIOME 300-experience Prof. Dr. Rik Leemans [ Dutch Institute of Public Health.
BY:- RAVI MALKAT HARSH JAIN JATIN ARORA CIVIL -2 ND YEAR.
Planning for Arctic GIS and Geographic Information Infrastructure Sponsored by the Arctic Research Support and Logistics Program 30 October 2003 Seattle,
 The textbook GIS methods section: Provides basic understanding of GIS concepts What is RS? How can we use RS for GIS, when, where and why?
Beyond OGC Standards: The New Challenges for Open Source GIS Gilberto Câmara Director General, National Institute for Space Research (INPE) Brazil OGRS.
Core Concepts of Geoinformatics: introdcution Gilberto Camara National Institute for Space Research, Brazil Institut für Geoinformatik, Univ Münster.
The Implementation of Land and Ecosystem Accounts in Europe Towards integrated land and ecosystem accounting Roy Haines-Young, University of Nottingham.
1 Land Cover Land Use Change Program and LBA Dr. Garik Gutman LCLUC Program Manager NASA Headquarters.
Mondays, 3:00-3:50 p.m. Wilkinson credit Geo 507 Virtual Seminar in Geographic Information Science.
Data-intensive Geoinformatics: using big geospatial data to address global change questions Gilberto Câmara GIScience 2012 Workshop on Big Data Licence:
Chapter 1 – A Geographer’s World
From Virtual Globes to Open Globes Gilberto Câmara (INPE, Brazil)
Trends in Amazon land change Gilberto Câmara National Institute for Space Research Brazil
Transparency builds governance Gilberto Câmara National Institute for Space Research (INPE) Brazil GEO Data Sharing WG,
Case-Based Reasoning for Eliciting the Evolution of Geospatial Objects Joice Mota, Gilberto Camara, Isabel Escada, Olga Bittencourt, Leila Fonseca, Lúbia.
Databases and Global Environmental Change Gilberto Câmara Diretor, INPE.
The CBERS satellite, data policy and social benefits Gilberto Câmara Director, National Institute for Space Research GEO Capacity Building Workshop, May.
Breakout Session IV: Applying Remote Sensing Observations to Impacts Assessment Background (1) The IPCC WG 2 Report (2008) “Climate Change Impacts, Adaptation.
Inter-American Institute for Global Change Research an intergovernmental organization for global change research socio-economic implications international.
Global climate system - link together many of the topics on the basis of the most recent modeling for future trends Climate patterns - short-term time.
What is Global Environmental Change? Changes in the biogeophysical environment caused or strongly influenced by human activities Land cover & soils Atmospheric.
GEOSS: the view from the South Gilberto Câmara Director, National Institute for Space Research Brazil.
Designing a Global Interoperable Information Network Gilberto Câmara National Institute for Space Research, Brazil Eye on Earth Summit, Abu Dhabi, 2011.
The challenge of global environmental monitoring Gilberto Câmara, Director General National Institute for Space Research (INPE) Brazil China Brasil High.
Space derived geospatial data for sustainable development Gilberto Câmara National Institute for Space Research (INPE) Brazil
Introduction to Enviromental Modelling Lecture 1 – Basic Concepts Gilberto Câmara Tiago Carneiro Ana Paula Aguiar Sérgio Costa Pedro Andrade Neto.
Monitoring Tropical Forests and Agriculture: the Roadmap for a Global Land Observatory Gilberto Câmara National Institute for Space Research (INPE), Brazil.
NOAA Climate Program Office Richard D. Rosen Senior Advisor for Climate Research CICS Science Meeting College Park, MD September 9, 2010.
Splinter Session 1a : Identify topics Europe would like to have included in the GEO WP Chair: Luigi Fusco, ESA Reporting: Luca Demicheli, EuroGeoSurveys.
E-Sensing: Big Earth observation data analytics for land use and land cover change information.
Global Positioning Systems (GPS) A system of Earth-orbiting satellites which provides precise location on the earth’s surface in lat./long coordinates.
World Geography Chapter 1. The Study of Geography Section 1.
Mining Changing Patterns in Satellite Image Time Series Thales Sehn Korting
“Building public good instituions in emerging nations” Gilberto Câmara Director, National Institute for Space Research Brazil
Remote Sensing Dr. Ahmad BinTouq GEO440: GIS for Urban & Regional Planning.
CYBER-GIS FOR SCIENTIFIC DISCOVERIES. Global Forest Change Hansen, M. C. et al (2013). High-Resolution Global Maps of 21st-Century Forest Cover Change.
Chapter 1 – A Geographer’s World
USGS EROS LCMAP System Status Briefing for CEOS
Food and Nutrition Security and Agriculture
Environmental Intelligence Platform – Monitoring Nutrients Pollution with Earth Observation Data for Sustainable Agriculture and Clean Waters Blue.
The e-sensing architecture for big Earth observation data analytics
Potential Landsat Contributions
Spatio-temporal information in society: global change
Spatio-temporal information in society: land change
Presentation transcript:

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

We need cooperation at a global level… By ,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

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?

source: Global Land Project Science Plan (IGBP)

From land cover to land use Soybeans Pasture Abandoned Land

Land change is crucial for the world

Changes in dietary patterns: Meat consumption FAOSTAT 2007

Productivity and prices: the challenge source: The Economist

The food challenge source: Nature

The food challenge: technology gaps source: The Economist

Forests and food production: potential conflicts

Slides from LANDSAT 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?

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

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”

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

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

GIS-20: Object-oriented modelling Egenhofer, M. and A. Frank (1992). "Object-Oriented Modeling for GIS." URISA Journal 4(2): 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

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

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)

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

TerraAmazon – open source software for large-scale land change monitoring Spatial database (PostgreSQL with vectors and images) : 5 million polygons, 500 GB images

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

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

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

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

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

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

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

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

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

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

32 Land Use Change by Sugarcane expansion source: INPE

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

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

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.

Resilience Concepts for spatial dynamical models Events and processes

degradation Concepts for spatial dynamical models vulnerability

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

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

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)

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

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

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

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]

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

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

TerraME: Computational environment for developing human-environment models Cell Spaces Support for cellular automata and agents [Carneiro, 2006]

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

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

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