From GIS20 to GIS21: A Vision for INPEs R

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From GIS-20 to GIS-21 A Vision for INPEs RD in
Geoinformatics

• Gilberto Câmara
• October 2008

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First, lets look at the big picture
LBA tower in Amazonia
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The fundamental question of our time
How is the Earths environment changing, and what
are the consequences for human civilization?
source IGBP
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Impacts of global environmental change By 2020 in
Africa, agriculture yields could be cut by up to
50
sources IPCC and WMO
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Global Change
Where are changes taking place? How much change
is happening? Who is being impacted by the
change?
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Global Earth Observation System of Systems
Vantage Points
Capabilities
L1/HEO/GEO TDRSS Commercial Satellites
Far-Space
Permanent
LEO/MEO Commercial Satellites and Manned
Spacecraft
Near-Space
Airborne
Aircraft/Balloon Event Tracking and Campaigns
Deployable
Terrestrial
User Community
Forecasts Predictions
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Earth observation satellites and geosensor webs
provide key information about global change
but that information needs to be modelled and
extracted
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How does INPEs research in Geoinformatics fits
in the big picture?
LBA tower in Amazonia
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Geoinformatics enables crucial links between
nature and society
Nature Physical equations Describe processes
Society Decisions on how to Use Earths
resources
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1986
1975
INPEs RD agenda in Geoinformatics modelling
change
1992
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Slides from LANDSAT
source USGS
Geoinformatics 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
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• Spatial segregation indexes

• Remote sensing image mining

INPEs strong point a combination of
problem-driven GI research and engineering

• GI software SPRING and TerraView

• Land change modelling

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GI Engineering from GIS-20 to GIS-21
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.
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Scientists and Engineers
Photo 51(Franklin, 1952)
Scientists build in order to study Engineers
study in order to build
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What set of concepts drove GIS-20?

• Map-based (cartographical user interfaces)
• Toblerian spaces (regionalized data analysis)
• Object-oriented modelling and spatial reasoning
• Spatial databases (vectors and images)

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GIS-20 Topological Spatial Reasoning
Egenhofer, M. and R. Franzosa (1991). "Point-Set
Topological Spatial Relations." IJGIS 5(2)
161-174

• OGCs 9-intersection
• dimension-extended

• Open source implementations (GEOS) used in
  TerraLib

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GIS-20 Map-like User interfaces
Jackson, J. (1990) Visualization of metaphors
for interaction with GIS. M.S. thesis,
University of Maine. G. Câmara, R.Souza,
A.Monteiro, J.Paiva, J.Garrido, Handling
Complexity in GIS Interface Design. I Brazilian
Symposium in Geoinformatics, GeoInfo 1999.
Geographers desktop (1992)
TerraView (2005)
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GIS -20 Region-based spatial analysis
MF Goodchild, A spatial analytical perspective
on GIS. IJGIS, 1987 L Anselin, I Syabri, Y Kho,
GeoDa An Introduction to Spatial Data
Analysis, Geographical Analysis, 2006. R Bivand,
E Pebesma, V Gómez-Rubio, Applied Spatial Data
Analysis with R. Springer-Verlag, 2008.
SPRINGs Geostatistics Module
GeoDA Spatial data analysis
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GIS-20 Object-oriented modelling
G.Câmara, R.Souza, U.Freitas, J.Garrido, F. Ii.
SPRING Integrating Remote Sensing and GIS with
Object-Oriented Data Modelling. Computers and
Graphics, vol.15(6)13-22, 1996.

• SPRINGs object-oriented
• data model (1995)

• ARCGISs object-centred
• data model (2002)

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GIS-20 Image and geospatial databases
R.H. Güting, An Introduction to Spatial Database
Systems. VLDB Journal, 1994. L Vinhas, RCM
Souza, G Câmara, Image Data Handling in Spatial
Databases. Brazilian Symposium in
Geoinformatics, GeoInfo 2003. G. Câmara, L.
Vinhas, et al.. TerraLib An open-source GIS
library for large-scale environmental and
socio-economic applications. In B. Hall, M.
Leahy (eds.), Open Source Approaches to Spatial
Data Handling. Berlin, Springer, 2008.

• TerraAmazon- A Large Environmental Database
  Developed on TerraLib and PostgreSQL

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GIS-21

• augmented reality

• mobile devices

• Data-centered, mobile-enabled, contribution-based,
  field-based modelling

• sensor networks

• ubiquitous images and maps

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GIS-21 Functional Programming
Frank, A. (1999). One Step up the Abstraction
Ladder Combining Algebras From Functional
Pieces to a Whole. COSIT 99 S. Costa, G. Camara,
D. Palomo, TerraHS Integration of Functional
Programming and Spatial Databases for GIS
Application Development, GeoInfo 2006.
class Coverage cv where evaluate cv a b ? a
? Maybe b domain cv a b ? a num
cv a b ? Int values cv a b ? b
Geospatial data processing is a collection of
types and functions Functional programming
allows rigorous development of GIS
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GIS-21 Mobile Objects
R.H. Güting and M. Schneider, Moving Objects
Databases. Morgan Kaufmann Publishers, 2005.
R.H. Güting, M.H. Böhlen, et al., A Foundation
for Representing and Querying Moving Objects.
ACM Transactions on Database Systems, 2000.
source Barry Smith
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GIS-21 Spatio-temporal semantics
P Grenon, B Smith, SNAP and SPAN Towards
Dynamic Spatial Ontology. Spatial Cognition and
Computation, 2004. A Galton, Fields and Objects
in Space, Time, and Space-time. Spatial
Cognition and Computation, 2004.
Different types of ST-objects (source JP Cheylan)
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GIS-21 Information Extraction from Images
M. Silva, G.Câmara, M.I. Escada, R.C.M. Souza,
Remote Sensing Image Mining Detecting Agents of
Land 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
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GIS-21 Dynamical spatial modellingwith Agents
in Cell Spaces
Tiago Garcia de Senna Carneiro, "Nested-CA A
Foundation for Multiscale Modelling of Land Use
and Land Cover Change. PhD Thesis, INPE, june
2006
TerraME Based on functional programming
concepts (second-order functions) to develop
dynamical models
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GIS-21 Dynamical modelling integrated in a
spatio-temporal database
G. Câmara, L. Vinhas, G. Queiroz, K. Ferreira,
A.M.V. Monteiro, M. Carvalho, MA Casanova.
TerraLib An open-source GIS library for
large-scale environmental and socio-economic
applications. In B. Hall, M. Leahy (eds.),
Open Source Approaches to Spatial Data
Handling. Berlin, Springer, 2008.
Spatio-temporal database
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GIS-21 Dynamical modelling integrated in a
spatio-temporal database
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GIS-21 Networks as enablers of human actions

• Bus traffic volume in São Paulo

• Innovation network in Silicon Valley

Ana Aguiar, Gilberto Câmara, Ricardo Souza,
Modeling Spatial Relations by Generalized
Proximity Matrices. GeoInfo 2003
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GIE-21 Network-based analysis
Emergent area
Consolidated area

• Modelling beef chains in Amazonia

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Modelling changefrom practice to theory
Outiline of a theory for change modelling in
geospatial data
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• What algebra is needed for spatio-temporal data?
• How can this algebra be handled in an
  geographical databases?

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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
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Identity conditions on ST data

• Average temp for IPCC scenarios

• Continuous fields (x,y,z,t)

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Identity conditions on ST data
land_cover cells in 1985
land_cover cells in 2000
Individual objects (id, t,(x,y,z))
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Identity conditions on ST data Images
M. Silva, G.Câmara, M.I. Escada, R.C.M. Souza,
Remote Sensing Image Mining Detecting Agents of
Land 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
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Identity conditions on ST data Images
Landsat Image 13/Ago/2003
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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)
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Identity conditions on ST data Images
Deforestation on 21/May/2004
Deforestation in 13/Aug/2003 (yellow)
deforestation from 13/Aug/2003 until 07/May/2004
(red) deforestation on 21/May/2004 (orange)
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Identity conditions have uncertain cases!
Furacão Catarina (março/2004) Imagem NASA
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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
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Slides from LANDSAT
snap (1973)
snap (1987)
snap (2000)
Aral Sea
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)
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Sensors sources of continuous information
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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
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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
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Evolving (modifiable) object
life I ? (T ? (S,V)) The function life produces
the evolution of a modifiable object
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A lifes trajectory
life I ?(T?(S,V)) The life of the object is
also a trajectory
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Which objects are alive at time T and where are
they?
exist T ? (I?(S,V))
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Models From Global to Local
Athmosphere, ocean, chemistry climate model
(resolution 200 x 200 km) Atmosphere only
climate model (resolution 50 x 50 km) Regional
climate model Resolution e.g 10 x 10
km Hydrology, Vegetation Soil Topography (e.g, 1
x 1 km) Regional land use change Socio-economic
changes Adaptative responses (e.g., 10 x 10 m)
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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
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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 instancet
has-a
location
T-fields have snapshots
T-objects have histories
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INPEs vision for modelling change
Combine GI science and engineering to produce a
new generation of dynamical models integrated in
a spatio-temporal database
f (It)
f (It1)
f (It2)
f ( Itn )
F
F
. .