Spatio-Temporal Database Constraints for Spatial Dynamic Simulation

Bianca Maria PedrosaLuiz Camolesi Júnior

Gilberto CâmaraMarina Teresa Pires Vieira

INPE

UNIMEP

Outline

Spatial dynamic systems TerraML computational environment Variability in simulation process A land-use change application

Spatial dynamic systems

f ( I (tn ))

. . .FF

f ( I (t) ) f ( I (t+2) )f ( I (t+1) )

Spatial dynamic systems simulates spatio-temporal processes in which the state of a location, on the Earth´s surface, changes over time, due to some physical phenomena.

tp - 20 tp - 10

tp

calibration calibrationtp + 10

ForecastForecast

Dynamic spatial models

fonte: Almeida et al (2003)

Spacial dynamic system elements

Transition Rules

FuzzyL(Clue)Expander(Dinâmica)

LocalMean (Riks)

Models

discretehybrid

continuous

DinâmicaRiks

Clue

Space representation

Neighborhood

Celli+1,,j

Celli,j

Celli+1,j+1

Celli,j+1

modelo celular

obj1

obj2

obj1 obj2

1

0

0

1

Spacial dynamic system elements

uniform proprieties regular structure

proximitry matrixnon stationary

TerraML

Cell-based modeling languageTerraLib Modeling Language

Hybrid Automata Temporal database constraints

control mode control mode

jump condition

flow condition

New

Constraints

Transitions are processes representing evolution and therefore subject to constraints, which are preconditions to limit, avoid or force a change

Variability is a feature to establish the possibility and the change limits of objects

Variability is associated to object attributes or processes to model the structural, functional and behavioral characteristics of elements in real world

Variability in simulation process

Invariant– Defined to attributes that cannot be

changed– Are used to represent immutable or stable

characteristics

Variant– Defined to attributes whose alterations are

highly provable – Support Evolution, involution or revolution of

object or processes

Dimensioning the limits

Moment– A time instant value

Granularity– Precision domain of time instant (ISO 2000)

Orientation– Reference system (Gregorian calendar)

Direction– All orientation has a origin moment and everything

happens after or before this moment (UTC)

Application– The use of temporal representation, allowing the

semantic recognition of the time datatype

Expressing Variability conditions

M in I

M before I

M after I

M after I

M before I

time

M I

time

IM

time

I M

M

time

I

M I

time

TerraML Schema

TerraML Schema

TerraML Schema

A land use change applicattion

A land use change applicattion

GLOBAL LOCAL

Demand > 0

Potential >0

Global mode (for all cells)– Calculate/update the Demand in each time step– Calculate/update the Global Demand in each time step

Local mode (for each cell)– Calculate the cell´s potencial for change– Select/alocate cells to change, based on demand

Local mode equations

2tan__1

11

cedisroadmainAccess ij

)*2(*)*1(*)*( ijijijij AccessAccessyAtractivitPotencial

jijiij wyAtractivit ,,

2tan__sec1

12

cedisroadondaryAccess ij

TerraML script

<cellprocessor author="bianca" date="11/08/04" model=“geoinfo" >

<input>

<database host="localhost" path="c:/tese_dados/"

name="rondonia.mdb" user="" pass="“

/>

<layer name="celulas450" layerid="46"/>

<table name="celulas450_dinamica" columns="35"

lines="70"/>

<neighborhood name="c:/tese_dados/vizinho1.txt" zones="1"/>

<global name="total_demand" value="700"/>

<global name="demand" value="0"/>

</input>

TerraML script

<control initime="1985" intervals="16" step="1" timeUnit="year">

<mode name="GLOBAL">

<constraint <inv attribute = “florest reserve” value = “1” /> <var attribute = “owner” value = “Federal” inittime = “1986” finaltime=”1990” /> </constraint >

<temporal attribute="demand" value="0.0625" inittime = “1986” finaltime=”1990” /> <temporal attribute="demand" value="0.0625" inittime = “1991” finaltime=”1995” /> <temporal attribute="demand" value="0.0625” inittime = “1996” /> </mode>

<mode name=“LOCAL”

TerraML script

<fuzzyL attribute="acessibility" column=”road_distance” alpha="0.001" beta="500" /> <localMean attribute="atractivity" column="land_cover"/>

<product attribute="potential"> <pair attribute="acessibility" weight="0.8"/> <pair attribute="atractivity" weight="0.2"/> </product>

<expander attribute="land_cover" column="potential" demand="demand"/>

</mode>

<transition from="global" to="local"> <condition attribute="demand" op="GT" value="0"/></transition>

</control></cellprocessor>

1985 1988

1991 1994

Simulation result samples

Conclusion

The constraints model proposed is based on semantic representation of variability to transitions in simulations.

The model proposed support both variant and invariant conditions and seems to cover the most frequent situations in environment systems.

Future efforts will focus on extending constraints to support the orientation and direction aspects of time representation