A Language to Support Spatial Dynamic Modeling Bianca Pedrosa, Gilberto Câmara, Frederico Fonseca,...

A Language to Support Spatial Dynamic Modeling

Bianca Pedrosa, Gilberto Câmara, Frederico Fonseca,

Tiago Carneiro, Ricardo Cartaxo

Brazil’s National Institute for Space ResearchPennsylvania State University

TerraML

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TerraML Purpose

Support spatial dynamic modeling Discrete and continuous behavior Inhomogeneous space Extensible framework

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Outline

Requirements of a dynamic modeling environment

The TerraML computational environment

The TerraML theoretical foundations The TerraML structure and syntax Future work

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Spatial dynamic modeling

Locations change due to external forces

Realistic representation of landscape

Elements of dynamic models

Different types of models

Geographical space is inhomogeneous

discretization of space in cells

generalization of CA

discrete and continous processes

Extensibility to include user-defined models

Flexible neighborhood definitions

Demands Requirements

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Inhomogeneous Space

Spaces of fixed location and spaces of fluxes in Amazonia

TerraMLComputational Environment

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Spatial Information Engineering Technological change

Current generation of GIS– Built on proprietary architectures– Interface+function+database = “monolythic” system– Geometric data structures = archived outside of the

DBMS

New generation of object-relational DBMS– All data will be handled by DBMS – Standardized access methods (e.g. OpenGIS)– Users can develop customized applications

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TerraLib: the support for TerraML

Open source library for GIS Data management

– object-relational DBMS • raster + vector geometries• ORACLE, Postgres, mySQL, Access

Environment for customized GIS applications

Web-based cooperative development– http://www.terralib.org

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TerraLib and TerraML

TerraML is integrated with TerraLib– access to typical GIS analytical tools

Dynamic ModellingQ

uery

and

Sim

ulat

ion

lang

uage

s

Spatial Access

methods

Algorit

mhs

Data Conve

rsion

Geographic

Data Types

Spatial A

nalysis

Datab

ase

Supor

tVisualization

TerraLib

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BUILDER

Computational Model

TerraMLXML based

Parser

TerraLib Code Generator

TerraLibComponent

Library

DOM/XERCES

Theoretical Foundations for TerraML

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TerraML Cellular Model

Cellular Space

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Cell-space x Cellular Automata

CA– Homogeneous, isotropic space– Local action– One attribute per cell (discrete values)– Finite space state

Cell-space– Non-homogeneous space– Action-at-a-distance– Many attributes per cell– Infinite space state

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Hybrid Automata

Formalism developed by Tom Henzinger (UC Berkeley)– Applied to embedded systems, robotics,

process control, and biological systems

Hybrid automaton– Combines discrete transition graphs with

continous dynamical systems– Infinite-state transition system

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Hybrid Automata

Variables Control graph Flow and Jump conditions Events

Control Mode A

Flow Condition

Control Mode B

Flow Condition

Event

Jump condition

Event

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Neighborhood Definition

Traditional CA– Isotropic space– Local neighborhood definition (e.g. Moore)

Real-world– Anisotropic space– Action-at-a-distance

TerraML– Generalized calculation of proximity matrix

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Supporting Different Models

Cell’s Potential for Change is Function of– Global Demand

• e.g. “2% of forest area will be deforested per year”

– Neighborhood Influence• e.g., “80% of deforestation occurs near existing

roads”

– Local Attributes• e.g., “cells wìth more than 2800 mm of rain/year

will not be feasible for agriculture”

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TerraML Structure

Transition

Input

Constraint

Simulation

Output

CellProcessor

layer

temporal

layer

discrete rule

continuous rule

spatial restriction

temporal restricition

commands

actions

temporal

global

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An Example in Hydrology

A water balance Automata

DRYsoilwater=soilwater+pre-evap

WETSurplus=soilwater-infilcp

Soilwater=infilcp

input soilwater>=infilcp

input

Surplus>0

TRANSPORTINGMOVE(LDD, surplus, infilcp)

discharge

Control Mode

Flow Condition Jump Condition Event Transition

DRY Solwat=solwat+pre-evap

Solwat>=infcap

WET

WET Surplus=soilwater-infilcap

Surplus>0 discharge

TRANSP

TRANSP MOVE(LDD,surplus, infilcap)

Surplus>0 input DRY

input

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TerraML Example

<cellprocessor author="bianca" date="04/03/02" model="simulation of runoff" case=" timesteps of 6 hours => modelling time one week"> <input>

<layer name="infilcap.map“ attribute=“infil"> InfilCap />

<layer name="soil.map“ attribute=“class"> SoilType />

<layer name=“LDDmap“ attribute=“ldd"> LDD /><temporal name="rain.tss"> RainTimeSeries />

</input> <output>

<Temporal name="rainfall“ attribute=“solwat"> SoilWater />

<layer name="runoff“ > Surplus /> </output>

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TerraML Example

<transition> <mode controlmode =“DRY” flowcondition=“soilwater+pre+evap”

jumpcondition =“soilwater>infl_cap“ to=“wet“ />

<mode controlmode name=“WET“ flowcondition= “Surplus=soilwater-infilcp; Soilwater=infilcp;” jumpcondition=“surplus>0“

to=“TRANSP“ event=“discharge“ /> <mode controlmode name=“TRANSP“ flowcondition= “MOVE(ldd,surplus,infilcap)” jumpcondition=“surplus>0“ to=“DRY“ event=“input“ />

</transition>

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TerraML Example

<simulation><cellularspace neighborhood=“LDD” result=“soilwater” /><timer init="1" end="28" step="1" timeUnit="6 hours">

<Transit> </timer></simulation>

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Future Work

Formalization of model types Constructions of real-life applications

– Hydrology– Deforestation

Web availability

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Acknowledgments

ESRI

Methodist University of Piracicaba, Brazil