The approach trough cellular automata represents an attempt at€¦ · Modelling dispersion phenomena in tidal environments: use of cellular automata in GIS applications A. Bianchin*,

Modelling dispersion phenomena in tidal

environments: use of cellular automata in GIS

applications

A. Bianchin*, E. Rinaldi** & A. Bergamasco***

* University of Venice, Institute of Architecture, Department

of Social and Economic Analysis of Territory.

** Stratema Laboratory of DAEST. University of Venice,

Institute of Architecture

*** Thetis. Marine Technology Centre. Arsenale. Venezia

Abstract

The purpose of this research is to reach an evaluation of the potential usefulnessof cellular automata, a simple and efficient modelling technique for simulation,in describing dynamic phenomena of interaction between elements or parametersrelevant for the assessment of environmental quality in lagoon basins.

The modelling context is the Venice lagoon with particular attention on thephenomena concerning substances which concur to create pollution. Thedynamics of three processes are studied: substance dispersion in a basin, as ruledby hydrodynamic forces; dynamics of interaction between pollutants andvegetation; and interactions between water and sediment. We also realized aninterface for data exchange between the module for cellular automata and a GISmarine application in Arclnfo environment.

1. Introduction

The study of dispersion patterns of polluting substances in lagoonenvironments is of high importance for the planning of ways to improvethe quality of human as well as animal and vegetal life.

This research developed three computer models using cellularautomata to help simulate the dispersion of substances in water.

Transactions on Information and Communications Technologies vol 18, © 1998 WIT Press, www.witpress.com, ISSN 1743-3517

314 GIS Technologies and their Environmental Applications

The approach trough cellular automata represents an attempt at

describing the dynamics of phenomena in a natural way and throughlocal formulations, as opposed to the global formulations offered by

models based on equation systems.Three kinds of phenomena have been considered: the diffusion of

substances, their advection and their interaction with the vegetation.The first cellular automaton simulates dispersion as caused basically

by river inflows with diffusion and advection being defined by differenttransformation rules. In this case the relevant factor is hydrodinamics.Rules are based on balance between cells in order to evaluate variationsin concentration within one day. The second cellular automaton considersthe interaction of pollutants with the lagoon vegetation and vice versa.

Rules are based on expertise and applied stochastically. The time scale is

seasonal, covering a few months. The third cellular automaton considersthe interaction between sediments, water and atmosphere. The exchangeand transformation processes of organic and inorganic materials areanalysed within a column including sediments, water and atmosphere.

Here too, the time scale is seasonal.The computer simulation models have been so designed as to be

integrated within an experimental Venice Lagoon GIS, an overall project

of which this research is a part.

2. The cellular automata for simulation ofsubstance dispersion

The transformation rules governing the diffusion-advection automatawere based on consideration of the phenomena of diffusion and

advection. It was a matter of simulating the variation in concentration of aparameter (e.g.: salinity) in water with respect to time variation and inrelation to other factors, such as rate of water flow and basin'smorphology. The rules for advection were based on the sum of thesubstance's concentration readings and keep the speed of water flow intoaccount. The rules for diffusion were based on the average of theconcentration readings.

In the automata concerning dispersion of nutrients, the phenomenaon which the rules were built were, beside the nutrient's diffusion andadvection, the production and absorption of that nutrient by thevegetation. It was a matter of simulating the variations in a nutrient'sconcentration in water with respect to time variation, in relation to waterflow and basin's morphology and in presence of vegetation. Theabsorption and production rules were based on stochastic-heuristic


GIS Technologies and their Environmental Applications 315

factors in determining the increase or decrease in the readings of thenutrient's concentration in the cells.

In the automata concerning the dynamics of interaction betweensediment and water column, the phenomena considered were thevegetation's birth (growth) and death, the transformation of nutrients'concentration in water, and the sediment's transformation. The rules forgrowth of vegetation of a species were based on the presence of

vegetation of that species in the surroundings, while the rules for death(transportation) of vegetation were based on stochastic-heuristic factorsin determining the transformation of a vegetation cell into a water cell.The rules for transformation of water and sediment were based, besideheuristic factors, also on the presence of nutrients and oxygen.

3. The Systems Used for AutomataImplementation

The advection-diffusion automata and the ones for advection-diffusionwith interaction with the vegetation were implemented with the SeTAsystem (Sea Transformation Automaton); the automaton for water-sediment interaction was implemented with the AUGH! system (AutomiUrbani Generalizzati con Help in linea - Urban Generalized Automata

with Help online). Both the SeTA and AUGH! software were developedby the STRATEMA-IUAV Laboratory.

3.1. The SeTA System

From the field readings of the data concerning substance concentrationwere produced the values for a certain number of cells of the area underconsideration. From the hydrodinamic model were extracted the matricesof water velocity; the same model also supplied information on thebasin's morphology. Through the information on vegetation a scenario ofvegetation distribution was built. Thus the substance's concentrationvalues become the input for an interpolation automaton which producestheir distribution on the entire area, supplying the map of theconcentration values. The application of a threshold level to the values ofthe concentration map (20 states) allows the extraction of a scenario inwhich each cell is characterized by a state corresponding to one level ofconcentration of the substance. This is the starting scenario for theperformance of the cellular automaton. The velocity matrices areconverted into maps in which each cell is characterized by a velocity

state. The starting scenario of substance's concentration, the velocity



maps, the vegetation scenario and the cells' transformation rules

constitute the cellular automaton. The automaton is run for a givennumber of cycles and produces a transformed scenario of substance's

concentration.

K-Map of

concentrationreadings

\ r

Velocitymaps

1

Scenariovegetazione

's performance

SeTA system 's environi

Fig. 1. The SeTA's system configuration

3.2 The AUGH! System

As opposed to SeTA, AUGH! is a general interface for the constructionof types of automata afferent to different contexts. The construction of acellula automaton is defined in AUGH! as the construction of a Project.

A Project is built by composing four elements: a set of the cell'sStates, a set of Rules of cell's variations, a neighborhood of analysis ofthe cells and a Scenario. Initially a set of cell's states is defined; then aneighborhood of analysis is defined; then a set of rules is built on the



basis of the set of states and of the neighborhood; finally the simulation

scenario is constructed.

Databaseset of states

Databaseneighborhoods

Databaseset of rules

DatabaseProjects

Fig. 2. Configuration of the AUGH! system

4. Automata Implementation

The implementation of two examples of automata is described: the one

relative to advection-diffusion and interaction with vegetation (of which

the simple advection-diffusion automaton is a subset) and the one relativeto the water-sediment interaction.

4.1 The Nitrogen Dispersion Automaton at Daily Temporal ScaleImplemented with SeTA System

The cell's states are relative to the concentration degree of nitrogen inwater, plus two special states. The simulation scenario is defined withcells afferent to those states. The auxiliary scenario of vegetationdistribution includes cells characterized by two states: phanerogamousand macroalga. The cell's transformation rules are the rules of advectionand diffusion plus the rules of nitrogen absorption by the phanerogamousand by the macroalga. The probability of activation for the advection and

diffusion rules is set at 100 %, while for the macroalga's andphanerogamous's absorption rules it is set respectively at 25 % and at 10% - it is hypothesized that the macroalgae perform a more intense activityof nitrogen absorption from the water column than the phanerogamous.The simulation scenario is one of distribution of the total concentration of


318 CIS Technologies and their Environmental Applications

L'automa SeTA "azoto : automa 1" c' costitulto dagll element!:

Set statl-caratterlstlche : Scenario concentrazlone sostanza :1. Grado concentrazione 1 - gtallo 12 - Grado concentniioiui 2 - glallo 23 - Crado coiueittrailone 3 • glallo 34 • Grado eoncentrailone 4 - glallo 45 • Grado concentraiione 5 • glall* s• Grado coMcentraiiom 6 • glallo scuroj+l

Sequenza mappe velocita':FIU 1.VELFllfZ.VELFIU_3.VELFIU_4.VEL

Regole d! varlazlone concentrazlone sostanza:RAA1. Celh: Sc (ng(Vl)), Yar: Scl - Sc. 1RAA2. Cella: Sc (mg(V2)|, Ytr: Scl - Se -1RAVI. Cellar Sc (Vel.°0),bit: celk(NJE.S,W)MOT(Vel->C "In), Var; Sc 1 - Sc. 1

Fig. 3. Elements constituting the automaton of Nitrogen dispersion

nitrogen, which represents a situation of lagoon edge where a river

inflows.The scenario has a size of 20 x 20 cells,Nitrogen concentration is initially lower on the south side (sea side)

and higher on the north side (lagoon's edge and river's mouth): this is dueto the nutrients carried from the drainage basin. Some generating cells (atmaximum level) can also be initially located at the river's mouth, tosimulate the nitrogen import from the drainage basin.

Stato delta cclla: Status celle scenario :

Scanslonl: |16 ( Esegulte: 16Coord.: % 20 Y: 18 Stato: 4

Clcll ognl mappa velocita': {* |

Fig. 4 Automaton of nitrogen dispersion. Output after 16 interactions.



In the simulation output it can be noticed that the nitrogen import

from the river towards the basin doesn't cause a relevant concentrationincrease, because of absorption by the vegetation: the reading is one ofsubstantial balance between imported and absorbed nitrogen, particularlyin the surroundings of areas with vegetation. However, in some of thoseareas there appears to be an evident loss of concentration, while in areas

divested of vegetation there results a partial concentration increase.

4.2 The Water-Sediment Interaction Automaton in VerticalBidimensional Sections Implemented with the AUGH! System

Transformation rules of vegetation (phanerogamous and macroalga) andof water quality operate on a scenario reproducing a vertical section of thelagoon basin. The cell's states are afferent to three typologies: water,sediment and vegetation. The simulation scenario is defined with cellsafferent to those states.

L'automa "acqua-sedimento" c' costitulto dai seguenti element):Set stall - caratteristlche: Scenario :

«c*u4 coiu. madia u*te ******** - Mi10 - macro tic* nvort* • raito itui*2 • acqu* rice* di ***!** m# • Mu *cur*3 - KIU* rice* di uoto • Mu ehi*i»4 • tedinunt* pr*iu fin* &**,& o*tlr. •Intorno dt anallsl:

Regole dl varlazlone:« c«n«. m*dl» MO!* *i*lc*n*.Intil(Q,Q,Q,Q,Q,Q,m«r.«J«* viva,m* c*nc. madU *ioW •t*lc*M.IntiUQ,Q,Q,> c*nt. mtdit «o*. .,,if n * . I n t i H Q , Q , Q , _i* c«nc. nudi* uot* *«*lctn*.Intt|(Q,Q,Q,Q,Q,Q,Q,inMt*«Ici m*rte!,0,0,(].DI-Fr.ilOO.Pr.i5.Art . •«

_(].DI-Fr.ilOO.Pr.iDl.rr.ilOft.lV.ilf

Ffoestfa | Aprtreg.r.

Fig. 5. Water-sediment interaction automaton. Automaton's elements

The analysis neighborhood here considered is Moore'sneighborhood, consisting of the eight cells surrounding the one inquestion at the first level. The cell's transformation rules can be groupedin four typologies: transformation rules of phanerogamous (growth anddeath); transformation rules of macroalgae; of water; and of sediment.



Cede dello scenario agglornateox Y: 15 X: 30 100%

N. Scansionl: [20]Escgulte : 20

Fig. 6. Water-sediment automaton. Output after 20 iterations

The simulation scenario is an ideal section of the lagoon basin, in anarea where both vegetative species phanerogamous (purple) andmacroalga (green) are present; the sediment is visualized as an upperlayer (fine grain and high oxygenation) and an underlying layer (also finegrain, but low oxygenation). Water oxygenation and nitrogen content areaverage. In the scenario resulting from the simulation it can be noted thatthe vegetation of macroalgae has grown remarkably, while thephanerogamous show only limited development. The photosyntheticaction of the two species has produced an enrichment of oxygen in thesurrounding water. Furthermore, oxygenation appears to have beenreduced in some areas of the sediment's surface layer, as a consequenceof oxygen absorption in the decomposition process of dead algae.

5. Data Exchange Interface between the SeTASystem and a Marine GIS Application

Among the functions of a GIS marine system, particular importance isassumed by the possibility of being interfaced with other applications,such as systems for dynamic spatial simulation of phenomena. On onehand, the GIS system can supply the input information to the simulationsystem, while on the other hand the simulation output can be stored up inthe GIS and remain available for further elaboration. For this reason westudied an interface for the exchange of data between the SeTA system(simulation of substance dispersion phenomena) and a marine GIS systemdeveloped in Arclnfo environment. Thus the data exchange concerns



information from the GIS to the SeTA system, such as field readings ofsubstances or data on vegetation; and information from the SeTA systemto the GIS, such as scenarios resulting from the simulation by cellularautomata. The interface methodology selected in a first prototype is anexchange of information, included in files, through a local or remote disk,accessible by both the GIS ans SeTA applications. The files are matricesof values in raster interchange format.

valueformat andattribution

table

SeTA environment

SJmulatioioutput

scenarios

Fig. 7. GIS-SeTA interface in a simulation process



6. Conclusions and Future Developments

In this paper we described some examples of simulation of substancedispersion phenomena in lagoon basins. The simulation is implementedthrough cellular automata, which can be integrated in a GIS marineapplication.

In the context of a lagoon information system there rises a need formutual exchange of data bewteen a GIS, static by nature, and asimulation model of dynamic phenomena. The use of cellular automata isproposed as a solution to that issue. The local approach characterizingsuch automata permits to track the simulation of phenomena step by step

in space and time and consequently permits to introduce, by comparisonwith known situations, those modifications which keep the system closerto the reality of the phenomena.

The systems described here are at present undergoing a testingphase. An ensuing phase of the project calls for the use of SeTA for the

study of the evolution of a lagoon basin in which important advection and

diffusion phenomena (river input) take place, and which in the past has

been for a number of years the object of water quality monitoring.

References

[ 1 ] Alba S., Applicazione degli automi cellulari per I 'analisi territorialee ambientale: ipotesi di uso in un GIS per aree marino-costiere.Doctorate dissertation, DAEST-IUAV

[2] Batty M., Generating urban forms from diffusive growth,Environment and Planning A, v. 23, 1991.

[3] Bergamasco A., Piola S., Deligios M., Model Oriented GIS forMarine and Coastal Environmental Applications, in GeographicalInformation, From Research to Application through Cooperation,vol. I, Oxford, 1996

[4] Couclelis H., Cellular Worlds, A Framework for Modeling Micro -Macro Dynamics, Environment and Planning A, v. 17, 1985

[5] Rinaldi E., AUGH! Generalized Urban Automaton with Help online. DAEST-IUAV, in course of publication.

[6] Tobler W. R., Cellular geography, in S. Gale, G. Olsson (editors),Philosophy in geography, Reidel, Dordrecht, 1979

[7] Toffoli T., Margolus N., Cellular Automata Machines: A newEnvironment for Modeling, The MIT Press, Boston, 1987


Documents

The approach trough cellular automata represents an attempt at€¦ · Modelling dispersion phenomena in tidal environments: use of cellular automata in GIS applications A. Bianchin*,