Pau Fonseca;
Josep Casanovas; Jordi Montero
Departament
d’Estadística i Investigació Operativa i LCFIB., Campus Nord – B6. Universitat
Politècnica de Catalunya,
c/ Jordi Girona
1-3, 08034 Barcelona (SPAIN) T.+3493 4016941 F.+3493 4017040
E-mail: {pau,
josepk, monty}@fib.upc.es
ABSTRACT
Some of typical
industry problems can be analyzed using
discrete simulation, in concrete the simulation event
scheduling
paradigm has been used over decades in
industry area
offering good results.
However, although
simulation can represent the reality
closer than any
other approximation, in other systems like
ecological,
economical or social don’t present similar
results. In fact,
currently is very difficult to depict this
kind of systems.
One of the first problems resides in his
evolving nature.
But, event scheduling simulations can be
used in this sort
of systems adding cellular automata and
intelligent agents
to the model structures, adding intrinsic
evolving nature.
Although the prediction usually cannot
be done, there are
other important benefits that can be
considered, like
data collection between the researchers of
the domain, the
recognition of gaps in the knowledge, and
of course, better
understanding of system in a global
approximation.
Nowadays these are the main goals
attended to
construct this sort of models.
The brief
description of this architecture, which allows the
simulation of evolving systems, like natural disasters,
is
the target of this
paper.
KEY WORDS
Cellular automata,
intelligent agents, natural disaster,
event scheduling,
GIS.
1. Introduction
This paper merge
three important areas, discrete event
simulation, that represent the simulation model kernel and
determines main
system architecture, GIS data
manipulation and
his utilization inside a simulation model
which enables
landscape data use inside simulation
model, and
finally use of artificial intelligent techniques
(like cellular
automaton or intelligent agents) in order to
enable system
evolution.
Natural
disasters, like wildfire, flooding, earthquakes or
tsunamis,
currently are unpredictable, and represent one
of the biggest
hazards to population of some earth areas.
Understand
through simulation techniques this disasters
represent not
only the possibility of human life salvation,
also enables the
capability of calculate the behavior of
some other
different systems that present evolving
behavior.
In this paper a
wildfire propagation and containment
model is
presented like a sample. Propagation model is
based in the
BEHAVE model (Andrews 1986, Andrews
and Chase 1989,
Burgan and Rothermel 1984, Andrews
and Bradshaw
1990) [15] [1].
2. GIS Data
Natural disasters
simulation models are focused in nature,
and for this
reason may require a massive set of GIS data,
in our wildfire
sample is necessary to define land slope,
vegetation,
combustible, wind speed, etc, consequently is
necessary
establish an interface, between this data and
simulation model, that enables the representation and
his
use in the model.
Data that
represents the elements (layers) are stored in
files that
follows IDRISI raster format (IDRISI is a GIS
developed by
Clark university). Each of these files
represents a
matrix, and each one of their cells defines
propagation model
features (all layers are represented by
two files *.img
file that contains data, the matrix, and
*.doc files that
contains data documentation).
The files used
are (following the behave model):
• Mapa: file
containing the DEM (Digital Elevation
Model).
• Model: file
that represents the propagation model
implemented for
each cell.
• Slope, Aspect:
files that stores the slope and his
direction. These
files are calculated using the DEM.
(Mapa files)
• M1, M10, M100,
Mherb, Mwood: files that contains
the combustible
description.
The results
files are two:
• ignMap.dtm:
Stores ignition time.
• flMap.dtm:
Stores flames elevation.
All these data
can be represented in virtual reality format,
which enables
landscape representation. The relevance of
this technology
is not only in the visual representation
facet, also in
his computer data representation. Virtual
reality stores
physical structures of landscape, structures
that are
required by the simulator in order to enable the
interaction with
the landscape elements. This also enables