To develop an expert system to be used as a decision tool towards
protecting forest land.
The proposed expert system will be
based on remotely sensed Multi-date Satellite Imagery,
Geographical Information Systems, Global Positioning Signals,
Mathematical Modeling and Advanced Visualization Techniques.
The system will consist of the following main
parts: (i) an electronic database within a Geographical
Information System to provide information on forest areas, (ii) a
mathematical model to process the database information and
classify forested areas according to their potentiality for fire
eruption, (iii) a visualization system to provide an on-line
pixmap representation of the potential of fire eruption on a
digital map of the area of interest. To construct the expert
system, representative forest-fire affected areas from two
Mediterranean countries, will be studied.
The electronic database will be incorporated, structured and
layered in a Geographical Information System (EASI/PACE) and will
include: multi-date satellite data, digitized geophysical data,
land-use data and socio-economic parameters pertaining to factors
that affect intentional fire eruption.
Image processing and photo-interpretation techniques will be
applied on geophysical maps and multi-date satellite imagery
(LANDSAT TM, LANDSAT TM+ERS-1 SAR, LANDSAT TM+SPOT PAN) to
determine geophysical parameters such as: (I) biomass, (II) soil
moisture, and land use data such as: (I) illegal residential
development across forest roads and at the outskirts of the
existing forest areas, and (II) intensity of illegal housing
construction. Change detection techniques such as: Post
Classification Comparison, Principal Component Analysis (PCA) and
Image Rationing/Differencing will be applied on multi-date
satellite data of fire-affected areas, to determine land-use
Critical parameters will be determined, by cross-correlating
geophysical, land-use change, and socio-economic data pertaining
to areas that have been affected by fire eruption. These
parameters will serve as input to the mathematical model. A
deductive neural network classification algorithm will be
developed to classify forested areas according to their
potentiality for fire eruption.
The mathematical model will be integrated with the GIS system
(EASI/PACE) to provide automatic access to the input parameters
residing at the GIS database. Also, a visualization software
package (AVS) will be used to integrate the mathematical model
with advanced visualization techniques.
Funding SchemeCSC - Cost-sharing contracts