A Fuzzy classification approach for decision making with spatial data is proposed.
The present study aims at developing
a generic automated methodology
for addressing Multi-Objective Multi-
Criteria Decision-Making problems.
Scientific approach which make use
of analytical modeling techniques are
essential to suggest suitable changes
in land use and to generate action
plan for an area for land and water
resource development. This problem
can be cast into a multi-objective multicriteria
decision-making problem.
It is multi-objective in the sense one
has to perform site suitability analysis
for multiple objectives, which include
agro-forestry, silvipasture, etc. Multiple
criteria like land use, slope, soil, landform,
groundwater prospects, etc, are involved
in analyzing each objective. Similarly for
generation of water resource action plan
one has to perform site suitability analysis
for check dam, percolation tank, stop dam,
gully plug etc. Though the same problem
can be broken into several single objective
multi criteria decision-making problem,
the procedure is going to be tedious.
Multi criteria decision
making (MCDM)
Multi criteria decision-making (MCDM)
problems involve a set of alternatives
that are evaluated on the basis of a
set of evaluation criteria (Malczewski
1999). The objective of using MCDM
is to help find solutions to decision
problems characterized by multiplechoice
alternatives, which can be
evaluated by means of performance
characteristics called decision criteria.
Alternate approaches to GIS-based multi
criteria analysis have been suggested
to overcome the problem of weighting
and data integration. Combining
different factors, some exclusionary and
some expedient, requires a weighting
factor. Analytic Hierarchy Process
(AHP) is an approach that can be used
to determine the relative importance
of a set of activities or criteria (Saaty
1990). AHP is a technique introduced
by Saaty and has been widely used
in the multi-criteria decision-making
process in varied fields (Saaty and
Vargas, 1990). Analytic Hierarchy
Process (AHP) has been identified as
a weighting strategy and Compromise
Programming (CP) technique has been
identified for data integration (Novaline
et al. 1996, Deekshatulu et al. 1999).
Multi-Objective Multi-Criteria Decision-
Making method Combination of Analytical
Hierarchy Process and Compromise
Programming techniques worked well in
solving Single Objective Multi-Criteria
problems like Site Selection for Water
Harvesting Structure, Landslide Hazard
Zonation (Novaline et al. 2001). But
such a combination cannot be effectively
used for solving Multi-Objective Multi-
Criteria problems. Though the Multi-Objective Multi-Criteria Decision-Making
problem can be broken into several single
objective multi criteria decision making
problem, solving this problem by applying
combination of Analytical Hierarchy
Process and Compromise Programming
techniques is not going to be straight
forward and effective. Moreover only
absolute suitability within an objective can
be addressed using MCDM techniques. In
Multi-Objective Multi-Criteria Decision-
Making problems, what is needed is
the relative suitability for different
objectives. In the present study we
propose a Fuzzy classification approach
in GIS for solving Multi-Objective Multi-
Criteria Decision-Making problem.
Methodology Fuzzy Classification in GIS The fuzzy representation allows us to
apply fuzzy techniques for geographical
information processing (Burrough 1989).
A fuzzy suitability rating method has been
developed in this research. Compared
with the conventional approaches, this
method provides more information
about land suitability. This approach
not only solves a multi-objective multicriteria
decision-making problem, but
also overcomes the information loss seen
in classical set theory-based decisionmaking
(Novaline et al., 1997).
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