spatial data have relationship with space aspect-location that is presented as database on a map. To acquire spatial analysis result use overlaying technical
from some thematic maps vector or raster. New spatial information is acquired based on new digital value that constitutes an integration of old digital value.
2.7. Multi Criteria Decision Making MCDM
Multi-Criteria Decision Making MCDM is the study of methods and procedures by which concerns about multiple conflicting criteria can be formally
incorporated into the management planning process. Decision analysis looks at the paradigm in which an individual decision maker or decision group
contemplates a choice of action in an uncertain environment. The decision theory helps identify the alternative with the highest expected value probability of
obtaining a possible value. The theory of decision analysis is designed to help the individual make a choice among a set of pre-specified alternatives. The decision
making process relies on information about the alternatives. The quality of information in any decision situation can run the whole gamut from scientifically-
derived hard data to subjective interpretations, from certainty about decision outcomes deterministic information to uncertain outcomes represented by
probabilities and fuzzy numbers. This diversity in type and quality of information about a decision problem calls for methods and techniques that can assist in
information processing. Ultimately, these methods and techniques MCDA, MCDM may lead to better decisions Malczewski 1999.
In order to incorporate heterogeneous information with different measurement scales, one has to bring them into a common domain of
measurement. This process is called Standardization, a basic operation in MCE. Criteria should be standardized keeping in mind the goal and alternatives that are
under evaluation. Standardization can change the outputs entirely if proper attention is not paid. For environmental criteria, there is a lack of valid and
reliable standardization processes Bunn, 1982. Decision-making is a subjective process, as the perception regarding a
problem can diverge from person to person. One cannot expect a decision maker or an expert to be highly consistent while dealing with such a subjective process.
The real world problems are influenced by many natural factors and processes that are difficult to measure and model precisely. After the problem is evaluated for
optimum conditions, sensitivity analysis assesses different conditions near the optimum values to check for the sensitivity of the criteria. Many decision-making
methods lack a valid approach towards sensitivity analysis. Sensitivity analysis also aids in understanding the interaction between the criteria, dominant criterion
and its effect, i.e. the variation in the final results when the weight of that criterion is varied Keeney and H. Raiffa, 1976.
The true goal in integrated decision-making support is to provide the decision-maker with the ability to look into the future, and to make the best
possible decision based on past and present information and future predictions. In the case of sustainable development, this means to be able to predict in advance
the risk and vulnerability of populations and infrastructure to hazards, both natural and man-induced. This requires that data be transformed into knowledge and that
the consequences of information use, as well as decision-making and participatory processes, be analyzed carefully
A decision involves making a selection from a set of alternative choices. Broadly speaking, a decision-support system DSS is simply a computer system
that helps to make a decision by leveraging the multi-criteria decision-making model. DSS provide a means for decision-makers to make decisions on the basis
of more complete information and analysis Szidarovszky et al, 1986. Among the main advantages of the use of DSS are the following:
• Increased number of alternatives examined
• Better understanding of the business
• Fast response to unexpected situations
• Improved communication
• Cost savings
• Better decisions
• More effective teamwork
• Time savings
• Better use of data resources
• When Theory Meets Practice
There is a need for approaches that combine available quantitative data with the more subjective knowledge of experts. Decision-theory techniques
applied by high-end knowledge professionals have been successfully used for contrasting expert judgments and making educated choices. The multi-criteria
decision-making model, by coupling theory and knowledge, provides an analytical approach to expert consultation and is adapted for a variety of
technology and business fields aiming at suitability assessments Lahdelma, 2000.
Particular and important types of DSS are the so-called spatial decision support systems SDSS. Spatial DSS refers to those decision support systems that
combine the use of Geographic Information Systems GIS technology with software packages for selection of alternatives of location for different activities.
GIS provides an important source of tools and techniques, which can usefully be incorporated in a DSS system that makes use of geographic or spatial data. There
is a need for approaches that combine available quantitative data with the more subjective knowledge of experts Jankowski, 1995.
Figure 3. Framework for Spatial Multicriteria Decision Analysis Malczewski 1999
Problem Definition
Recommendation Sensitivity
Analysis Decision
Rules Decision
makers- Preferences
Alternatives Decision
Matrix Constrains
Evaluation Criteria
Intelligence Phase GIS
Choice Phase MCDMGIS
Design Phase MCDM
2.8. Analytical Hierarchy Process
