Fuzzy logic approach for sustainable land use planning
|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.
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).