Using Fuzzy Logic Analysis and Fuzzy ANP (FANP) Method in GIS for Landfill Site Selection (Case Study: Aliabad City)

Document Type : مقاله پژوهشی

Authors

• Vahid Nikzada
• Mohamad Javad Amiri
• Yasser Moarab
• Negar Foroughi

University of Tehran

10.22067/geo.v6i1.47944

Abstract

1. Introduction
In developing countries, the ever increasing human population and the associated anthropogenic activities have accelerated the phenomenon of urbanization in the past decade. With the rising population and the associated unsustainable practices, there has been an enormous increase in the quantum as well as the diversity of the solid waste being generated. The problem of solid waste has assumed significant dimension especially in the urban centers. Domestic, industrial and other wastes, whether these are of low or medium level, have become a perennial problem as they continue to cause environmental pollution and degradation.So,rapid urbanization and population increase have called for an improved waste management services.
In this research, authors tried to use Fuzzy Logic method to obtain Fuzzy maps and used FANP method to weight criteria analytic network process. The ultimate goal of this research is to select a suitable site for landfill based on the FANP methodin Ali Abad Katool city.

2. Study Area
Aliabad Katoolcity with an area of 1160 square kilometers is one of Golestan province cities. Which it is limited to Gonbadkavoos and Aghghola cities from the north and Gorgan city from the west and Ramiyan city from the east and the Alborz mountains and Semnan city from the south. It is located in latitude of 36 degrees and 36 minutes until 37 degrees and 5 minutes of north and longitude of 54 degrees and 41 minutes and 9 minutes of east,and based on housing census of 2011, has a total population of 132.757.

3. Material and Methods
3-1- Multi Criteria Evaluation method(MCE)
In This method, in order to expose to a specific goal, it is required to evaluate several criteria (Voogd, 1983; Carver,1991; Eastman, 2012). The purpose of the multi-criteria evaluation is to select the best alternative (the best site or pixels) on the basis of their ranking by evaluating multi main Criteria.
There are several methods for the analysis of multi criteria evaluation. The most important of those include a weighted linear combination method, Boolean methods, value approaches functiondesirability, AHP, ideal point method and agreement method. Multi criteria evaluation often performed by one of these two methods:Boolean overlay and weighted linear combination. The fist process involves the overlap Boolean whereby all criteria reduced to the appropriate logic modes and then combined by one or more logical operators such as subscription (AND) and sum (OR).Second process is the weighted linear combination (WLC) in which continuous metrics (factors) is standardized to the normal numerical range and then combined with a weighted average. The result is a continuous raster map which covers one or more Boolean constraints to match with the qualitative metrics and eventually lead to the final decision.
3-2- Weighted Linear Combination (WLC)
Weighted linear combination (WLC) method is themost common technique in the analysis of multi-criteria evaluation.This technique also called scoring method. This method is based on the average weight. Analyzer or decision maker, weighting the criteria based on the relative importance of each criterion. Then, by multiplying the relative weight in the attribute value, final value is obtained for eachan alternative after specifying the final value of each alternative, the alternative that has the greatest value would be the most appropriate alternative for the intended purpose. In this decision rule, the value of each alternative is calculated by the following formula (Shahabi & Niyazi, 2009).
3-3- Map Standardization in Fuzzy Logic
In fuzzy logic, according the value which follows the intended criterion, each region obtains the value membership that expresses the desirability of the area. This means that each area with a larger value membership has a higher desirability. Fuzzy logic isnot certainty like Boolean logic and each layer is rated on a scale from 0 to 1. Another influential factor in fuzzy map standardization is determining the threshold which is called control points. But, one thing that should be considered in choosing function is the type of intended criterion that is increasing or decreasing and shows the control points and type of fuzzy function.

4. Results and Discussion
- Pairwise Comparisons of Criteria and Sub-Criteria Internal Relationships
Pairwise comparisons of criteria and sub-criteria which they conducted with expert’s opinions are shown in this article.
4-1- Steps of Obtaining Criteria and Sub-Criteria Weightswith Fuzzy Analytic Network Process
Based on various sources and experts’ opinions and FANP techniques, pairwise comparisons were performed between criteria and sub-criteria (Because of the high number of pairwise comparisons tables they arenot mentioned). And then, according to pairwise comparisons, weightsof each criterion and sub criterion are obtained in 5 steps which are shown in.

4-2- Calculating Required Land for Aliabad City’s Landfill
To calculate area of the required land for landfill over the next 20 years,landfill trench method with a depth of 4m is done.Also distance between the trenches is considered equal to its width. With these assumptions, Useful areas, makes up 50% of the range set.
4-3- Obtaining Data Layer Maps
In this study, map production was conducted based on fuzzy logic. Each effective data layer on landfill site selection standardized in IDRISI software according to table 3 charts. As well as their fuzzy maps produced in this software. These fuzzy data layer maps are shown in. In conjunction with fuzzy logic analysis included both “fuzzy membership functions, which assigned ratings for attribute values in a given thematic layer between 0 and 1, and “fuzzy overlay tool,” which merged multiple fuzzy membership results into the composite index map.
4-4- Overlaying Data Layers
Produced maps have been overlaid by applying 5 operators 1-Gamma,2- Product,3- AND,4- OR, 5- SUM in GIS and IDRISI software to perform site selection and achieve suitable areas for landfill. And, urban residential areas were eliminated from the final layer maps. All maps are shown in the article.

5. Conclusion
Map production with Fuzzy Sum and Fuzzy OR operators is not a suitable method for landfill site selection due to the ignoring unfavorable factors. Unlike Fuzzy OR and Fuzzy Sum, Fuzzy Product operator considers conservative approach and just shows the best places for this site selection. Also, Fuzzy Gamma operator with the numbers of 0.3 and 0.5, Fuzzy Gamma and Fuzzy AND with the number of 0.9 respectively have a less conservative approach than Fuzzy Product. But in general, these operators with Fuzzy Product are suitable for landfill site selection. In the meantime, based on Natural Breaks (Jenks) method from relevant operators maps are listed with four categories, suitable, average, weak and very weak (the classification of these operators is given in Figure 5).Then suitable category became classified. Methods which their Spots area were less than required area of landfill for estimated population of next 20 years of AliabadKatoolcity were excluded. Finally (AND), (Gamma) methods with the number of 0.9, determined a suitable landfill site for a period of 20 years as seen in it. Details and the priority of suitable areas for landfill site selection are given in this article.

Keywords

• Site Selection
• Landfill
• GIS
• FANP
• Aliabad city

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