Application of multi-criteria decision-making methods in land use evaluation to determine municipal waste landfills location

 Recently, the use of GIS in urban planning has been developed with the rapid expansion of cities and the dramatic increase in the amount of information that must be processed for urban management. This study investigates the best landfill site for Zahedan city using the performance of decision support tools, Network analysis process (ANP) and Weighted linear combination (WLC) for weighting criteria, and map standardization methods based on Boolean and Fuzzy logic in the form of multi-criteria decision-making. Indeed, based on the variables' impacts in locating the waste landfill in Zahedan city, using multi-criteria decision-making methods (MCDM) to weigh and prioritize and evaluate the effective factors are considered to identify the optimal location regarding the ecological potential of the region. The proposed model indicates the priorities of creating different types of decision-making during the evaluation analysis of the development capabilities of the study area.

Developing a multi-criteria evaluation method in a GIS environment to determine and estimate the capability of desirable landfills in Zahedan city is considered. Thus, by preparing a questionnaire by the Delphi method, 18 sub-criteria in two groups of criteria: 1. ecological criteria (Slope, altitude, soil, erosion, fault, precipitation, wind, direction, surface water, groundwater, vegetation, land use, and geology); 2. Socio-economic criteria (Distance from city, village, mine, airport, and road) is determined, and regarding expert's perceptions and using Network Analysis Process (ANP) in super decision software, weights of each criterion were calculated; and in the next step, the layers of criteria were evaluated in a database based on ArcGIS and stored as benchmark maps; and finally using the WLC method were considered to combine all layers to extract the map of a suitable landfill site in Zahedan city.

 By fuzzifying 18 layers (criteria) with fuzzy logic and also applying constraints with Boolean logic, 18-layer maps are prepared and by merging layers with one of the common methods of weight linear composition in Multi-criteria decision, the final landfill location map has been explored. In terms of the spatial distribution of suitable landfills in Zahedan city, according to 5 categories of classification, it was found that the highest level of the region is categorized as the low capable class (99.76%) and suitable areas for landfilling in total is around 0.231, also no part of the Zahedan city has a very high or high capability for using as the landfill location, while around the city of Nusratabad, areas with very high and high capability are observed. It was also found that mainly lands with both low and medium capability, are located in the suburban areas of Zahedan and Nusratabad, with 22 units for the city of Zahedan and 35 units for the city of Nusratabad.

 Reviewing the research literature shows the strengths of using a multi-criteria decision-making method to locate landfills, enabling the use of a robust set of interactive tools to regulate compensability between criteria, which allows a quick assessment of the relationship between the criteria. Other strengths of this method include the ability to integrate homogeneous data sets such as qualitative and quantitative criteria using specialized knowledge, the flexibility to select specific criteria for different study areas or various issues, to implement one or more decision-making groups, the flexibility to change the level of criterion importance and different choices for acceptable levels of decision-making risks. By comparing the final outputs related to other areas, it can be concluded that the final results are close and the method is suitable for landfill locations everywhere. Therefore, it is suggested that for other areas, the evaluation of land capability should be examined with the proposed method in this research. However, since the location of landfills by different criteria and the influence of public opinion depends on scientific analysis, we assume that this method has significant potential to support the decision-making complexities of real-world applications.