Integrating multi-criteria evaluation techniques with geographic information Systems for landfill site selection: A case study using ordered weighted average in Mashhad

Document Type : مقاله پژوهشی

Authors

• Mohammad Rahim Rahnama
• Hossein Aquajani
• Mehdi Fattahi

Ferdowsi University of Mashhad

10.22067/geo.v1i3.16943

Abstract

Introduction
Environmental protection is one of the most priorities in Land use planning. In this regard, place and location have the greatest role and its importance is increasing when the adverse effects of environmental neglect, can cause irreversible situation.
Selection a suitable location for the burial of solid waste can prevent the unfavourable ecological and socio – economic effects. Landfill site selection requires spatial data analysis, acceptable rules and standards.
Choosing the various factors and therefore the number of Map layers, decision-makers to lead them unconsciously into a system that in addition to high accuracy also has high speed and simple of operation.
Nowadays, these processes are using spatial models and GIS in the desired method is provided.
A selected landfill is an important process in urban planning that effect on economic and environmental sectors and environment hygiene.
Multi-criteria evaluation methods and GIS can use as an efficient tool for managing and applying layers seeking information in the place. In developed countries and also in Iran, a great deal research has been done in this field.
This study with utilize past experiences and applying GIS technology want to provide a method for landfill site selection.
Material and Methods
This paper is studied multiple criteria decision analysis method based on GIS to select the appropriate location landfill in the metropolis of Mashhad. According to limited variables in the southern and south west areas of metropolitan Mashhad, average 18 km radius has been determined. This area has been calculated approximately 2465 Km2 and include the cities of Mashhad, Torghabeh, and the town Shandiz Razavieh (the eastern most point of the urban area). Growth Population, pilgrim of Imam Reza (AS), uncontrolled urban development, business activities and focus industrial and office in Mashhad increased waste generation which has adverse effects on the quality of the environment in Mashhad. At present, the volume of waste generated in the city of Mashhad, about 1,500 tons during peak travel to Mashhad (spring and summer), the figure is well over 2,000 tons. Method sin this study, is combination of site selection models and GIS.The multi-criteria decision framework considers environmental and economic factors which are standardized by fuzzy membership functions and combined by integration of analytical hierarchy process (AHP) and ordered weighted average (OWA) techniques. The AHP is used for the elicitation of attribute weights while the OWA operator function is used to generate a wide range of decision alternatives for addressing uncertainty associated with interaction between multiple criteria. The usefulness of the approach is illustrated by different OWA scenarios that report landfill suitability on a scale between 0 and 1. The OWA scenarios are intended to quantify the level of risk taking (i.e., optimistic, pessimistic, and neutral) and to facilitate a better understanding of patterns that emerge from decision alternatives involved in the decision making process.
Ordered weights in a decision making that involves three factors take [1, 0, 0] for the AND operator, [0, 0, 1] for the OR operator, and [0.33, 0.33, 0.33] for the arithmetic mean (i.e. risk neutral). Finally, this is a multi-objective decision problem to consider environmental and economic criteria’s, the landfill allocation used a WLC to aggregate suitability maps created by each objective.
Environmental criteria’s, including: surface water springs, rivers, dams, groundwater level, slope, elevation, faults socioeconomic criteria, including population density, habitat settlements (city or villages) and the distance from the road. The type of fuzzy membership functions used to standardize the factors such as J-shaped – decreasing، Sigmoidal – decreasing, Linear – increasing
Results and Discussion
According to applied models, specific feathers in different parts of the study area were identified in different scenarios;. In some models, a large area of stains and patterns with a lower risk of these devices was limited. The OWA weights were used to generate different patterns to control the levels of trade-off and risk. This study presents an application of GIS-based multi-criteria evaluation approach for characterizing and assessing favourable landfill sites in Mashhad.
Aggregation procedures to generating a wide range of decision alternatives needed for landfill suitability problems. The AHP methodology is used to evaluate the importance of criteria and generates the global weights, which are used in conjunction with the local weights in OWA procedure for producing the decision alternatives. The AHP/ OWA aggregation procedure incorporates uncertainty through a fuzzy membership function and expert opinions. In addition, local weights are used to provide leverage for controlling the level of uncertainties associated with different decision alternatives and risk taking (i.e., optimistic, pessimistic, and neutral).
The decision alternative is associated with the AND operator and produces a risk averse
Solution. According to this alternative, the most suitable areas for landfill sitting are located in north and north-western and south-eastern of Mashhad.
Total of six decision alternatives used for landfill suit ability associated with the environmental factor and The OWA weights were used to generate different patterns to control the levels of trade-off and risk.
The maps of the WLC alternatives show three different scenarios generated by different weights applied to the objectives. For instance, first alternative applies a weight of 0.75 to the environmental objective and a weight of 0.25 to the economic objective, second alternative uses equal weights and third alternative applies a weight of 0.25 to the environmental objective and a weight of0.75 to the economic objective.
In this paper the appropriate places based on the models in three scenarios be identified and used to locate a landfill around the Mashhad metropolis has been introduced.
Extent of suitable areas for landfill sites in the first scenario, which had the lowest risk, with an area of 491.5 hectares, less than 0.199 percent of the study area, the second scenario 543.3 hectares and 0.22 percent and the third scenario has the highest risk of approximately 3041 hectares 1.233% of the study area as suitable locations for landfill indicates show respectively.



Conclusion
The results from this study demonstrate that the aim of the approach is not to find a single ‘optimal’ solution, but to show other strengths associated with the weighting flexibility of the OWA approach. For example, the OWA approach provides a robust interactive toolset for adjusting trade-offs and compensation between criteria that allows a rapid assessment and inter predation of possible alternative scenarios and relationships between criteria. Other strengths of this approach include the ability to integrate heterogeneous datasets such as quantitative and qualitative criteria using expert knowledge, the flexibility to select specific criteria for different study areas or different problems under consideration, to implement a single or a group decision-making, the flexibility to change the importance level of criteria, and the freedom to develop
Various modeling scenarios for acceptable levels of decision risks. However, since landfill sitting depends on political and public opinion forces in conjunction with scientific analysis, we posit that this methodology holds significant potential to support the complexity of decision-making in real world applications.

Keywords

• Site Selection
• Landfill
• GIS
• OWA
• Fuzzy

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References

Mashhad Municipality, Department of Planning and Development., 2010. Statistics of Mashhad Metropolitan.

Afzali, A., 2008. The Application of GIS and AHP in Urban Waste Exclusion Site Selection, Study Area (NajafAbad). Esfahan University, Department of Natural Resources.

Amini,M., 2006. Site Selection of Urban Solid Waste Exclusion by Remote Sensing technology and GIS . Tabriz University.

Rahnma, et. Al., 2012. Analysis Strategy of Mashhad Local Environmental Management –in terms of SWOT. Second Conference on Environmental Management.

Abdoli, M., 2000. Urban Solid Waste Exclusion Management. Urban Planning Department of Ministry of Interior.

Yousefi, Heidarali,et.al., 2010. Geographic Journal of territory. Science-Research.Year VII, No, 26, Summer 2010, p 103.

Baban, S.M.J., Flannagan, J., 1998. Developing and implementing GIS-assistedconstraints criteria for planning landfill sites in the UK. Planning Practice and Research 13, 139–151.

Banai, R., 1993. “Fuzziness in Geographical Information Systems: Contribution from the Analytic Hierarchy Process. International Journal of Geographical Information Science 7 (4), 315-329.

Barlaz, M., Kaplan, P., Ranjithan, S., Rynk, R., 2003. Evaluating environmental Impacts of solid waste management alternatives. BioCycle 44, 52–56.

Beedasy,J., D.,Whyatt.,1999. Diverting the tourists: aspatial decision- support system for tourism planningon a developing island. J. Appl. Earth Observ. Geoinform 3 (4), 163–174.

Bell, N., Schuurman, N., Hayes, M.V., 2007. Using GIS-based methods of multicriteria analysis to construct socio-economic deprivation indices. International Journal of Health Geographics 6 (17). doi:10.1186/1476-072X-6-17.

Boroushaki, S., Malczewski, J., 2010. Using the fuzzy majority approach for GIS based multicriteria group decision-making. Computers and Geosciences 36, 302–312.

Calijuri, M.L., 2004. Multi-criteria analysis for the identification of waste disposal areas. Geotechnical and Geological Engineering 22 (2), 299–312.

Chang, N.B., Parvathinathan, G., Breedenc, J.B., 2008. Combining GIS with fuzzy multicriteria decision-making for landfill siting in a fast-growing urban region. Journal of Environmental Management 87, 139–153.

Chiueh, P.T., Lo, S.L., Chang, C.L., 2008. A GIS-based system for allocating municipal solid waste incinerator compensatory fund. Waste Management 28, 2690–2701.

Gallant, J.C.,Wilson, J. P., 2000. Primary Topographic Attributes. In: Wilson, J. P., Gallant, J. C. (Eds.), Terrain Analysis Principles and Applications. John Wiley & Sons, Inc., NewYork, 51–85.

Gemitzi, A., Tsihrintzis, V.A., Voudrias, V., Petalas, C., Stravodimos, G., 2007. Combining GIS, multicriteria evaluation techniques and fuzzy logic in siting MSW landfills. Environmental Geology 51, 797–811.

Goorah, S., Esmyot, M., Boojhawon, R., 2009. The health impact of nonhazardous Solid waste disposal in a community: the case of the Mare Chicose landfill inMauritius. Journal of Environment Health 72, 48–54.

Gorsevski, P.V., Donevska, K, R., Mitrovski, C, D and Frizado ,J ,P. 2012. Integrating multi-criteria evaluation techniques with geographic information Systems for landfill site selection.

Gorsevski, P.V., Jankowski, P., Gessler, P.E., 2006. An heuristic approach for mapping landslide hazard by integrating fuzzy logic with analytic hierarchy processControl and Cybernetics 35, 121–146.

Gruber,S.,Peckham,S.,2008. Land Surface Parameters and Objectsin Hydrology. In: Hengl,T., Reuter, H.I.(Eds.), Geomorphometry: Concepts, Software, Applications, Developments in Soil Science. Elsevier, Amsterdam 171–194.

Guiqin, W., Li, Q., Guoxue, L., Lijun, C., 2009. Landfill site selection using spatial information technologies and AHP: A case study in Beijing, China. Journal of Environmental Management 90, 2414–2421.

Habibi, K. Lotfi, S. and Koohsari, M. J. 2008 “Spatial Analysis of Urban Fire Station Locations by Integrating AHP Model and IO Logic Using GIS,” Journal of Applied Sciences 8 (19), 2008, 3302-3315.

Jiang, H., Eastman, R.J., 2000. Application of fuzzy measures in multi-criteriaevaluation in GIS. International Journal of Geographical Information Systems 14, 173–184.

Kontos, T.D., Komilis, D.P., Halvadakis, C.P., 2003. Siting MSW landfills on LesvosIsland with a GIS based methodology. Waste Management & Research 21, 262–277.

Kouznetsova, M., Hauang, X., Ma, J., Lessner, L., Carpenter, D., 2007. Increased rate of Hospitalization for diabetes and residential proximity of hazardous waste sites. Environmental Health Perspectives115, 75.

Lober, D.J., 1996. Why not here? The importance of context, process, and outcome on public attitudes toward siting of waste facilities. Society and Natural Resources 9, 375–394.

Makropoulos ,C., D.,Butler, 2005. Spatial ordered weighted averaging: incorporating spatially variable attitude towards risk in spatial multi-criteria decision-making. Environmental Modelling& Software 21 (1), 69–84.

Makropoulos, C., Butler, D., Maksimovic, C., 2003. A fuzzy logic spatial decisionsupport system for urban water management. Journal of Water Resources Planning and Management 129, 69–77.

Malczewski, J. 1999. GIS and Multicriteria Decision Analysis: Evaluation Criteria and Criterion Weighting. John Wiley & Sons, Inc. 392 pp

Malczewski, J., Rinner, C., 2005. Exploring multicriteria decision strategies in GISwith linguistic quantifiers: a case study of residential quality evaluation. Journalof Geographical Systems 7, 249–268.

Malczewski, J, C., Rinner. 2005. Exploring multicriteria decision strategies in GIS with linguistic quantifiers: a case study of residential quality evaluation. Journal of Geographical Systems 7 (2), 249–268

Malczewski,J. 2004. GIS-based land-use suitability analysis: a critical overview. Progr. Plann. 62 (1), 3–65.

Malczewski,J.,1999.GIS and Multi criteria Decision Analysis. John Wiley &SonsInc.,NewYork.

Malczewski, J., etal. 2003. GIS multicriteria evaluation with ordered weighted averaging (OWA): case study of developing watershed management strategies. Environment and Planning A 35 (10), 1769–1784.

Mellers, B., and Chang, S., 1994. “Representations of risk judgments”. Organ Behav Hum Dec 52(7), 167–184.

Rinner, C., Malczewski,J., 2002. Web-enabled spatial decision analysis using Ordered Weighted Averaging(OWA) .Journal of Geographical Systems 4,385-403.

Saaty, T.L., 1980. The Analytic Hierarchy Process. McGraw-Hill, New York.

Sharifi, M.A, Vanwesten. C . J., Siteselection for Wasted is Posal through Spatial Multiple Criteria Decision Making, ITC, 1997.

Wagner,E.D. 2002. Public key infrastructure (PKI) and virtual private network (VPN) compared using a utility function and the analytic hierarchy process (AHP). M.Sc. Thesis,Virginia Polytechnic Institute and State University, 50 pp.

Yager, R.R., 1991. “Connectives and quantifiers in fuzzy sets”, Fuzzy Sets and Systems, 40, 39-76.

Yager, R.R., Filev, D.P., 1999. “Induced ordered weighted averaging operators”, IEEE Transactions on Systems, Man, and Cybernetics- Part B 29, 141–150.

Yager, R. R., 1988. On ordered weighted averaging aggregation operatorsin Multi criteria decision making IEEE Transactionson Systems, Man, and Cybernetics 8, 183–190.