Comparison of GIS-based surrogate weighting methods for multi-directional landfill site selection in West Mediterranean Planning Region in Turkey

Abstract

On account of sustainable municipal solid waste (MSW) management, the determination of appropriate positions for MSW multi-directional landfill sites includes thought of geomorphological, topographical, hydrological, monetary and environmental parameters. Deciding these regions in a manner that limits ecological contamination and well-being dangers is a significant multi-criteria decision-making issue in the controls of land executives. A landfill site choice procedure has been completed utilizing three pure weighting techniques (rank sum, rank reciprocal and rank-order centroid) coordinated with geographical information system instruments. The outcomes demonstrate that 32,045 km2 (87.4%) of the total area is inadmissible for landfill sites. This study compares the results of three subjective weighting methods at a large-scale regional planning scenario. The exhibited methodology helps chiefs in deciding safe areas for MSW landfill sites. The results show that in the early period of the spatial planning, simplified pure methods can be adequate. In this case, using more complicated methods will not definitely deduce different findings. However, when regional planning requires identifying the spatial scope of the favored specific sites, considering the intersection area proposed by three methods will be ideal.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

References

  1. Aderoju, O. M., Dias, G. A., & Gonçalves, A. J. (2020). A GIS-based analysis for sanitary landfill sites in Abuja, Nigeria. Environment, Development and Sustainability, 22(1), 551–574.

    Google Scholar 

  2. Ahn, B. S. (2011). Compatible weighting method with rank order centroid: Maximum entropy ordered weighted averaging approach. European Journal of Operational Research, 212(3), 552–559.

    Google Scholar 

  3. Ahn, B. S. (2017). Approximate weighting method for multiattribute decision problems with imprecise parameters. Omega, 72, 87–95.

    Google Scholar 

  4. Ahn, B. S., & Park, K. S. (2008). Comparing methods for multiattribute decision making with ordinal weights. Computers & Operations Research, 35(5), 1660–1670.

    Google Scholar 

  5. Alsamamra, H., Ruiz-Arias, J. A., Pozo-Vázquez, D., & Tovar-Pescador, J. (2009). A comparative study of ordinary and residual Kriging techniques for mapping global solar radiation over southern Spain. Agricultural and Forest Meteorology, 149(8), 1343–1357.

    Google Scholar 

  6. Anagnostopoulos, K. P., Vavatsikos, A. P., Spiropoulos, N., & Kraias, I. (2010). Land suitability analysis for natural wastewater treatment systems using a new GIS add-in for supporting criterion weight elicitation methods. Operational Research, 10(1), 91–108.

    Google Scholar 

  7. Anagnostopoulos, K. P., Vavatsikos, A. P., Spiropoulos, N., & Kraias, I. (2010). Land suitability analysis for natural wastewater treatment systems using a new GIS add-in for supporting criterion weight elicitation methods. Operational Research, 10(1), 91–108.

    Google Scholar 

  8. Asefi, H., & Lim, S. (2017). A novel multi-dimensional modeling approach to integrated municipal solid waste management. Journal of Cleaner Production, 166, 1131–1143.

    Google Scholar 

  9. Baban, S. M. J., & Flannagan, J. (1998). Developing and implementing GIS-assisted constraints criteria for planning landfill sites in the UK. Planning Practice & Research, 13(2), 139–151.

    Google Scholar 

  10. Bahrani, S., Ebadi, T., Ehsani, H., Yousefi, H., & Maknoon, R. (2016). Modeling landfill site selection by multi-criteria decision making and fuzzy functions in GIS, case study: Shabestar, Iran. Environmental Earth Sciences, 75(4), 337.

    Google Scholar 

  11. Barakat, A., Hilali, A., El Baghdadi, M., & Touhami, F. (2017). Landfill site selection with GIS-based multi-criteria evaluation technique. A case study in Béni Mellal-Khouribga Region, Morocco. Environmental Earth Sciences, 76(12), 413.

    Google Scholar 

  12. Barron, F. H., & Barrett, B. E. (1996a). Decision quality using ranked attribute weights. Management Science, 42(11), 1515–1523.

    Google Scholar 

  13. Barron, F. H., & Barrett, B. E. (1996b). The efficacy of SMARTER—Simple multi-attribute rating technique extended to ranking. Acta Psychologica, 93(1–3), 23–36.

    Google Scholar 

  14. Basse, R. M., Charif, O., & Bodis, K. (2016). Spatial and temporal dimensions of land use change in cross border region of Luxembourg. Development of a hybrid approach integrating GIS, cellular automata and decision learning tree models. Applied Geography, 67, 94–108.

    Google Scholar 

  15. Berndt, C., & Haberlandt, U. (2018). Spatial interpolation of climate variables in Northern Germany—Influence of temporal resolution and network density. Journal of Hydrology: Regional Studies, 15, 184–202.

    Google Scholar 

  16. Butler, J., & Olson, D. L. (1999). Comparison of centroid and simulation approaches for selection sensitivity analysis. Journal of Multi-Criteria Decision Analysis, 8(3), 146–161.

    Google Scholar 

  17. Carter, B., & Rinner, C. (2014). Locally weighted linear combination in a vector geographic information system. Journal of Geographical Systems, 16(3), 343–361.

    Google Scholar 

  18. Chabuk, A. J., Al-Ansari, N., Hussain, H. M., Knutsson, S., & Pusch, R. (2017). GIS-based assessment of combined AHP and SAW methods for selecting suitable sites for landfill in Al-Musayiab Qadhaa, Babylon, Iraq. Environmental Earth Sciences, 76(5), 209.

    Google Scholar 

  19. Danielson, M., & Ekenberg, L. (2017). A robustness study of state-of-the-art surrogate weights for MCDM. Group Decision and Negotiation, 26(4), 677–691.

    Google Scholar 

  20. Danielson, M., Ekenberg, L., & He, Y. (2014). Augmenting ordinal methods of attribute weight approximation. Decision Analysis, 11(1), 21–26.

    Google Scholar 

  21. Demesouka, O. E., Anagnostopoulos, K. P., & Siskos, E. (2019). Spatial multicriteria decision support for robust land-use suitability: The case of landfill site selection in Northeastern Greece. European Journal of Operational Research, 272(2), 574–586.

    Google Scholar 

  22. Doljak, D., & Stanojević, G. (2017). Evaluation of natural conditions for site selection of ground-mounted photovoltaic power plants in Serbia. Energy, 127, 291–300.

    Google Scholar 

  23. EEA. (1995). European Environment Agency. Retrieved July 02, 2019 from https://www.eea.europa.eu/publications/COR0-landcover.

  24. Feyzi, S., Khanmohammadi, M., Abedinzadeh, N., & Aalipour, M. (2019). Multi-criteria decision analysis FANP based on GIS for siting municipal solid waste incineration power plant in the north of Iran. Sustainable Cities and Society, 47, 101513.

    Google Scholar 

  25. Gbanie, S. P., Tengbe, P. B., Momoh, J. S., Medo, J., & Kabba, V. T. S. (2013). Modelling landfill location using geographic information systems (GIS) and multi-criteria decision analysis (MCDA): case study Bo, Southern Sierra Leone. Applied Geography, 36, 3–12.

    Google Scholar 

  26. Gigović, L., Pamučar, D., Božanić, D., & Ljubojević, S. (2017). Application of the GIS–DANP–MABAC multi-criteria model for selecting the location of wind farms: A case study of Vojvodina, Serbia. Renewable Energy, 103, 501–521.

    Google Scholar 

  27. Hoornweg, D., & Bhada-Tata, P. (2012). What a waste: A global review of solid waste management (Vol. 15, p. 116). Washington, DC: World Bank.

    Google Scholar 

  28. Jia, J., Fischer, G. W., & Dyer, J. S. (1998). Attribute weighting methods and decision quality in the presence of response error: A simulation study. Journal of Behavioral Decision Making, 11(2), 85–105.

    Google Scholar 

  29. Kamdar, I., Ali, S., Bennui, A., Techato, K., & Jutidamrongphan, W. (2019). Municipal solid waste landfill siting using an integrated GIS–AHP approach: A case study from Songkhla, Thailand. Resources, Conservation and Recycling, 149, 220–235.

    Google Scholar 

  30. Kapilan, S., & Elangovan, K. (2018). Potential landfill site selection for solid waste disposal using GIS and multi-criteria decision analysis (MCDA). Journal of Central South University, 25(3), 570–585.

    Google Scholar 

  31. Karimi, H., Amiri, S., Huang, J., & Karimi, A. (2019). Integrating GIS and multi-criteria decision analysis for landfill site selection, case study: Javanrood County in Iran. International Journal of Environmental Science and Technology, 16(11), 7305–7318.

    Google Scholar 

  32. Karteris, M., Theodoridou, I., Mallinis, G., Tsiros, E., & Karteris, A. (2016). Towards a green sustainable strategy for Mediterranean cities: Assessing the benefits of large-scale green roofs implementation in Thessaloniki, Northern Greece, using environmental modelling, GIS and very high spatial resolution remote sensing data. Renewable and Sustainable Energy Reviews, 58, 510–525.

    Google Scholar 

  33. Khodaparast, M., Rajabi, A. M., & Edalat, A. (2018). Municipal solid waste landfill siting by using GIS and analytical hierarchy process (AHP): A case study in Qom city, Iran. Environmental Earth Sciences, 77(2), 52.

    Google Scholar 

  34. Kirkwood, C. W., & Sarin, R. K. (1985). Ranking with partial information: A method and an application. Operations Research, 33(1), 38–48.

    Google Scholar 

  35. Krige, D. G. (1951). A statistical approach to some basic mine valuation problems on the Witwatersrand. Journal of the Southern African Institute of Mining and Metallurgy, 52(6), 119–139.

    Google Scholar 

  36. Malczewski, J. (2000). On the use of weighted linear combination method in GIS: Common and best practice approaches. Transactions in GIS, 4(1), 5–22.

    Google Scholar 

  37. Mateos, A., Jiménez-Martín, A., Aguayo, E. A., & Sabio, P. (2014). Dominance intensity measuring methods in MCDM with ordinal relations regarding weights. Knowledge-Based Systems, 70, 26–32.

    Google Scholar 

  38. MFWA. (2017). Ministry of Forestry and Water Affairs, 28.10.2017/Regulation No. 30224 on the protection of drinking water basins. (In Turkish).

  39. Michael, E. A., & Samanta, S. (2016). Landslide vulnerability mapping (LVM) using weighted linear combination (WLC) model through remote sensing and GIS techniques. Modeling Earth Systems and Environment, 2(2), 88.

    Google Scholar 

  40. Nasiri, H., Boloorani, A. D., Sabokbar, H. A. F., Jafari, H. R., Hamzeh, M., & Rafii, Y. (2013). Determining the most suitable areas for artificial groundwater recharge via an integrated PROMETHEE II-AHP method in GIS environment (case study: Garabaygan Basin, Iran). Environmental Monitoring and Assessment, 185(1), 707–718.

    Google Scholar 

  41. Reisi, M., Afzali, A., & Aye, L. (2018). Applications of analytical hierarchy process (AHP) and analytical network process (ANP) for industrial site selections in Isfahan, Iran. Environmental Earth Sciences, 77(14), 537.

    Google Scholar 

  42. Rostamzadeh, R., Ghorabaee, M. K., Govindan, K., Esmaeili, A., & Nobar, H. B. K. (2018). Evaluation of sustainable supply chain risk management using an integrated fuzzy TOPSIS–CRITIC approach. Journal of Cleaner Production, 175, 651–669.

    Google Scholar 

  43. Roszkowska, E. (2013). Rank ordering criteria weighting methods—A comparative overview. Optimum Studia Ekonomiczne, 5(65), 14–33.

    Google Scholar 

  44. Sánchez-Lozano, J. M., Antunes, C. H., García-Cascales, M. S., & Dias, L. C. (2014). GIS-based photovoltaic solar farms site selection using ELECTRE-TRI: Evaluating the case for Torre Pacheco, Murcia, Southeast of Spain. Renewable Energy, 66, 478–494.

    Google Scholar 

  45. Stillwell, W. G., Seaver, D. A., & Edwards, W. (1981). A comparison of weight approximation techniques in multiattribute utility decision making. Organizational Behavior and Human Performance, 28(1), 62–77.

    Google Scholar 

  46. Sureeyatanapas, P. (2016). Comparison of rank-based weighting methods for multi-criteria decision making. Engineering and Applied Science Research, 43, 376–379.

    Google Scholar 

  47. Wackernagel, H. (2003). Ordinary Kriging. In Multivariate Geostatistics (pp. 79–88). Berlin: Springer.

  48. Wang, Z., Ren, J., Goodsite, M. E., & Xu, G. (2018). Waste-to-energy, municipal solid waste treatment, and best available technology: Comprehensive evaluation by an interval-valued fuzzy multi-criteria decision making method. Journal of Cleaner Production, 172, 887–899.

    Google Scholar 

  49. Yıldırım, Ü., & Güler, C. (2016). Identification of suitable future municipal solid waste disposal sites for the Metropolitan Mersin (SE Turkey) using AHP and GIS techniques. Environmental Earth Sciences, 75(2), 101.

    Google Scholar 

Download references

Acknowledgements

The authors thank civil engineer Serhan Gedik, geological engineer Hasan Akkoçak and also city and regional planner Mehmet Can Özkurt from General Directorate of Highways, Antalya Metropolitan Municipality, General Directorate of Meteorology in Turkey.

Funding

No funding information available.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Emre Tercan.

Ethics declarations

Conflict of interest

All authors states that there is no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix

Appendix

See Table 5.

Table 5 Limitations weights used in the GIS model

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Dereli, M.A., Tercan, E. Comparison of GIS-based surrogate weighting methods for multi-directional landfill site selection in West Mediterranean Planning Region in Turkey. Environ Dev Sustain 23, 3438–3457 (2021). https://doi.org/10.1007/s10668-020-00725-x

Download citation

Keywords

  • Municipal solid waste
  • Multi-directional landfill site
  • Weighted linear combination
  • GIS
  • Regional planning
  • Subjective weighting