A Multi-criteria GIS Based Methodology for Smart Cities Site Selection

  • Nada A. Fashal
  • Ghada A. El KhayatEmail author
  • Boshra B. Salem
  • Saleh M. El Kaffas
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 947)


Building a Smart City (SC) is a practically irreversible decision that needs large investments. The success of a smart city in realizing its objectives of economic prosperity largely depends on its ability to reach its full potential; which in turn depends on its location. This research contributes a site selection method for SCs that satisfies the decision maker’s criteria. Through the analysis of relevant literature, the main criteria to be considered when locating a SC were identified. Interviews with subject matter experts enabled retaining the most relevant criteria to the Egyptian reality. Layers corresponding to these criteria were built in a Geographic Information System (GIS). The Intersect process was then applied to perform site selection and identify the region respecting the decision maker’s criteria. The developed GIS-Based Multi-Criteria Evaluation (MCE) methodology was tested on a study area that spans Alexandria, El Beheira and Matrouh governorates in Egypt. The prototype developed is a very beneficial instrument that enables facts based decision making as opposed to the current subjective practices used in selecting a SC location.


Geographic Information Systems (GIS) Smart Cities (SC) Knowledge Precincts (KP) Site selection Multi-Criteria Evaluation (MCE) Decision support Location analysis 



The authors would like to thank Mr. Ahmed El-Sobky (ITIDA and Chairman of Silicon Waha), Dr. Mohamed Meheina (Bibliotheca Alexandrina), Dr Walaa Sheta (Dean of the Institute of Informatics) and Eng. Mohamed Hanafy (ITI) who acted as subject matter experts in this research.


  1. 1.
    Komninos, N.: Intelligent cities: variable geometries of spatial intelligence. Intell. Build. Int. 3(3), 172–188 (2011)CrossRefGoogle Scholar
  2. 2.
    Kourtit, K., Nijkamp, P.: Smart cities in the innovation age. Innov. Eur. J. Soc. Sci. Res. 25(2), 93–95 (2012)CrossRefGoogle Scholar
  3. 3.
    Roche, S.: Geographic Information Science I: why does a smart city need to be spatially enabled? Prog. Hum. Geogr. 38(5), 703–711 (2014)CrossRefGoogle Scholar
  4. 4.
    Chan, K., Lau, T.: Assessing technology incubator programs in the science park: the good, the bad and the ugly. Technovation 25(10), 1215–1228 (2005)CrossRefGoogle Scholar
  5. 5.
    Westhead, P., Batstone, S., Martin, F.: Technology-based firms located on science parks: the applicability of Bullock’s ‘soft-hard’ model. Enterp. Innov. Manag. Stud. 1(2), 107–139 (2000)CrossRefGoogle Scholar
  6. 6.
    Yigitcanlar, T.A., Martinez-Fernandez, M.C.: Making space and place for knowledge production: knowledge precinct developments in Australia (2007)Google Scholar
  7. 7.
    Yigitcanlar, T.A.: Knowledge-based urban development. In: Mehdi, K.-P. (ed.) Encyclopedia of Information Science and Technology, 3rd edn, pp. 7475–7485. IGI Global, Hershey (2015)CrossRefGoogle Scholar
  8. 8.
    Yigitcanlar, T., Velibeyoglu, K., Martinez-Fernandez, C.: Rising knowledge cities: the role of urban knowledge precincts. J. Knowl. Manag. 12(5), 8–20 (2008)CrossRefGoogle Scholar
  9. 9.
    Yigitcanlar, T.: Evolving definition of knowledge cities. Int. J. Knowl.-Based Dev. 8(1), 1–4 (2017)Google Scholar
  10. 10.
    Huggins, R.: The evolution of knowledge clusters: progress and policy. Econ. Dev. Q. 22(4), 277–289 (2008)CrossRefGoogle Scholar
  11. 11.
    Luis Arboníes, A., Moso, M.: Basque Country: the knowledge cluster. J. Knowl. Manag. 6(4), 347–355 (2002)CrossRefGoogle Scholar
  12. 12.
    Garcia, B.C.: Developing futures: a knowledge-based capital for Manchester. J. Knowl. Manag. 8(5), 47–60 (2004)CrossRefGoogle Scholar
  13. 13.
    Scott, A.J.: Technopolis: high-technology industry and regional development in Southern California (1993)Google Scholar
  14. 14.
    Smilor, R.W., Gibson, D.V., Kozmetsky, G.: Creating the technopolis: high-technology development in Austin, Texas. J. Bus. Ventur. 4(1), 49–67 (1989)CrossRefGoogle Scholar
  15. 15.
    Anttiroiko, A.-V.: Science cities: their characteristics and future challenges. Int. J. Technol. Manage. 28(3–6), 395–418 (2004)CrossRefGoogle Scholar
  16. 16.
    Larsen, K.: Learning cities: the new recipe in regional development. Organisation for Economic Cooperation and Development. The OECD Observer, no. 217/218, p. 73 (1999)Google Scholar
  17. 17.
    Komninos, N.: Intelligent Cities: Innovation, Knowledge Systems, and Digital Spaces. Taylor & Francis, London (2002)Google Scholar
  18. 18.
    Camagni, R., Capello, R., Nijkamp, P.: Towards sustainable city policy: an economy-environment technology nexus. Ecol. Econ. 24(1), 103–118 (1998)CrossRefGoogle Scholar
  19. 19.
    Yigitcanlar, T.: Technology and the City: Systems, Applications and Implications. Routledge, New York (2016)CrossRefGoogle Scholar
  20. 20.
    Anthopoulos, L., Fitsilis, P.: From digital to ubiquitous cities: defining a common architecture for urban development, pp. 301–306. IEEE (2010)Google Scholar
  21. 21.
    Couclelis, H.: The construction of the digital city. Environ. Plan. 31(1), 5–19 (2004)CrossRefGoogle Scholar
  22. 22.
    Cocchia, A.: Smart and digital city: a systematic literature review. In: Dameri, R.P., Rosenthal-Sabroux, C. (eds.) Smart City. PI, pp. 13–43. Springer, Cham (2014). Scholar
  23. 23.
    Szymańska, A.I., Płaziak, M.: Enterprise and classical factors of its location on the market. Procedia-Soc. Behav. Sci. 120, 13–22 (2014)CrossRefGoogle Scholar
  24. 24.
    Alraouf, A.A.: Knowledge cities: examining the discourse smart villages, internet cities or creativity engines. Plan. Malaysia J. 4(1), 31–48 (2006)Google Scholar
  25. 25.
    Revelle, C.S., Eiselt, H.A., Daskin, M.S.: A bibliography for some fundamental problem categories in discrete location science. Eur. J. Oper. Res. 184(3), 817–848 (2008)MathSciNetCrossRefGoogle Scholar
  26. 26.
    Vito, A., Giuseppe, D., Guido, S.: A decision based support system based on GIS technology. In: Nilmini, W., Eliezer, G. (eds.) Encyclopedia of Healthcare Information Systems, pp. 383–390. IGI Global, Hershey (2008)Google Scholar
  27. 27.
    Captivo, M.E., Clímaco, J., Fernandes, S.: A bicriteria DSS dedicated to location problems. In: Encyclopedia of Decision Making and Decision Support Technologies, vol. 1, pp. 53–60 (2008)Google Scholar
  28. 28.
    Jones, C.B.: Geographical Information Systems and Computer Cartography. Routledge, London (2014)Google Scholar
  29. 29.
    Chakraborty, D., Sahoo, R.: Fundamentals of Geographic Information System. Viva Books, New Delhi (2007)Google Scholar
  30. 30.
    Huisman, O., De By, R.: Principles of Geographic Information Systems. ITC Educational Textbook Series, vol. 1, p. 17 (2009)Google Scholar
  31. 31.
    Belka, K.: Multicriteria analysis and GIS application in the selection of sustainable motorway corridor. Institutionen för datavetenskap (2005)Google Scholar
  32. 32.
    Schneider, M.: Spatial data types: conceptual foundation for the design and implementation of spatial database systems and GIS (1999)Google Scholar
  33. 33.
    Sugumaran, R., Degroote, J.: Spatial Decision Support Systems: Principles and Practices. CRC Press, Boca Raton (2010)CrossRefGoogle Scholar
  34. 34.
    Information Resources Management Association: Geographic Information Systems: Concepts, Methodologies, Tools, and Applications: Concepts, Methodologies, Tools, and Applications. Information Science Reference (2012)Google Scholar
  35. 35.
    Yeh, A.G.-O.: Urban planning and GIS. Geogr. Inf. Syst. 2(877–888), 1 (1999)Google Scholar
  36. 36.
    Chakhar, S., Mousseau, V.: Spatial multicriteria decision making. In: Encyclopedia of Geographic Information Science, pp. 747–753 (2008)Google Scholar
  37. 37.
    Raikov, A.N.: Strategic planning of science city socioeconomic development. In: Alexandrov, D.A., Boukhanovsky, A.V., Chugunov, A.V., Kabanov, Y., Koltsova, O. (eds.) DTGS 2017. CCIS, vol. 745, pp. 295–306. Springer, Cham (2017). Scholar
  38. 38.
    Fashal, N.A., El Khayat, G.A.: A survey on knowledge precincts location problems and their GIS tools. In: Proceedings of ICT in Our Lives, Alexandria, Egypt, 19–21 December 2015, pp. 59–64 (2015)Google Scholar
  39. 39.
    Rikalovic, A., Cosic, I., Lazarevic, D.: GIS based multi-criteria analysis for industrial site selection. Procedia Eng. 69, 1054–1063 (2014)CrossRefGoogle Scholar
  40. 40.
    Raikov, A.N., Avdeeva, Z., Ermakov, A.: Big data refining on the base of cognitive modeling. IFAC-PapersOnLine 49(32), 147–152 (2016)CrossRefGoogle Scholar
  41. 41.
    Xu, L., Yang, J.-B.: Introduction to multi-criteria decision making and the evidential reasoning approach. Manchester School of Management Manchester (2001)Google Scholar
  42. 42.
    San Cristobal, J.R.: Multi Criteria Analysis in the Renewable Energy Industry. Green Energy and Technology. Springer, Heidelberg (2012). Scholar
  43. 43.
    Malczewski, J.: GIS-based multicriteria decision analysis: a survey of the literature. Int. J. Geogr. Inf. Sci. 20(7), 703–726 (2006)CrossRefGoogle Scholar
  44. 44.
    Nyeko, M.: GIS and multi-criteria decision analysis for land use resource planning. J. Geogr. Inf. Syst. 4(04), 341–348 (2012)Google Scholar
  45. 45.
    Phua, M.-H., Minowa, M.: A GIS-based multi-criteria decision making approach to forest conservation planning at a landscape scale: a case study in the Kinabalu Area, Sabah, Malaysia. Landscape Urban Plan. 71(2–4), 207–222 (2005)CrossRefGoogle Scholar
  46. 46.
    Chang, N.-B., Parvathinathan, G., Breeden, J.B.: Combining GIS with fuzzy multicriteria decision-making for landfill siting in a fast-growing urban region. J. Environ. Manage. 87(1), 139–153 (2008)CrossRefGoogle Scholar
  47. 47.
    Chandio, I.A., Matori, A.N.B.: Land suitability analysis using geographic information systems (GIS) for hillside development: a case study of Penang Island (2011)Google Scholar
  48. 48.
    Van Haaren, R., Fthenakis, V.: GIS-based wind farm site selection using Spatial Multi-Criteria Analysis (SMCA): evaluating the case for New York State. Renew. Sustain. Energy Rev. 15(7), 3332–3340 (2011)CrossRefGoogle Scholar
  49. 49.
    Chen, H., Wood, M., Linstead, C., Maltby, E.: Uncertainty analysis in a GIS-based multi-criteria analysis tool for river catchment management. Environ. Model Softw. 26(4), 395–405 (2011)CrossRefGoogle Scholar
  50. 50.
    Pedrero, F., Albuquerque, A., do Monte, H.M., Cavaleiro, V., Alarcón, J.J.: Application of GIS-based multi-criteria analysis for site selection of aquifer recharge with reclaimed water. Resour. Conserv. Recycl. 56(1), 105–116 (2011)CrossRefGoogle Scholar
  51. 51.
    Sumathi, V., Natesan, U., Sarkar, C.: GIS-based approach for optimized siting of municipal solid waste landfill. Waste Manag. 28(11), 2146–2160 (2008)CrossRefGoogle Scholar
  52. 52.
    Vahidnia, M.H., Alesheikh, A.A., Alimohammadi, A.: Hospital site selection using fuzzy AHP and its derivatives. J. Environ. Manage. 90(10), 3048–3056 (2009)CrossRefGoogle Scholar
  53. 53.
    Yalcin, M., Gul, F.K.: A GIS-based multi criteria decision analysis approach for exploring geothermal resources: Akarcay basin (Afyonkarahisar). Geothermics 67, 18–28 (2017)CrossRefGoogle Scholar
  54. 54.
    Bajracharya, B., Too, L., Imukuka, J.K., Hearn, G.N.: Developing knowledge precincts in regional towns: opportunities and challenges (2009)Google Scholar
  55. 55.
    El Khayat, G.A., Fashal, N.A.: Inter and intra cities smartness: a survey on location problems and GIS tools. In: Sami, F., Khaoula, M. (eds.) Handbook of Research on Geographic Information Systems Applications and Advancements, pp. 296–320. IGI Global, Hershey (2017)CrossRefGoogle Scholar
  56. 56.
    Pucha-Cofrep, F., Fries, A., Cánovas-García, F., Oñate-Valdivieso, F., González-Jaramillo, V., Pucha Cofrep, D.: Fundamentals of GIS (2018)Google Scholar
  57. 57.
    Hansen, H.S.: GIS-based multi-criteria analysis of wind farm development, pp. 75–78. Citeseer (2005)Google Scholar
  58. 58.
    Jankowski, P.: Integrating geographical information systems and multiple criteria decision-making methods. Int. J. Geogr. Inf. Syst. 9(3), 251–273 (1995)CrossRefGoogle Scholar
  59. 59.
    Ellen, Y., Nicholas, S.: A learner-centered approach to technology integration: online geographical tools in the ESL classroom. In: Jared, K., Grace, O. (eds.) Handbook of Research on Learner-Centered Pedagogy in Teacher Education and Professional Development, pp. 1–22. IGI Global, Hershey (2017)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Nada A. Fashal
    • 1
  • Ghada A. El Khayat
    • 1
    Email author
  • Boshra B. Salem
    • 2
  • Saleh M. El Kaffas
    • 3
  1. 1.Faculty of CommerceAlexandria UniversityAlexandriaEgypt
  2. 2.Faculty of ScienceAlexandria UniversityAlexandriaEgypt
  3. 3.Faculty of Computers and InformationArab Academy for Science and Technology and Maritime TransportAlexandriaEgypt

Personalised recommendations