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Choice of abandoned territories conversion scenario according to MCDA methods

    Vytautas Bielinskas Affiliation
    ; Marija Burinskienė Affiliation
    ; Askoldas Podviezko Affiliation

Abstract

Urban brownfields are found in all parts of the world. They suffer from a negative image and are generally being viewed as problem areas. However, urban brownfields also offer potentials for new uses and for the ecological regeneration of cities. Strategic decision-making has a long term impact on the quality of life, ecological balance and urban structure. Therefore, the paper is aimed at providing a methodology for selecting the optimal scenario for urban brownfields regarding criteria for urban development and focuses on three possible scenarios representing sustainable urban development in the city. The results of the research are provided as a priority list for each scenario in the context of every neighbourhood of Vilnius city. The obtained results show the scenario optimal for each neighbourhood having the highest priority to implementing solutions in real life. Economic, social, physical (urbanistic) and environmental criteria are considered. Geographic information system (GIS) tools are employed for collecting spatial information, obtaining the initial set of criteria and deriving statistical data. Different MCDA methods, including TOPSIS, EDAS, COPRAS and SAW are used in the research. The correlation between the values of the sets pairs of cumulative criteria for the applied MCDA methods appeared to be satisfactory for the conducted re-search. The developed framework will support the decision-making process in brownfield land redevelopment aiding sustainable urban planning.

Keyword : urban brownfields, urban planning, urban indicators, MCDA, EDAS, COPRAS, TOPSIS

How to Cite
Bielinskas, V., Burinskienė, M., & Podviezko, A. (2018). Choice of abandoned territories conversion scenario according to MCDA methods. Journal of Civil Engineering and Management, 24(1), 79-92. https://doi.org/10.3846/jcem.2018.303
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Mar 9, 2018
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This work is licensed under a Creative Commons Attribution 4.0 International License.

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