MODEL OF THE PROCESS OF GEOSPATIAL MULTI-CRITERIA DECISION ANALYSIS FOR TERRITORIAL PLANNING
Keywords:geographic information systems, spatial modeling, multicriteria decision analysis, fuzzy sets
Context. The process of multi-criteria decision analysis for territorial planning and rational placement of spatial objects, based on modeling the properties of the territory, is considered.
Objective. Development of technology for multi-criteria decision analysis for territorial planning based on the apparatus of the theory of fuzzy sets and functions of geoinformation analysis.
Method. An object-spatial approach to the formation of a set of alternatives and criteria is proposed, according to which the process of multicriteria decision analysis is divided into two stages: macro- and microanalysis.The macroanalysis stage involves the assessment of the ecological and socio-economic properties of the territory using geomodeling functions. The paper provides a formalized description of the macroanalysis stage, including methods for assessing the qualitative and quantitative impact of spatial objects on the properties of the territory and decomposing objects into thematic layers of criteria. At the stage of microanalysis, the ranking of alternatives is performed taking into account the chosen decision-making strategy. The method of standardization of criteria attributes using fuzzy set membership functions and the modification of the method for calculating the coefficients of relative importance (weights) of criteria, taking into account the spatial heterogeneity of the preferences of the decision maker, are considered. A comparative analysis of the methods for aggregating the estimates of alternatives according to different criteria has been carried out. A feature of the presented technology of geospatial multi-criteria decision analysis of decisions for territorial planning is the possibility of its integration into modern geographic information systems.
Results. The procedure of geospatial multi-criteria decision analysis was implemented in the environment of the geographic information system ESRI ArcGIS 10.5 and was studied in solving the spatial problem of rational location of an enterprise.
Conclusions. The proposed object-spatial approach to multi-criteria decision analysis makes it possible to explicitly take into account the spatial heterogeneity of geographic data, which is the result of the influence of geographic objects on the properties of the territory. The developed technology can be used to solve a wide range of problems related to determining the most rational placement of various capital construction and infrastructure facilities.
Chakhar S., Mousseau V. Spatial multicriteria decision making, Encyclopedia of GIS. New York, Springer-Verlag, 2008, pp. 747–753. DOI:10.1007/978-3-319-23519-6_839-2
Chakhar S., Martel J. M. Enhancing geographical information systems capabilities with multicriteria evaluation functions, Journal of Geographic Information and Decision Analysis, 2003, Vol. 7, No. 2, pp. 69–71.
Malczewski J. GIS-based multicriteria decision analysis: a survey of the literature, International Geographical Information Science, 2006, Vol. 20, No. 7, pp. 703–726.
Malczewski J., Rinner C. Multicriteria Decision Analysis in Geographic Information Science. New York, Springer, 2015, 331 p. DOI:10.1007/978-3-540-74757-4
Lidouh K. On themotivation behind MCDA and GIS integration, Multicriteria Decision Making, 2013, Vol. 3, No. 2/3, pp. 101–113. DOI:10.1504/ IJMCDM.2013.053727
Afshari A., Vatanparast M., Ćoćkalo D. Application of multi criteria decision making to urban planning – a review, Journal of Engineering Management and Competitiveness, 2016, Vol. 6, Issue 03, pp. 46–53.
Cegan J., Filion A., Keisler J. Trends and applications of multi-criteria decision analysis in environmental sciences: literature review, Environment Systems and Decisions. – 2017, Vol. 37, pp. 1–11. DOI: 10.1007/s10669-017-9642-9.
Mardani A., Jusoh A., Nor M. D. et al.] Multiple criteria decision-making techniques and their applications – a review of the literature from 2000 to 2014, Economic Research, 2015, Vol. 28, No. 1, pp. 516–571. DOI: 10.1080/1331677X.2015.1075139
Chaoxu L., Renzhi L., Sicheng P. Land-use suitability assessment for urban development using a GIS-based soft computing approach: A case study of Ili Valley, China, Ecological Indicators, 2021, Vol. 123, pp. 1–13. DOI:10.1016/j.ecolind.2020.107333
Malczewski J. GIS-based land-use suitability analysis: a critical overview, Progress in Planning, 2004, Vol. 62, Issue 1, pp. 3–65. DOI:10.1016/ j.progress.2003.09.002
Rikalovic A., Cosic I., Lazarevic D. GIS Based MultiCriteria Analysis for Industrial Site Selection, Procedia Engineering, 2014, Vol. 69, No. 12, pp. 1054–1063. DOI: 10.1016/j.proeng.2014.03.090
Samani Z. N., Karimi M., Alesheikh A. A. A Novel Approach to Site Selection: Collaborative Multi-Criteria Decision Making through Geo-Social Network (Case Study: Public Parking), International Journal Geo-Information, 2018, Vol. 7, Issue 3. DOI:10.3390/ ijgi7030082
Lokhande T. I., Mane S. J., Mali S. T. Landfill Site Selection using GIS and MCDA Methods: A Review, International Journal of Research in Engineering, Science and Technology, 2017, Vol. 3, No. 3, pp. 25–30.
Kuznichenko S., Buchynska I., Kovalenko L. et al. Suitable site selection using two-stage GIS-based fuzzy multi-criteria decision analysis, Advances in Intelligent Systems and Computing, 2020, No. 1080, pp. 214–230. DOI:10.1007/978-3-030-33695-0_16
Kuznichenko S., Kovalenko L., Buchynska I. et al. Development of a multi-criteria model for making decisions on the location of solid waste landfills, Eastern-European Journal of Enterprise Technologies, 2018, Vol. 2, No. 3(92), pp. 21–31. DOI: 10.15587/1729-4061.2018.129287
Kuznichenko S., Buchynska I., Kovalenko L. et al. Integrated information system for regional flood monitoring using internet of things, CEUR Workshop Proceedings, 2019, Vol. 2683, pp. 1–5.
Karpinski M., Kuznichenko S., Kazakova N. et al. Geospatial Assessment of the Territorial Road Network by Fractal Method, Future Internet, 2020, Vol. 12, Issue 201. DOI: 10.3390/fi12110201.
Kuznichenko S., Buchynska I. A fuzzy approach for determining the cognitive spatial location of an object in geographical information system, Eastern-European Journal of Enterprise Technologies, 2021, Vol. 6, No. 9(114), pp. 24–31. DOI: 10.15587/1729-4061.2021.246556
Zadeh L. A. Fuzzy sets, Information and Control, 1965, Vol. 8, No. 3, pp. 338–353.
Malczewski J. On the use of weighted linear combination method in GIS: common and best practice approaches, Transactions in GIS, 2002, Vol. 4, No. 1, pp. 5–22. DOI: 10.1111/1467-9671.00035
Saaty T. L. The analytic hierarchy process: planning, priority setting, resource allocation. New York, McGrawHill, 1980, 287 p.
Hwang C. L., Yoon K. Multiple attribute decision making: methods and applications a state-of-the-art survey. New York, Springer-Verlag, 1981, 269 p. DOI:10.1007/978-3-642-48318-9
Roy B. Multi-criteria methodology for decision aiding / B. Roy. – Springer Science+Business Media, 1996. – 292 p. DOI:10.1007/978-1-4757-2500-1
Vahidnia M. H., Alesheikh A. A., Alimohammadi A. Fuzzy analytical hierarchy process in GIS application, Photogrammetry, Remote Sensing and Spatial Information Sciences, 2008, Vol. 37, pp. 593-596.
Chen Y., Yu J., Khan S. The spatial framework for weight sensitivity analysis in AHP-based multi-criteria decision making, Environmental modelling & software, 2013, Vol. 48, pp. 129–140. DOI: 10.1016/ j.envsoft.2013.06.010
Ligmann-Zielinska A., Jankowski P. Spatially-explicit integrated uncertainty and sensitivity analysis of criteria weights in multicriteria land suitability evaluation, Environmental Modelling & Software, 2014, Vol. 57, pp. 235–247. DOI: 10.1016/j.envsoft.2014.03.007
Malczewski J., Jankowski P. Emerging trends and research frontiers in spatial multicriteria analysis, International Journal of Geographical Information Science, 2020, Vol. 34:7, pp. 1257–1282. DOI: 10.1080/13658816.2020.1712 403
Lloyd C. D. Local models for spatial analysis. Boca Raton, CRC Press, 2010, 352 p.
Keller L.R., Simon J. Preference functions for spatial risk analysis, Risk Analysis, 2019, Vol. 39 (1), pp. 44–256.
Malczewski J., Liu X. Local ordered weighted averaging in GIS-based multicriteria analysis, Annals of GIS, 2014, Vol. 20, No. 2, pp. 117–129. DOI: 10.1111/risa.12892
Jankowski P. Behavioral decision theory in spatial decisionmaking models, Handbook of behavioral and cognitive geography. U.K.: Edward Elgar Pub, 2018, Ch. 3, pp. 41–55. DOI: 10.4337/9781784717544. 00009
Ligmann-Zielinska A., Jankowski P. Impact of proximityadjusted preferences on rank-order stability in geographical multicriteria decision analysis, Journal of Geographical Systems, 2012, Vol. 14, No. 2, pp. 167–187 DOI: 10.1007/s10109-010-0140-6
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