A clustering-based approach to land valuation in land consolidation projects

dc.authoridErtunc, Ela/0000-0002-6982-0459
dc.authoridKARKINLI, AHMET EMIN/0000-0001-7216-6251
dc.contributor.authorErtunc, Ela
dc.contributor.authorKarkinli, Ahmet Emin
dc.contributor.authorBozdag, Asli
dc.date.accessioned2024-11-07T13:31:23Z
dc.date.available2024-11-07T13:31:23Z
dc.date.issued2021
dc.departmentNiğde Ömer Halisdemir Üniversitesi
dc.description.abstractLand valuation is a comprehensive assessment process that aims to assign the agricultural value of all parcels in the land consolidation area, based on soil quality and land productivity (using a relative non-dimensional score). Thus, the land value represents a critical parameter that directly influences the monetary interests of landowners. This process should be managed in a reliable, correct, and fair manner. Furthermore, the traditional land valuation process is time-consuming and costly, and its results may be inconsistent because those who determine the value cannot take into account and compare the land valuation parameters required for all parcels. The solution to these deficiencies requires a new valuation approach. After land consolidation in the project area, the value of the existing parcels must be determined according to certain criteria in order to give to the enterprise land with the equal value to its previous land. In this study, a new land valuation model was developed with the help of clustering algorithms (K-means, K-medoids, Fuzzy C-means) and Weighted Differential Evolution, a heuristic optimization algorithm, using the most basic nine different parameters affecting the land value. The clustering method used in this model performs the valuation by clustering the parcels with common characteristics according to the parameter values. The method in which the cumulative sum of the distances of parcels to the cluster centers is the shortest exhibits the best clustering performance. In this study, the best clustering performance was obtained with the WDE-based clustering algorithm. When compared with the other algorithm results by mapping the classical valuation results, it was determined that the clustering method results evaluated the parcels more precisely. The study contributes to the literature in terms of including in the developed method parameters other than those used in the existing methods and determining the land value more precisely, fairly, and reliably with the help of heuristic algorithms.
dc.identifier.doi10.1016/j.landusepol.2021.105739
dc.identifier.issn0264-8377
dc.identifier.issn1873-5754
dc.identifier.scopus2-s2.0-85116312083
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1016/j.landusepol.2021.105739
dc.identifier.urihttps://hdl.handle.net/11480/14814
dc.identifier.volume111
dc.identifier.wosWOS:000725642800008
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier Sci Ltd
dc.relation.ispartofLand Use Policy
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241106
dc.subjectLand valuation
dc.subjectLand consolidation
dc.subjectK-means
dc.subjectK-medoids
dc.subjectFuzzy C-means
dc.subjectFuzzy Weighted differential evolution algorithm
dc.titleA clustering-based approach to land valuation in land consolidation projects
dc.typeArticle

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