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Πεδίο DCΤιμήΓλώσσα
dc.contributor.authorDemetriou, Demetris-
dc.contributor.authorSee, Linda-
dc.contributor.authorStillwell, John-
dc.date.accessioned2023-09-18T08:55:55Z-
dc.date.available2023-09-18T08:55:55Z-
dc.date.issued2013-12-01-
dc.identifier.citationInternational Journal of Geographical Information Science, 2013, vol. 27, iss. 12, pp. 2391 - 2409en_US
dc.identifier.issn13658816-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/30429-
dc.description.abstractLand fragmentation is a widespread situation which may often hinder agricultural development. Land consolidation is considered to be the most effective land management planning approach for controlling land fragmentation and hence improving agricultural efficiency. Land partitioning is a basic process of land consolidation that involves the subdivision of land into smaller sub-spaces subject to a number of constraints. This paper explains the development of a module called LandParcelS (Land Parcelling System) that is a part of an integrated planning and decision support system called LACONISS (LAndCONsolidation Integrated Support System) which has been developed to assist land consolidation planning in Cyprus. LandParcelS automates the land partitioning process by designing and optimising land parcels in terms of their shape, size and value. The methodology integrates geographical information systems and a genetic algorithm that has been applied to two land blocks that are part of a larger case study area in Cyprus. Partitioning is treated as either a single or multi-objective problem for various optimisation cases. The results suggest that a step forward has been made in solving this complex spatial problem, although further research is needed to improve the algorithm. This approach may have relevance to other spatial planning tasks that involve single or multi-objective optimisation problems, especially those dealing with space partitioning. © 2013 © Taylor & Francis.en_US
dc.language.isoenen_US
dc.relation.ispartofInternational Journal of Geographical Information Scienceen_US
dc.rights© Taylor & Francisen_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectgenetic algorithmsen_US
dc.subjectGISen_US
dc.subjectland partitioningen_US
dc.subjectsingle and multi-objective optimisationen_US
dc.subjectThiessen polygonsen_US
dc.titleA spatial genetic algorithm for automating land partitioningen_US
dc.typeArticleen_US
dc.collaborationUniversity of Leedsen_US
dc.collaborationInternational Institute for Applied Systems Analysisen_US
dc.subject.categoryCivil Engineeringen_US
dc.journalsSubscriptionen_US
dc.countryUnited Kingdomen_US
dc.countryAustriaen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.1080/13658816.2013.819977en_US
dc.identifier.scopus2-s2.0-84887122596-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/84887122596-
dc.relation.issue12en_US
dc.relation.volume27en_US
cut.common.academicyear2012-2013en_US
dc.identifier.spage2391en_US
dc.identifier.epage2409en_US
item.fulltextNo Fulltext-
item.languageiso639-1en-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.cerifentitytypePublications-
item.openairetypearticle-
crisitem.journal.journalissn1362-3087-
crisitem.journal.publisherTaylor & Francis-
crisitem.author.deptDepartment of Civil Engineering and Geomatics-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0002-6121-5932-
crisitem.author.parentorgFaculty of Engineering and Technology-
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