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Statistical methods in landscape architecture for different research purposes

dc.contributor.authorAltay, Elvan Ender
dc.contributor.buuauthorENDER ALTAY, ELVAN
dc.contributor.departmentMimarlık Fakültesi
dc.contributor.departmentPeyzaj Mimarlığı Bölümü
dc.contributor.scopusid57743628300
dc.date.accessioned2025-11-28T12:58:05Z
dc.date.issued2025-06-20
dc.description.abstractLandscape architecture can be addressed and nourished in multiple scientific fields. Landscape architecture, which can touch on different points from design to the human mind or the protection of nature, therefore needs to diversify its analytical studies. Therefore, it is necessary to deal with different datasets produced or evaluated in academic research. There is an increasing need for studies that combine datasets that can be used for different purposes and are open to different evaluations. Recently, the issue of preventing destructive effects on the environment or making these effects more tolerable in residential areas has been intensively researched. For this reason, the accurate evaluation of multiple factors and effects is only possible using various statistical methods. However, it may be challenging to choose the most suitable or accurate method for this study among the possibilities. The primary aim of this chapter was to determine the most frequently used statistical methods in landscape architecture. It also provides an essential perspective on which studies these methods are mainly suitable and what purposes they can serve.
dc.identifier.endpage178
dc.identifier.isbn[9798895304624, 9798895306505]
dc.identifier.scopus2-s2.0-105013007689
dc.identifier.startpage155
dc.identifier.urihttps://hdl.handle.net/11452/57151
dc.indexed.scopusScopus
dc.language.isoen
dc.publisherNova Science Publishers Inc.
dc.relation.journalLandscape Planning Sustainable Practices Design and Urban Development
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectStatistical methods
dc.subjectLandscape architecture
dc.subjectEnvironment
dc.subject.scopusGeographically Weighted Regression in Spatial Analysis
dc.titleStatistical methods in landscape architecture for different research purposes
dc.typeBook Chapter
dspace.entity.typePublication
local.contributor.departmentMimarlık Fakültesi/Peyzaj Mimarlığı Bölümü
local.indexed.atScopus
relation.isAuthorOfPublication0269e919-80c7-4f64-8e94-379e6ab0e344
relation.isAuthorOfPublication.latestForDiscovery0269e919-80c7-4f64-8e94-379e6ab0e344

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