Regional Clusters, Similarities, and Changes in Turkey’s Wood Production: A Comparative Analysis Using K-Means and Ward’s Clustering Methods

This study aimed to separate the wood production in regions and provinces of Turkey into homogeneous groups based on similarities by using the country’s wood production figures for 2013 and 2018. Within this context, the hierarchical Ward’s and non-hierarchical K-means clustering methods were used c...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Rıfat Kurt, Erol İmren
Formato:	article
Lenguaje:	EN
Publicado:	University of Zagreb, Faculty of Forestry and Wood Technology 2021
Materias:	wood production clustering k-means, ward’s method Forestry SD1-669.5
Acceso en línea:	https://doaj.org/article/e1f434b4cf9f4389970918de399386a4
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:e1f434b4cf9f4389970918de399386a4
record_format	dspace
spelling	oai:doaj.org-article:e1f434b4cf9f4389970918de399386a42021-11-26T09:43:11ZRegional Clusters, Similarities, and Changes in Turkey’s Wood Production: A Comparative Analysis Using K-Means and Ward’s Clustering Methods0012-67721847-115310.5552/drvind.2021.2031https://doaj.org/article/e1f434b4cf9f4389970918de399386a42021-01-01T00:00:00Zhttps://hrcak.srce.hr/file/385824https://doaj.org/toc/0012-6772https://doaj.org/toc/1847-1153This study aimed to separate the wood production in regions and provinces of Turkey into homogeneous groups based on similarities by using the country’s wood production figures for 2013 and 2018. Within this context, the hierarchical Ward’s and non-hierarchical K-means clustering methods were used comparatively. Clustering analyses of 2 to 6 in number were performed via both methods, and the same regions mostly fell into the same cluster groups, although in different cluster combinations. The results showed that some provinces with rich forest areas did not produce enough wood. It was observed that these provinces were in the same clusters with provinces having a low amount of forest areas and low wood production. Over the five-year period, very few provinces and regions differed in line with the previous development plans. The creation of a spatial database for wood raw material production using the findings obtained in this study will contribute to the development of operational inventory methods that can be included in long- and medium-term forestry plans.Rıfat KurtErol İmrenUniversity of Zagreb, Faculty of Forestry and Wood Technologyarticlewood productionclusteringk-means, ward’s methodForestrySD1-669.5ENDrvna Industrija, Vol 72, Iss 4, Pp 337-346 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	wood production clustering k-means, ward’s method Forestry SD1-669.5
spellingShingle	wood production clustering k-means, ward’s method Forestry SD1-669.5 Rıfat Kurt Erol İmren Regional Clusters, Similarities, and Changes in Turkey’s Wood Production: A Comparative Analysis Using K-Means and Ward’s Clustering Methods
description	This study aimed to separate the wood production in regions and provinces of Turkey into homogeneous groups based on similarities by using the country’s wood production figures for 2013 and 2018. Within this context, the hierarchical Ward’s and non-hierarchical K-means clustering methods were used comparatively. Clustering analyses of 2 to 6 in number were performed via both methods, and the same regions mostly fell into the same cluster groups, although in different cluster combinations. The results showed that some provinces with rich forest areas did not produce enough wood. It was observed that these provinces were in the same clusters with provinces having a low amount of forest areas and low wood production. Over the five-year period, very few provinces and regions differed in line with the previous development plans. The creation of a spatial database for wood raw material production using the findings obtained in this study will contribute to the development of operational inventory methods that can be included in long- and medium-term forestry plans.
format	article
author	Rıfat Kurt Erol İmren
author_facet	Rıfat Kurt Erol İmren
author_sort	Rıfat Kurt
title	Regional Clusters, Similarities, and Changes in Turkey’s Wood Production: A Comparative Analysis Using K-Means and Ward’s Clustering Methods
title_short	Regional Clusters, Similarities, and Changes in Turkey’s Wood Production: A Comparative Analysis Using K-Means and Ward’s Clustering Methods
title_full	Regional Clusters, Similarities, and Changes in Turkey’s Wood Production: A Comparative Analysis Using K-Means and Ward’s Clustering Methods
title_fullStr	Regional Clusters, Similarities, and Changes in Turkey’s Wood Production: A Comparative Analysis Using K-Means and Ward’s Clustering Methods
title_full_unstemmed	Regional Clusters, Similarities, and Changes in Turkey’s Wood Production: A Comparative Analysis Using K-Means and Ward’s Clustering Methods
title_sort	regional clusters, similarities, and changes in turkey’s wood production: a comparative analysis using k-means and ward’s clustering methods
publisher	University of Zagreb, Faculty of Forestry and Wood Technology
publishDate	2021
url	https://doaj.org/article/e1f434b4cf9f4389970918de399386a4
work_keys_str_mv	AT rıfatkurt regionalclusterssimilaritiesandchangesinturkeyswoodproductionacomparativeanalysisusingkmeansandwardsclusteringmethods AT erolimren regionalclusterssimilaritiesandchangesinturkeyswoodproductionacomparativeanalysisusingkmeansandwardsclusteringmethods
_version_	1718409689508610048

Regional Clusters, Similarities, and Changes in Turkey’s Wood Production: A Comparative Analysis Using K-Means and Ward’s Clustering Methods

Ejemplares similares