Türkiye’de Orman Bölge Müdürlüklerinin Endüstriyel Odun Üretim Miktarı İstatistiklerinin Benzerliklerinin Kümeleme ve Diskriminant Analizi ile Araştırılması

Year 2019, Volume: 19 Issue: 2, 214 - 224, 30.09.2019

İlker Akyüz Nadir Ersen Bahadır Çağrı Bayram Mustafa Acar Kadri Cemil Akyüz Tutku Üçüncü

https://doi.org/10.17475/kastorman.625588

Abstract

Çalışmanın amacı: Bu çalışmada orman
bölge müdürlüklerinin endüstriyel odun üretim miktarları detaylı bir şekilde
incelenmiş olup, endüstriyel odun üretimi bakımından bölge müdürlüklerinin
benzerlikleri küme ve diskriminant analiz yardımıyla araştırılmıştır.

Çalışma alanı: Türkiye’deki orman
bölge müdürlükleri çalışma alanını oluşturmaktadır.

Materyal ve Yöntem: Benzer özellikleri
taşıyan kümeleri oluşturmak için yedi farklı değişken kullanılmıştır. Bu
değişkenlerin 2013-2016 yıllarındaki değerlerinin ortalaması alınmıştır.
Araştırma yöntemi olarak ise kümeleme analizi ve diskriminant analizi
kullanılmıştır.

Sonuçlar: Kümeleme analizi
sonucuna göre, orman bölge müdürlüklerini en fazla 6 ve en az 2 gruba
ayrılabileceği tespit edilmiştir. Oluşturulan gruplamalardan en yüksek başarıyı
belirlemek için yürütülen ayırma analizi sonucunda orman bölge müdürlüklerinin
6’li gruplamada %100 başarı elde ettiği saptanmıştır. Ayrıca, endüstriyel odun
üretiminde en yüksek değere sahip olan Kastamonu orman bölge müdürlüğünün tek
başına bir grup oluşturduğu bulunmuştur.

Önemli Vurgular: Endüstriyel odun
üretimi için orman bölge müdürlükleri orman alanlarının kullanımı ile ilgili
çalışmalara daha fazla önem vererek dışa bağımlılığın önüne geçebiliriz.

Keywords

Endüstriyel Odun, Kümeleme Analizi, Diskriminant Analizi

Investigation of the Similarities of Industrial Wood Production Statistics of Regional Directorates of Forestry in Turkey Using Cluster and Discriminant Analysis

Abstract

Aim of study: In this study, the amount of industrial wood production of the
regional directorates of forestry in Turkey was examined deeply and the
similarities between the regional directorates in industrial wood production
were investigated by cluster and discriminant analysis.

Area of study: The study area is regional directorates of forestry in Turkey.

Material and Method: Seven different variables were used to construct similar clusters. The
arithmetic mean of these seven variables was taken for 4 years (2013-2016).  Cluster and discriminant analysis were used
as method.

Main results: According to the clustering analysis results, it was determined that
regional directorates of forestry could be divided into maximum 6 and minimum 2
groups. As a result of the discriminant analysis conducted to determine the
highest success of the groupings, it was determined that the regional
directorates of forestry distinguished in 100% success in 6 groups. Also, it
was found that a Kastamonu regional directorate of forestry, which has the
highest value in industrial wood production, has formed a group alone.

Highlights: For the production of industrial wood, the regional directorates of
forestry can put more emphasis on the use of forest areas. Thus, we can avoid
the dependence on foreign sources.

Keywords

Industrial Wood, Cluster Analysis, Discriminant Analysis

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