Ayhan ATEŞOĞLU

Remote sensing and GIS applications for suitable afforestation area selection in Turkey

Bu çalışmanın amacı, uzaktan algılama verileri yardımıyla coğrafi bilgi sistemlerini kullanarak potansiyelağaçlandırma alanlarını tespit etmektir. Çalışmada, topografik, bitki ve arazi kullanım durumları farklı olan Arıt veEşme -Güre orman işletme şefliği sınırları seçilmiştir. Her iki alana ait Landsat TM uydu görüntü verilerine kontrollüsınıflandırma metodu maksimum benzerlik algoritması uygulanmıştır. Öncelikle potansiyel olan ağaçlandırmaalanlarına ilişkin kriterler belirlenerek uzaktan algılama yazılı ile kontrollü sınıflandırma metodu için bu alanlardankontrol alanları seçilmiştir. Kontrollü sınıflandırmaya ilişkin her iki alan için doğruluk değerlendirmeleri yapılmıştır.2032 ha toplam alanı bulunan Arıt Orman İşletme Şefliğine ilişkin genel doğruluk %81, 38447 ha EşmeGüreOrman İşletme Şefliğine ilişkin genel doğruluk % 89 oranında gerçekleşmiştir. Bu çalışma uzaktan algılamasınıflandırma yöntemleriyle potansiyel ağaçlandırma alanlarının tespit edilebilirliğini ispatlamıştır.

Türkiye'de uygun ağaçlandırma alanlarının belirlenmesinde uzaktan algılama ve CBS uygulamaları

The aim of the study, the potential afforestation areas locate using remote sensing data and geographicinformation system. In this study, Arit and Esme -Gure forest district areas that have different site conditions,vegetation and topographic conditions was chosen. Landsat TM image was used do pixel based supervisedclassification and maximum likelihood classification strategy were applied. At first, the criteria that will be potentialafforestation area were determined, then the training areas selected on the remote sensing images using on maps tothe best classification of potential afforestation areas. Accuracy assessment was evaluated of supervised classificationand the result images genera ted vector. The study revealed that 2032 ha is total potential afforestation forest area forArit Forest district (overall accuracy; 81%) and 38447 ha is total potential afforestation forest area for Esme- GureForest district (overall accuracy; 89%). The study has demonstrated a method that can be used due to the fact thathigher accuracy.

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