| Yazarlar (2) |
Emre Akturk
|
|
Kerim Guney
|
| Özet |
| This article presents a novel and innovative approach to mapping the forest cover of Türkiye over the last 30 years. The authors have developed a machine learning-based hybrid classification method named 'Combination of the Best Hybrid Classification Method (CBHCM)', which combines three different machine learning image processing techniques to provide a more comprehensive and accurate representation of the country's forest cover changes. The study's results, as evidenced by the high kappa coefficient of 0.806, demonstrate the success and reliability of this new approach. Furthermore, it provides insight into the changes experienced by different phytogeographic regions over the same period. This study highlights the increasing trend of forest cover in all three phytogeographic regions in Türkiye but also raises the question of the structural status of these forests. This research offers a valuable ... |
| Anahtar Kelimeler |
| Makale Türü | Özgün Makale |
| Makale Alt Türü | ESCI dergilerinde yayımlanan tam makale |
| Dergi Adı | International Journal of Image and Data Fusion |
| Dergi Tarandığı Indeksler | |
| Makale Dili | İngilizce |
| Basım Tarihi | 07-2025 |
| Cilt No | 16 |
| Sayı | 1 |
| Doi Numarası | 10.1080/19479832.2025.2473715 |
| Makale Linki | https://doi.org/10.1080/19479832.2025.2473715 |
| Atıf Sayıları |
