| Yazarlar (2) |
Prof. Dr. Fatih SİVRİKAYA
Kastamonu Üniversitesi, Türkiye |
Prof. Dr. Gonca Ece ÖZCAN
Kastamonu Üniversitesi, Türkiye |
| Özet |
| Bark beetles cause significant damage to forests, which are valuable natural resources. The creation of susceptibility maps for bark beetles is a significant stage in the management and reduction of bark beetle-related harm. The present investigation involved the development of a susceptibility map for bark beetles, utilizing the Maximum Entropy (MaxEnt) model, a machine learning technique, and incorporating 19 different bioclimatic climate variables. The model's accuracy was evaluated through receiver operating characteristic (ROC) analysis, and the area under the curve (AUC) was computed to be 0.705. The MaxEnt model indicated that the annual mean temperature (BIO 1) had the greatest impact on the susceptibility of bark beetles. Categorization of bark beetles' susceptibility was delineated into four different categories, namely low, moderate, high, and extreme. Based on the results, approximately 58% of the study area included areas that exhibit vulnerability to bark beetle infestation. The accuracy of the bark beetle susceptibility map, which was developed based on these results, was found to be high and consistent with the observed bark beetle damage. |
| Anahtar Kelimeler |
| Bildiri Türü | Tebliğ/Bildiri |
| Bildiri Alt Türü | Tam Metin Olarak Yayınlanan Tebliğ (Uluslararası Kongre/Sempozyum) |
| Bildiri Niteliği | Alanında Hakemli Uluslararası Kongre/Sempozyum |
| Bildiri Dili | İngilizce |
| Kongre Adı | 6th Intercontinental Geoinformation Days (IGD) |
| Kongre Tarihi | 13-06-2023 / 14-06-2023 |
| Basıldığı Ülke | Azerbaycan |
| Basıldığı Şehir | Bakü |
