Comparative Performance of dNBR and dNDVI for Burn Severity Mapping via Large Wildfires of 2021 in Türkiye
Yazarlar (4)
ALKAN GUNLU
Prof. Dr. Fatih SİVRİKAYA Kastamonu Üniversitesi, Türkiye
okan urker
Christopher Dunn Kastamonu Üniversitesi
| Makale Türü | Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | International Journal of Wildland Fire (Q1) | ||
| Makale Dili | – | Basım Tarihi | 05-2026 |
| Cilt / Sayı / Sayfa | 35 / 7 / – | DOI | 10.1071/WF25096/272866 |
| Makale Linki | https://connectsci.au/wf/article-abstract/doi/10.1071/WF25096/272866 | ||
| UAK Araştırma Alanları |
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| Özet |
| Background The large wildfires that occurred in 2021 in the southwestern coastlines of Türkiye, characterized by typical Mediterranean ecosystems, caused significant damage to forests and shrublands. These fires adversely affect forest ecosystems, causing negative impacts on biological diversity, global carbon balance, and climate change. Therefore, accurate and reliable burn severity maps are needed, especially for post-fire management, to assess the severity of the wildfires properly. Purpose In this context, studies on burn severity classes using remote sensing data have been increasingly conducted in recent years. Methods In this study, maps related to burn severity classes were produced using differenced normalized burn ratio (dNBR) and differenced normalized difference vegetation index (dNDVI) derived from Landsat 8 and Sentinel-2 satellite images for the mega wildfires that happened in Marmaris … |
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BM Sürdürülebilir Kalkınma Amaçları
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| Google Scholar | 1 |