Snow cover detection using remote sensing techniques over different climate zones of Türkiye
Yazarlar (3)
Prof. Dr. Günay Çakır Gümüşhane Üniversitesi, Türkiye
Doç. Dr. Nuri Bozali Karadeniz Technical University, Türkiye
Prof. Dr. Fatih SİVRİKAYA Kastamonu Üniversitesi, Türkiye
| Makale Türü |
Özgün Makale
(SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale)
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| Dergi Adı | Scientific Reports (Q1) | ||
| Dergi ISSN | 2045-2322 Wos Dergi Scopus Dergi | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | İngilizce | Basım Tarihi | 07-2025 |
| Cilt / Sayı / Sayfa | 15 / 1 / 23993–0 | DOI | 10.1038/s41598-025-07158-4 |
| Makale Linki | https://doi.org/10.1038/s41598-025-07158-4 | ||
| UAK Araştırma Alanları |
Orman Hasılatı ve Amenajmanı
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| Özet |
| Snow-covered land surfaces can be easily mapped using remote sensing technologies. Accurate estimation of snow cover on the land surface allows for the construction of water resource management today. Using Landsat TM/ETM + satellite images, this study tried to assess how much snowfall covered the soil in Trabzon, Gümüşhane, and Bayburt provinces between 1999 and 2023. Satellite images were classified into three categories using the ERDAS 9.1 TM software. These classes are classified as snow-covered surfaces, other places, and data loss (cloud-shadow). When performing image analysis, it was important to verify that the cloudiness rate in the images was less than 15%. Images with cloudiness rates of more than 15% were not used. Seasonal and annual trend analysis of snow-covered areas (SCA) over three distinct regions (Trabzon, Gümüşhane, and Bayburt) were examined using the Mann … |
| Anahtar Kelimeler |
| Climate | GIS | Landsat images | Remote sensing | Snowy area |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Web of Science | 1 |
| Scopus | 2 |
| Google Scholar | 3 |