Analysis of Land Cover Changes after the Water Retention of Yusufeli Dam by Google Earth Engine

Yıl 2025, Cilt: 6 Sayı: 2, 213 - 229, 27.09.2025

Ekrem Saralıoğlu , Baker Alahmed

https://doi.org/10.48123/rsgis.1660237

Öz

This study aims to investigate the land cover changes in Yusufeli district of Artvin province, which is one of the richest regions in terms of biodiversity in Turkey and also contains Turkey's only biosphere reserve area, after the completion of the Yusufeli Dam and the start of water retention. The research was carried out using remote sensing techniques and Google Earth Engine (GEE) platform. GEE is a powerful tool for processing and analyzing large-scale satellite imagery and was used in this study to quickly and effectively detect land cover changes. Within the scope of the study, Sentinel-2 images of 2020 and 2024 with maximum 1% cloudiness were used. In the study, change analysis with Normalized Difference Water Index (NDWI), classification of both images with Support Vector Machines (SVM), and analysis studies on land use classes were carried out. Classification of Sentinel-2 images of 2020 and 2024 with SVM was performed with an overall accuracy of 93.74% and 92.36%, respectively. As a result of the change analyses, it was determined that the surface area of the Çoruh River increased by 2632.11 ha between 2020 and 2024, and the largest inundated areas were forest land, rocky and stony areas and settlement areas.

Anahtar Kelimeler

Remote sensing , Change detection , Google Earth Engine , Yusufeli

Yusufeli Barajı Su Tutma Sonrası Arazi Örtüsü Değişimlerinin Google Earth Engine ile Analizi

Öz

Bu çalışma, Türkiye’nin en yüksek barajı olan Yusufeli Barajı’nın tamamlanması ve su tutulmaya başlanması sonrasında meydana gelen arazi örtüsü değişimlerini incelemeyi amaçlamaktadır. Araştırma, uzaktan algılama teknikleri ve Google Earth Engine (GEE) platformu kullanılarak gerçekleştirmiştir. GEE, büyük ölçekli uydu görüntülerinin işlenmesi ve analiz edilmesi için güçlü bir araç olup, bu çalışmada arazi örtüsü değişimlerini hızlı ve etkili bir şekilde tespit etmek için kullanılmıştır. Çalışma kapsamında, en fazla %1 bulutluluğa sahip 2020 ve 2024 yılına ait Sentinel-2 görüntüleri kullanılmıştır. Çalışmada Normalize Edilmiş Fark Su İndeksi (Normalized Difference Water Index (NDWI)) ile değişim analizi, her iki görüntünün Destek Vektör Makineleri (DVM) ile sınıflandırılması, arazi kullanım sınıfları üzerinden analiz çalışmaları gerçekleştirilmiştir. 2020 ve 2024 yıllarına ait Sentinel-2 görüntülerinin DVM ile sınıflandırılması sırasıyla %93.74 ve %92.36 genel doğruluk ile gerçekleştirilmiştir. Yapılan değişim analizleri sonucunda 2020-2024 yılları arasında Çoruh Nehri’nin yüzey alanında 2632.11 ha’lık artış ve su altında kalan en büyük alanları orman toprağı, kayalık ve taşlık alanlar ile iskân alanlarının oluşturduğu tespit edilmiştir.

Anahtar Kelimeler

Uzaktan algılama , Değişim analizi , Google Earth Engine , Yusufeli

Kaynakça

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