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Askıda sediman konsantrasyonunun belirlenmesinde geleneksel yaklaşımlar, makine öğrenmesi ve yeni eğilimler

Gültekin Erten(Maden Tetkik ve Arama Genel Müdürlüğü, Jeoloji Etütleri Dairesi Başkanlığı, Uzaktan Algılama ve CBS Koordinatörlüğü, Ankara, Türkiye)0000-0002-3844-8666
Aytekin Erten(Niğde Ömer Halisdemir Üniversitesi, Fen Bilimleri Enstitüsü Jeoloji Mühendisliği Anabilim Dalı, Niğde, Türkiye)0000-0002-4435-8165
Pages
41–61
Publication Date
2025-12-15
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Bu çalışma, gelecekte askıda sediman konsantrasyonu araştırmalarında uydu zaman serilerinin, ileri makine öğrenmesi algoritmalarının ve çok ölçekli çevresel değişkenlerin birlikte kullanılmasının yeni fırsatlar sunduğunu vurgulamaktadır.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Askıda sediman konsantrasyonu; akarsu, delta ve kıyı ortamlarında su kalitesi, taşınım süreçleri ve morfodinamik değişimlerin anlaşılması açısından kritik bir göstergedir.
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Key Findings & Data:Son 40 yılda uzaktan algılama teknikleri, saha gözlemleri ve makine öğrenmesi yöntemlerinin gelişmesiyle birlikte askıda sediman konsantrasyonu tahmini ve izlenmesine yönelik çok sayıda yöntem önerilmiştir.
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Conclusion & Impact:Bu çalışma, gelecekte askıda sediman konsantrasyonu araştırmalarında uydu zaman serilerinin, ileri makine öğrenmesi algoritmalarının ve çok ölçekli çevresel değişkenlerin birlikte kullanılmasının yeni fırsatlar sunduğunu vurgulamaktadır.
🔬Design:Survey & Empirical Study
📍Scope:Comprehensive Sample
⚙️Variables:Askıda sediman konsantrasyonu · Uzaktan algılama · Makine öğrenmesi

Özet

Askıda sediman konsantrasyonu; akarsu, delta ve kıyı ortamlarında su kalitesi, taşınım süreçleri ve morfodinamik değişimlerin anlaşılması açısından kritik bir göstergedir. Son 40 yılda uzaktan algılama teknikleri, saha gözlemleri ve makine öğrenmesi yöntemlerinin gelişmesiyle birlikte askıda sediman konsantrasyonu tahmini ve izlenmesine yönelik çok sayıda yöntem önerilmiştir. Bu makale, dünya üzerinde farklı bölgelerde gerçekleştirilen çalışmaları inceleyerek askıda sediman konsantrasyonu araştırmalarındaki gelişmeleri özetlemektedir. Ele alınan literatür, üç ana eksende gruplandırılmıştır: (i) optik uydu verilerinden türetilen bant oranları ve indekslere dayalı geleneksel yaklaşımlar, (ii) yapay zekâ ve hibrit modeller gibi veri odaklı yöntemler ve (iii) bölgesel uygulamalar üzerinden sediman taşınımının iklim ve insan etkileriyle ilişkileri. Karşılaştırmalar, geleneksel bant oranı modellerinin özellikle küçük ve kapalı havzalarda halen etkin olduğunu, ancak geniş ölçekli izlemelerde makine öğrenmesi ve uydu tabanlı entegrasyonların doğruluğu belirgin şekilde artırdığını göstermektedir. Mevcut literatürdeki boşluklar arasında uzun dönemli analizlerin sınırlı olması, topoğrafik ve iklimsel değişkenlerin çoğu modelde yetersiz temsil edilmesi ve kıyı-delta sistemlerinde Askıda sediman konsantrasyonunun doğrudan etkilerinin az incelenmiş olması öne çıkmaktadır. Bu çalışma, gelecekte askıda sediman konsantrasyonu araştırmalarında uydu zaman serilerinin, ileri makine öğrenmesi algoritmalarının ve çok ölçekli çevresel değişkenlerin birlikte kullanılmasının yeni fırsatlar sunduğunu vurgulamaktadır.

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Cite This Article

Erten, G., Erten, A. (2025). Askıda sediman konsantrasyonunun belirlenmesinde geleneksel yaklaşımlar, makine öğrenmesi ve yeni eğilimler. MTA Yerbilimleri ve Madencilik Dergisi, Cilt: 8 Sayı: 8, 41–61. https://ajindex.com/articles/1619861

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