Journals / DSİ Teknik Bülteni / 2018 / Sayı: 127

SATELLITE-DERIVED BATHYMETRY USING MULTI-TEMPORAL SATELLITE IMAGES

ÇOK ZAMANLI UYDU GÖRÜNTÜLERİ KULLANILARAK UYDU-KAYNAKLI BATİMETRİ

Pages
14–27
DOI
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AI Summary & Key Takeaways

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

The generated maps can be used directly when the accuracy is found to be sufficient; Also, it is suggested to use batimetric map acquisition for exploratory studies when more precise studies are required.

📌 3 Key Takeaways

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Objective & Hypothesis:The change in the amount of water in dams and lakes can be determined by bathymetric maps made with certain periods.
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Key Findings & Data:In this study, it was tried to determine the bathymetric elevations of the Seyhan Dam Lake due to the water depth by using Log Ratio Transformation (LRT) method as described by Stumpf et al [2003].
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Conclusion & Impact:The generated maps can be used directly when the accuracy is found to be sufficient; Also, it is suggested to use batimetric map acquisition for exploratory studies when more precise studies are required.
🔬Design:Research Article
📍Scope:2003 Verileri
⚙️Variables:Domain Parameters

Abstract

The change in the amount of water in dams and lakes can be determined by bathymetric maps made with certain periods. Bathymetric maps constructed with classical methods such as lead-line and technological methods such as echo-sounder are now also made with remote sensing methods. In this study, it was tried to determine the bathymetric elevations of the Seyhan Dam Lake due to the water depth by using Log Ratio Transformation (LRT) method as described by Stumpf et al [2003]. This method was developed by the US National Oceanic and Atmospheric Administration (NOAA) and is considered to be the most effective method of analysis of water depth. For the calibration of the depth of water, 17 points were used. The depths of these points were selected from the bathymetric map of the Seyhan Dam Lake in 2005, with a depth difference of 2 m between the points. As remote sensing data, 8 images were selected and analyzed considering the cloudiness in Landsat 8 satellite. As a result of the analyzes, the regression value R2 , between the average bathymetric levels and the actual bathymetric levels was 0,9359 and Root Mean Square Error (RMSE) was 2,78 m. The generated maps can be used directly when the accuracy is found to be sufficient; Also, it is suggested to use batimetric map acquisition for exploratory studies when more precise studies are required.

Özet

Barajlar ve göllerdeki su miktarındaki değişim belirli periyotlarla yapılan batimetrik haritalar ile tespit edilebilmektedir. İp iskandil gibi klasik yöntemlerle ve echo-sounder gibi teknolojik yöntemlerle yapılan batimetrik haritalar günümüzde uzaktan algılama yöntemleri ile de yapılmaktadır. Bu çalışmada, Stumpf vd. [2003] tarafından açıklandığı şekilde Log Ratio Transformation (LRT) yöntemi kullanılarak Seyhan Baraj Gölünün su derinliğinin ve dolayısı ile batimetrik kotların tespit edilmesine çalışılmıştır. Bu yöntem ABD Ulusal Okyanus ve Atmosfer İdaresi (NOAA) tarafından geliştirilmiş olup su derinliğinin hesaplanmasında en etkili analiz yöntemi olarak görülmektedir. Su derinliğinin kalibrasyonu için 17 adet nokta kullanılmıştır. Bu noktaların derinlikleri 2005 yılında yapılmış Seyhan Baraj Gölü batimetrik haritasından noktalar arası 2 m derinlik farkı olacak şekilde seçilmiştir. Uzaktan algılama verisi olarak Landsat 8 uydusuna ait 2017 yılı içerisinde bulutsuzluk durumu dikkate alınarak 8 adet görüntü seçilmiş ve analiz edilmiştir. Analizler sonucunda ortalama batimetrik kotlar ile gerçek batimetrik kotlar arasındaki regresyonun R2’si 0,9359 ve Karesel Ortalama Hatası (KOH) ise 2,78 m olarak bulunmuştur. Bulunan hassasiyetin yeterli görüleceği çalışmalarda üretilen haritalar doğrudan kullanılabileceği gibi daha hassasiyet istenen çalışmalarda batimetrik harita alımının istikşaf çalışmalarında kullanılması önerilmektedir.

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Cite This Article

AKGÜL, M. A., DAĞDEVİREN, M., BİROĞLU, İ. (2018). SATELLITE-DERIVED BATHYMETRY USING MULTI-TEMPORAL SATELLITE IMAGES. DSİ Teknik Bülteni, Sayı: 127, 14–27. https://ajindex.com/articles/150608

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