Arşiv logosu
  • Türkçe
  • English
  • Giriş
    Yeni kullanıcı mısınız? Kayıt için tıklayın. Şifrenizi mi unuttunuz?
Arşiv logosu
  • Koleksiyonlar
  • Sistem İçeriği
  • Analiz
  • Talep/Soru
  • Türkçe
  • English
  • Giriş
    Yeni kullanıcı mısınız? Kayıt için tıklayın. Şifrenizi mi unuttunuz?
  1. Ana Sayfa
  2. Yazara Göre Listele

Yazar "Gümüşay, Mustafa Ümit" seçeneğine göre listele

Listeleniyor 1 - 2 / 2
Sayfa Başına Sonuç
Sıralama seçenekleri
  • [ X ]
    Öğe
    An assessment of machine learning methods for seagrass classification in the Mediterranean
    (Univ Latvia, 2020) Bakırman, Tolga; Gümüşay, Mustafa Ümit
    Posidonia oceanica is an endemic seagrass species in the Mediterranean. Even though this species has been put under protection, P. oceanica is currently listed as threatened. Therefore, in order to conserve this species, high resolution, accurate and temporal distribution maps are needed to be produced. In this study, it is aimed to create seagrass distribution maps with machine learning algorithms namely as random forests and support vector machines using WorldView-2 imagery. In-situ data has been collected via underwater video and scuba diving for classification training and testing. Atmospheric, radiometric and water column corrections are applied for preprocessing of the optical satellite image. The light penetration in the water is limited by depth. Therefore, we have limited our study area based on maximum depth of 20 meters. The classification accuracies and Cohen's kappa coefficients are calculated as 94% and 0.89 for random forests, 71% and 0.61 for support vector machines, respectively. According to the results, it can be clearly said that random forests method is superior to support vector machines for seagrass mapping in our study area. The proposed framework in this study enables to rapidly produce seagrass distribution maps which can be used to monitor temporal change for a sustainable ecosystem.
  • Yükleniyor...
    Küçük Resim
    Öğe
    Performance of hydraulic structures, lifelines and industrial structures during October 30, 2020 Samos-Aegean sea earthquake
    (2022) Toprak, Selçuk; Uçkan, M. Eren; Yılmaz, M. Tolga; Cüceoğlu, Faik; Gümüşay, Mustafa Ümit; Nacaroğlu, Engin; Kaya, Ercan S.; Aksel, Murat
    This paper presents the effects of October 30, 2020 Samos-Aegean Sea earthquake on hydraulic structures, lifelines and industrial facilities which mainly located in the western cost of Turkey, within the borders of Izmir and Aydin Cities. These two highly populated cities are known for their importance in contributing country's economics by their industrialized areas. In addition, Izmir is the third largest city of Turkey with its high seismic hazard zone. Although some disruptions in the aftermath of the earthquake were occurred in gas and electricity services, these issues immediately identified, and all systems were managed to reoperate. Damages to the infrastructures were mainly due to the collapse of buildings and tsunami effects. No significant damages were reported on lifeline systems, large industrial facilities, and dams due to relatively low shaking intensity.

| Alanya Alaaddin Keykubat Üniversitesi | Kütüphane | Açık Bilim Politikası | Açık Erişim Politikası | Rehber | OAI-PMH |

Bu site Creative Commons Alıntı-Gayri Ticari-Türetilemez 4.0 Uluslararası Lisansı ile korunmaktadır.


Alanya Alaaddin Keykubat Üniversitesi, Alanya, Antalya, TÜRKİYE
İçerikte herhangi bir hata görürseniz lütfen bize bildirin

Powered by İdeal DSpace

DSpace yazılımı telif hakkı © 2002-2026 LYRASIS

  • Çerez Ayarları
  • Gizlilik Politikası
  • Son Kullanıcı Sözleşmesi
  • Geri Bildirim