Earthquakes occur all around the world, causing varying degrees of damage and destruction. Earthquakes are by their very nature a sudden phenomenon and predicting them with a precise time range is difficult. Some phenomena may be indicators of physical conditions favorable for large earthquakes (e.g., the ionospheric Total Electron Content (TEC)). The TEC is an important parameter used to detect pre-earthquake changes by measuring ionospheric disturbances and space weather indices, such as the global geomagnetic index (Kp), the storm duration distribution (Dst), the sunspot number (R), the geomagnetic storm index (Ap-index), the solar wind speed (Vsw), and the solar activity index (F10.7), have also been used to detect pre-earthquake ionospheric changes. In this study, the feasibility of the 6th-day earthquake prediction by the deep neural network technique using the previous five consecutive days is investigated. For this purpose, a two-staged approach is developed. In the first stage, various preprocessing steps, namely TEC signal improvement and time-frequency representation-based TEC image construction, are performed. In the second stage, a multi-input convolutional neural network (CNN) model is designed and trained in an end-to-end fashion. This multi-input CNN model has a total of six inputs, and five of the inputs are designed as 2D and the sixth is a 1D vector. The 2D inputs to the multi-input CNN model are TEC images and the vector input is concatenated space weather indices. The network branches with the 2D inputs contain convolution, batch normalization, and Rectified Linear Unit (ReLU) activation layers, and the branch with the 1D input contains a ReLU activation layer. The ReLU activation outputs of all the branches are flattened and then concatenated. And the classification is performed via fully connected, softmax, and classification layers, respectively. In the experimental work, earthquakes with a magnitude of M_w5.0 and above that occurred in Turkey between 2012 and 2019 are used as the dataset. The TEC data were recorded by the Turkey National Permanent GNSS Network-Active (TNPGN-Active) Global Navigation Satellite System (GNSS) stations. The TEC data five days before the earthquake were marked as “precursor days” and the TEC data five days after the earthquake were marked as “normal days”. In total, 75% of the dataset is used to train the proposed method and 25% of the dataset is used for testing. The classification accuracy, sensitivity, specificity, and F1-score values are obtained for performance evaluations. The results are promising, and an 89.31% classification accuracy is obtained.

En tr The lineaments in the area between Palu (Elazığ)-Pütürge (Malatya) on the East Anatolian Fault System (EAFS) were extracted by using automatic methods from Landsat (4-5) TM satellite image. Artificial and/or natural lineaments, which were not formed by the help of geological effects, were eliminated. Within the study area, a total of 101 geological lineaments were defined and rose diagram prepared. According to the rose diagram, the main orientations of the faults were determined as N75⁰E with total of 1.286,879 km long. A rose diagram is interpreted taking into account the tectonic evolution of the region. In this regard, two main geological lineaments directions of N55⁰E and N85⁰E were determined in the study area. In this data, N85⁰E directed lineaments, which correspond to the fold axes or reverse faults, are related to the approximately N-S directed compression during the Middle Miocene-Pliocene period. The EAFS, as well as many strike-slip faults, started to activate, and the strike-slip tectonic regime has been dominant since the Late Pliocene. Due to the fact that N55⁰E oriented lineaments both are approximately parallel to EAFS and confirm by field work suggest that N55⁰E oriented faults are related to strike-slip tectonic regime. Geological lineament analysis results obtained by automated methods on satellite images are very consistent with current tectonic regime controlling the region. Doğu Anadolu Fay Sistemi’nin (DAFS) Palu (Elazığ)–Pütürge (Malatya) arasındaki bölümünün çizgisellikleri Landsat (4-5) TM uydu görüntüleri üzerinden otomatik yöntemle çıkarılmıştır. Bu çizgisel yapılardan; jeolojik unsurların dışındaki etkilerle oluşmuş yapay ve/veya doğal çizgisellikler elemine edilmiştir. Çalışma alanı içerisinde 101 adet jeolojik çizgisellik belirlenerek gül diyagramı hazırlanmıştır. Çizgisellik analizlerine göre jeolojik çizgiselliklerin toplam uzunlukları 1.287 km ve ortalama doğrultularının ise 75⁰ olduğu tespit edilmiştir. Gül diyagramından elde edilen sonuçlar bölgenin tektonik evrimi göz önünde bulundurularak yorumlanmıştır. Bu veriler ışığında çalışma alanında K55⁰D ve K85⁰D yönlü iki ana jeolojik çizgisellik doğrultusu belirlenmiştir. Bu çizgiselliklerden K85⁰D yönlü olanların Orta Miyosen-Erken Pliyosen döneminde bölgede etkili olan yaklaşık kuzey-güney sıkışma ile ilgili oldukları ve kıvrım eksenlerine veya ters faylara karşılık geldikleri arazi verileri ile desteklenmektedir. Geç Pliyosen döneminden itibaren bölgede DAFS başta olmak üzere birçok doğrultu atımlı fay aktif hale geçerek doğrultu atım tektoniği baskın duruma geçmiştir. K55⁰D yönlü olan çizgiselliklerin sol yanal doğrultu atımlı fayları temsil ettiği arazi verilerince doğrulanmıştır. Uydu görüntüleri üzerinden otomatik yöntemle elde edilen jeolojik çizgisellik analiz sonuçlarının, bölgenin etkisi altında olduğu tektonik rejim ürünleriyle oldukça uyumlu olduğu gözlenmiştir.