LATE-AND POST-ALPINE TECTONIC EVOLUTION OF THE SOUTHERN PART OF THE ATHOS PENINSULA, NORTHERN GREECE

To όριο μεταξύ των εσωτερικών Ελληνίδων και της Ελληνικής ενδοχώρας αποκαλύπτεται στο νότιο τμήμα της χερσονήσου του Άθω ως μια επαφή ΒΑ-ΝΔ παράταξης μεταξύ της Σέρβο μακεδόνικης μάζας και της Περιροδοπικής Ζώνης. Μελετήθηκαν τα κύρια τεκτονικά χαρακτηριστικά και η παραμόρφωση της περιοχής κατά τη διάρκεια της τελική αλπικής ορογένεσης όσο και μετά από αυτήν με σκοπό την καλύτερη κατανόηση των τελικών ορογενετικών διεργασιών που οδήγησαν στην σημερινή διαμόρφωση αυτού του ορίου. Η υπαίθρια έρευνα έδειξε ότι οι κυρίαρχες δομές στο νότιο τμήμα της χερσονήσου του Αθω είναι ένα ασύμμετρο, βυθιζόμενο προς τα ΝΑ, με φορά προς τα ΒΑ μέγα-αντίμορφο και μια ΒΑ-ΝΔ διεύθυνσης αριστερόστροφη διατρητική ζώνη. Αυτές οι δομές είναι αποτέλεσμα μιας transpressional παραμόρφωσης που άρχισε τουλάχιστον από το Ηώκαινο σε πλαστικές, συμμεταμορφικές (χαμηλή πρασινοσχιστολιθική φάση) συνθήκες και σταδιακά άλλαξε κατά το Ολιγόκαινο - Κάτω Μειόκαινο σε θραυσιγενείς συνθήκες με Α-Δ διεύθυνσης ανάστροφα ρήγματα-επωθήσεις και ΒΒΑ-ΝΝΑ διεύθυνσης δεξιόστροφα και ΒΑ-ΝΑ διεύθυνσης αριστερόστροφα ρήγματα οριζόντιας μετατόπισης. Αυτή η παραμόρφωση σβήνει κατά το Μέσο Μειόκαινο και αλλάζει σε transtension με Α-Δ διεύθυνσης αριστερόστροφα ρήγματα οριζόντιας μετατόπισης και ΒΑ-ΝΑ δεξιόστροφα πλάγια έως κανονικά ρήγματα. Από το Ανω Μειόκαινο ένα εφελκυστικό καθεστώς κυριαρχεί στην περιοχή με τον ελάχιστο κύριο άξονα τάσης (σ3) σε ΒΑ-ΝΔ διεύθυνση κατά το Άνω Μειόκαινο - Πλειόκαινο και σε Β-Ν διεύθυνση από το Κάτω Πλειστόκαινο — σήμερα.The boundary between Internal Hellenides and the Hellenic hinterland is exposed in the southern part of the Athos peninsula as a NE-SW trending contact between the Serbomacedonian massif and the Circum-Rhodope Belt. The main tectonic features and deformation of the area during late- and post-alpine times have been investigated in order to understand better the late orogenic processes that led to the present arrangement of this boundary. The field study showed that the prevailing structures in the southern Athos peninsula are an asymmetric, SW-plunging, NWverging mega-scale antiform and a NE-SW striking left-lateral shear zone. These structures are the result of a transpressional deformation that initiated at least since the Eocene under ductile, syn-metamorphic (low-greenschist fades) conditions and progressively changed during the Oligocene-Early Miocene to brittle conditions with E-W striking reverse faults-thrusts and NNW-SSE striking right-lateral and NESW striking left-lateral strike-slip faults. This deformation waned in Middle Miocene changing to transtension with E- W striking, left-lateral strike-slip and NW-SE rightlateral oblique to normal faults. Since the Late Miocene an extensional regime dominates the area with the least principal stress axis (σ3) orientated NE-SW during Late Miocene - Pliocene andN-Sfrom Early Pleistocene -presen

FAULTING DEFORMATION OF THE MESOHELLENIC TROUGH IN THE KASTORIA-NESTORION REGION (WESTERN MACEDONIA, GREECE)

The Kastoria-Nestorion region, which belongs to the Tertiary MesoHellenic Trough (MHT), is a low relief NW-SE trending intermountainous basin filled with Tertiary molasse-type sedimentary rocks and nowadays drained by the Aliakmnonas River and its tributaries. In the present work, the large fault zones in the region and the general fault pattern are defined, mapped and described with the aid of satellite images. In addition, a large number of fault-slip data from the mesoscale exposed faults has been recorded, in order to better understand the faulting geometry and kinematics of the region. The stress-inversion analysis of these fault-slip data in comparison with earthquake faultplane solution information permits us to define the stress regimes imposed to the region from the Late Tertiary up to the present and to correlate them with the late orogenic and post-orogenic deformation of the Hellenic orogen. In particular, five stress regimes have been defined from which the former two (D1 and D2) are related to the late collisional processes between the Apulia and Eurasia plates, the next two events (D3 and D4) are related to the present-day Hellenic subduction zone, whereas the last D5 event which is the active deformation of the region appears as an intra-continental or intra-plate deformation more related with the Adria-Eurasia ongoing convergence rather with the Hellenic subduction zone

Farm Area Segmentation in Satellite Images Using DeepLabv3+ Neural Networks

Farm detection using low resolution satellite images is an important part of digital agriculture applications such as crop yield monitoring. However, it has not received enough attention compared to high-resolution images. Although high resolution images are more efficient for detection of land cover components, the analysis of low-resolution images are yet important due to the low-resolution repositories of the past satellite images used for timeseries analysis, free availability and economic concerns. In this paper, semantic segmentation of farm areas is addressed using low resolution satellite images. The segmentation is performed in two stages; First, local patches or Regions of Interest (ROI) that include farm areas are detected. Next, deep semantic segmentation strategies are employed to detect the farm pixels. For patch classification, two previously developed local patch classification strategies are employed; a two-step semi-supervised methodology using hand-crafted features and Support Vector Machine (SVM) modelling and transfer learning using the pretrained Convolutional Neural Networks (CNNs). For the latter, the high-level features learnt from the massive filter banks of deep Visual Geometry Group Network (VGG-16) are utilized. After classifying the image patches that contain farm areas, the DeepLabv3+ model is used for semantic segmentation of farm pixels. Four different pretrained networks, resnet18, resnet50, resnet101 and mobilenetv2, are used to transfer their learnt features for the new farm segmentation problem. The first step results show the superiority of the transfer learning compared to hand-crafted features for classification of patches. The second step results show that the model trained based on resnet50 achieved the highest semantic segmentation accuracy.acceptedVersionPeer reviewe