AN OBJECT BASED IMAGE ANALYSIS APPROACH FOR THE EXTRACTION OF THE KOLOUMBO VOLCANO AND ASSOCIATED DOMES-CONES FROM A DIGITAL SEABED ELEVATION MODEL

Η παρούσα μελέτη, αφορά στη μελέτη του θαλάσσιου πυθμένα από ψηφιακά μοντέλα αναγλύφου, με την ανάπτυξη μεθοδολογίας αντικειμενοστρεφούς ανάλυσης εικόνας. Έχει ως στόχο την αυτοματοποιημένη εξαγωγή γεωμορφολογικών χαρακτηριστικών πυθμένα, στον οποίο εντοπίζεται έντονη ηφαιστειακή δραστηριότητα. Η περιοχή μελέτης βρίσκεται στη λεκάνη της Ανύδρου, όπου δεσπόζει το υποθαλάσσιο ηφαίστειο του Κολούμπο, καθώς και μικρότεροι υποθαλάσσιοι ηφαιστειακοί κώνοι, 7 χλμ βορειοανατολικά της Σαντορίνης. Για το σκοπό αυτό, έγινε χρήση ψηφιακού μοντέλου αναγλύφου πυθμένα χωρικής ανάλυσης 50m και των παραγώγων αυτού: Slope, Topographic Position Index (TPI) και Terrain Ruggedness Index (TRI). Δημιουργήθηκαν συνολικά εννέα επίπεδα κατάτμησης και ταξινόμησης με στόχο την παραγωγή του τελικού επιπέδου κατάτμησης “level 5”, στο οποίο και ταξινομήθηκαν οι τελικές κατηγορίες γεωμορφολογικών χαρακτηριστικών. Τα αποτελέσματα της μεθόδου αξιολογήθηκαν με τη χρήση 1617 αλγορίθμων που αφορούν την ευστάθεια της ταξινόμησης, αλλά και με ποιοτική και ποσοτική σύγκριση των αποτελεσμάτων με υπάρχων χαρτογραφικό υλικό.This paper concerns the study of the seafloor through digital seabed elevation models, using object based image analysis methods. The goal of this research was the automated extraction of geomorphological features from the seabed in regions presenting intense volcanic activity. The study area is located around the submarine volcano of the Kolοumbo (in the submarine area northeast of the Santorini island, Greece). For this purpose, a Digital Elevation Model (DEM) of the seabed with a spatial resolution of 50m was used. Derivatives of the DEM, such us Slope, Topographic Position Index (TPI) and Terrain Ruggedness Index (TRI) were created in the open source software "QGIS 2.4". The implementation of the object based image analysis approach was performed in eCognition 8.7 software. Nine segmentation and classification levels were created in order to produce the final level segmentation "level 5", where the final geomorphological features were classified. The results of the method were evaluated using classification stability measures and qualitative and quantitative comparison of the results with existing map

DIGITAL EARTH OBSERVATION INFRASTRUCTURES AND INITIATIVES: A REVIEW FRAMEWORK BASED ON OPEN PRINCIPLES

Recent years have seen a tremendous increase of digital Earth Observation (EO) infrastructures, which provide web-based environments for accessing and processing data in a highly automated and scalable way. However, the current landscape of EO infrastructures and initiatives is fragmented, with various levels of user on-boarding and uptake success. The current work aims to make sense of this complex landscape by providing two main contributions. First, it offers a classification scheme used to review and analyse more than 150 EO infrastructures and initiatives. Then, adopting a user-centric perspective, the main limitations and obstacles currently faced by users when working with the existing EO platforms are identified. For each of these limitations, we propose a number of good practices that could benefit, from a user point of view, the design and functioning of EO platforms. Some technological enablers, i.e. specific resources (such as software components, standards and data encodings) that emerged from the analysis as holding a great potential for improving the usability of existing EO platforms, are finally listed. The work aims to provide a first scientific insight on how to best design and operate EO platforms to maximise the benefits of their user communities