Πλοήγηση ανά Συγγραφέας "Peleli, Sofia"

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  • Μικρογραφία εικόνας
    Τεκμήριο
    Sinkhole formation GIS-based mapping and geo-statistical prediction analysis in Chania area, Crete.
    (ΕΛ.ΜΕ.ΠΑ., ΣΧΟΛΗ ΜΗΧΑΝΙΚΩΝ (ΣΜΗΧ), Τμήμα Ηλεκτρονικών Μηχανικών, 2023-06-16) Πελέλη, Σοφία; Peleli, Sofia
    The last years many researches have been done to evaluate sinkhole formation and to produce sinkhole susceptibility maps using the probability method of frequency ratio for prediction analysis. By determining the vulnerable areas it is possible to decrease the probability of damage caused by sinkholes in urban and agricultural areas. The purpose of this study is at first to create an accurate sinkhole inventory map in the study area and secondly to make a prediction analysis by producing a sinkhole susceptibility index based on the frequency ratio method within a geographic information system environment. For sinkhole formation inventory map, two TanDEM-X DEMs with a spatial resolution of 11.1m and 30m respectively were adapted. Six filters (area, depth, eccentricity, circularity index, proximity to streams & proximity to roads) were applied on initial sinkholes identification of each DEM to exclude falsely-identified depressions. Finally two sinkhole inventory maps were produced with 1038 sinkholes for the 11-meter TanDEM-X and 428 for the 30-meter TanDEM-X, showing that the 11-meter DEM is able to identify more sinkholes due to its better spatial resolution. The inventory map of the 11-meter TanDEM-X DEM was chosen for the prediction analysis. Sinkholes were separated in the training sinkhole dataset (70%) and the test sinkhole dataset (30%) and twelve sinkhole formation controlling factors; geology (lithology), hydrogeology, soils depth, slope, elevation, groundwater exploitation, distance & density to faults, distance &density to deep wells, drainage density and land use were chosen and analyzed for the sinkhole susceptibility index, which was classified in four classes; low, moderate, high & very high susceptibility. The sinkhole susceptibility map shows that 83.3% of the test sinkhole dataset fall within the “high” and “very high” susceptibility zones.
  • Μικρογραφία εικόνας
    Τεκμήριο
    Παρακολούθηση της θερμοκρασίας της επιφάνειας της Γης (LST) του Αιγαιακού ηφαιστειακού τόξου χρησιμοποιώντας τεχνικές τηλεπισκόπησης και MODIS -LST εικόνες.
    (Τ.Ε.Ι. Κρήτης, Σχολή Εφαρμοσμένων Επιστημών (Σ.Εφ.Ε), Τμήμα Μηχανικών Φυσικών Πόρων και Περιβάλλοντος Τ.Ε., 2017-02-22) Πελέλη, Σοφία; Peleli, Sofia
    Γίνεται μελέτη των θερμοκρασιακών ανωμαλιών που παρατηρούνται στο Ανατολικό Αιγαίο με χρήση τηλεπισκόπησης (MODIS -LST και με τη τεχνική του RST) για την παρακολούθηση των γεωθερμικών πεδίων της περιοχής.