An exhumation model of the south Peloponnesus, Greece

An exhumation model comprising forward and backward thrusting and late orogenic collapse is proposed in order to explain the kinematics of the tectonic windows in the south Peloponnesus. The model is based on mapping, mesoscopic structural data and strain analysis. Syn-compressional thickening took place throughout the Oligocene and Early Miocene which includes the subduction of the Pindos Ocean at the western margin of the Pelagonian microcontinent and the intracontinental subduction of the Phyllite–Quartzite and the Plattenkalk series. The latter subduction was associated with blueschist metamorphism, westward-directed ductile thrusting, and folding. The exhumation history of the deeper parts of the orogen began at the Oligocene–Miocene boundary with the progressive entrance of the low-density crust and the Plattenkalk carbonates in the subduction zone. Increased buoyancy caused: (a) the initiation of the Phyllite–Quartzite series extrusion; (b) vertical coaxial stretching; and (c) the evolution of two pop-up structures, i.e. the Parnon and Taygetos anticlines. This syn-compressional exhumation was taking place in the lower Miocene with decreasing rates from 7 to 1.5 mm/year. The change in the local stress field from compression to extension began in the middle Miocene with the formation of hinterland-dipping normal faults. The exhumation/denudation rate caused by the footwall uplift along these faults does not exceed 0.2 mm/year. Received: 16 April 1999 / Accepted: 19 January 2000     

Ray and finite-difference modelling of CDP seismic sections for shallow lignite deposits

A numerical experiment carried out to investigate the structural model of the Domenico lignite site is discussed. The model is a 2D structure containing several lignite layers at different depths, and a low-velocity layer at the top of the model. The experiment consists in simulating a measured CDP section by two independent techniques, based on completely different concepts: the finite-difference method and the ray method. Due to the incompleteness of the ray synthetic wave field, as well as to numerical problems of the finite differences at higher frequencies, the agreement between the synthetic seismogram sections for the individual shot points is poor. However, the CDP stacked sections modelled by the ray and finite-difference methods agree rather well. This is because the main differences between the wave fields computed by the two methods are due to the presence of the low-velocity layer (ground roll, head waves, etc.), and just these parts of the wave field can be suppressed by routine data processing such as f–k filtration. Synthetic ray and finite-difference CDP stacks agree relatively well with the observed data. They confirm three lignite seams and a fault in the shallower one. The synthetic data also indicate that many apparent horizons of the measured section may be due to the multiple reflections within the subsurface low-velocity layer.     

Using the SyNaRMa system as a disaster management tool

Natural disasters have a considerable effect in human, infrastructure and economy. In the case of a, e.g., catastrophic earthquake that happens and affects the urban environment, immediate and efficient actions are required that ensure the minimization of the damage and loss of human lives. Local and national authorities should respond in order to meet the above objective. Nowadays, one of the most appropriate tools for this purpose is the web-based geographic information systems (GIS). Such a system, named SyNaRMa (Information System for Natural Risk Management in the Mediterranean), has been developed in the frame of an INTERREG IIIB ArchiMED project (2006?C2008). The present paper aims at addressing the role of the SyNaRMa system as a tool for facilitating disaster management. It is argued that the development of a web-based GIS can assist disaster management agencies to improve the quality of their decision making and increase efficiency and effectiveness in all levels of disaster management activities. This research is primarily based on the findings of the abovementioned project that resulted in the development of an information system for natural risk management in the Mediterranean that can facilitate sharing, access and usage of spatial data in disaster management, i.e., preparedness, response and recovery activities.     

Scaling properties within the Gulf of Corinth, Greece; comparison between offshore and onshore active faults

The Gulf of Corinth, Greece, is a 110-km-long by 30-km-wide active graben displaying strong seismicity hosted both on north and south dipping normal faults. This complex fault pattern consists of two fault populations, offshore and onshore. The offshore fault population is investigated by densely arranged seismic reflection profiles during the last 20 years, whereas the onshore fault population displays spectacular and well exposed faults, delineated by high accuracy mapping. We analyzed fault length and throw, in order to study the scaling properties of 136 well-determined offshore and onshore faults and the comparison between the two datasets. We examined the statistical properties on both fault populations, in order to describe the role of segmentation in the growth of faults and the different stages of the evolution of the fault networks.Our results on power law relationships associated with the scaling properties of the fault zones in the Gulf of Corinth, suggest that both fault populations are bi-fractal, providing the initiation of a sature state in deformation. In addition, the vertical throw of faults shows that both fault populations have similar properties but different distributions below and above 5 km, respectively. Displacement–length ratios, show that faults larger than 9 km appear to accumulate throw without any dramatic change to their length. These observations combined with other geophysical studies within the Gulf, suggest that the characteristic fault lengths of 5 km and 9 km can be correlated to the crustal mechanical structure and the seismicity of the Gulf.     

Landslide susceptibility mapping using a modified decision tree classifier in the Xanthi Perfection,Greece

The objective of this study was to validate the outcomes of a modified decision tree classifier by comparing the produced landslide susceptibility map and the actual landslide occurrence, in an area of intensive landslide manifestation, in Xanthi Perfection, Greece. The values that concerned eight landslide conditioning factors for 163 landslides and 163 non-landslide locations were extracted by using advanced spatial GIS functions. Lithological units, elevation, slope angle, slope aspect, distance from tectonic features, distance from hydrographic network, distance from geological boundaries and distance from road network were among the eight landslide conditioning factors that were included in the landslide database used in the training phase. In the present study, landslide and non-landslide locations were randomly divided into two subsets: 80 % of the data (260 instances) were used for training and 20 % of the data (66 instances) for validating the developed classifier. The outcome of the decision tree classifier was a set of rules that expressed the relationship between landslide conditioning factors and the actual landslide occurrence. The landslide susceptibility belief values were obtained by applying a statistical method, the certainty factor method, and by measuring the belief in each rule that the decision tree classifier produced, transforming the discrete type of result into a continuous value that enabled the generation of a landslide susceptibility belief map. In total, four landslide susceptibility maps were produced using the certainty factor method, the Iterative Dichotomizer version 3 algorithm, the J48 algorithm and the modified Iterative Dichotomizer version 3 model in order to evaluate the performance of the developed classifier. The validation results showed that area under the ROC curves for the models varied from 0.7936 to 0.8397 for success rate curve and 0.7766 to 0.8035 for prediction rate curves, respectively. The success rate and prediction curves showed that the modified Iterative Dichotomizer version 3 model had a slightly higher performance with 0.8397 and 0.8035, respectively. From the outcomes of the study, it was induced that the developed modified decision tree classifier could be efficiently used for landslide susceptibility analysis and in general might be used for classification and estimation purposes in spatial predictive models.     

Structural Analysis for Gold Mineralization Using Remote Sensing and Geochemical Techniques in a GIS Environment: Island of Lesvos,Hellas

Exploration for epithermal Au has been active lately in the Aegean Sea of the eastern Mediterranean Basin, both in the islands of the Quaternary arc and in those of the back-arc region. The purpose of this study was the structural mapping and analysis for a preliminary investigation of possible epithermal gold mineralization, using remotely sensed data and techniques, structural and field data, and geochemical information, for a specific area on the Island of Lesvos. Therefore, Landsat-TM and SPOT-Pan satellite images and the Digital Elevation Model (DEM) of the study area were processed digitally using spatial filtering techniques for the enhancement and recognition of the geologically significant lineaments, as well as algebraic operations with band ratios and Principal Component Analysis (PCA), for the identification of alteration zones. Statistical rose diagrams and a SCHMIDT projection Stereo Net were generated from the lineament maps and the collected field data (dip and strike measurements of faults, joints, and veins), respectively. The derived lineament map and the band ratio images were manipulated in a GIS environment, in order to study the relation of the tectonic pattern to both the alteration zoning and the geomorphology of the volcanic field of the study area. Target areas of high interest for possible mineralization also were specified using geochemical techniques, such as X-Ray Diffraction (XRD) analysis, trace-element, and fluid-inclusion analysis. Finally, preliminary conclusions were derived about possible mineralization, the type (high or low sulfidation), and the extent of mineralization, by combining the structural information with geochemical information.     

Applying weight of evidence method and sensitivity analysis to produce a landslide susceptibility map

The main purpose of this study is to define the main variables that contribute to the occurrence of landslides in Kimi, Euboea, Greece, and to produce a landslide susceptibility map using the weight of evidence method. For the developed model, a sensitivity analysis is carried out in order to understand the model’s behavior when small changes are introduced in the weight value of the landslide-related variables. Landslide locations were identified from field surveys and interpretation of aerial photographs which resulted in the construction of an inventory map with 132 landslide events, while eight contributing variables were identified and exploited. All landslide-related variables were converted into a 5?×?5-m float-type raster file. These input-raster layers included a lithological unit layer, an elevation layer, a slope angle layer, a slope aspect layer, a distance from tectonic features layer, a distance from hydrographic network layer, a topographic wetness index layer, and a curvature layer. The validation of the developed model was achieved by using a subset of unprocessed landslide data, showing a satisfactory agreement between the expected and existing landslide susceptibility level, with the area under the predictive rate curve estimated to be 0.808. The area under the success rate curve was estimated to be 0.828 indicating a very high classification rate for existing landslide areas. According to the results of the sensitivity analysis, the lithological unit “yellowish gray to white marls” was the most sensitive as it had the highest change in the relative frequency of observed landslides. The overall outcomes of the performed analysis provide crucial knowledge in successful land use planning and management practice and also in risk reduction projects.