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Areas in Western Greece are particularly prone to landslides. Usually triggered by earthquakes or intense rainfalls, they cause damage to infrastructure (roads, bridges, etc.) and human properties. Hence, there is an urgent need for the implementation of monitoring and landslide prevention methodologies. In the last years, Unmanned Aerial Vehicles (UAVs), Global Navigation Satellite Systems (GNSS), and Interferometric SAR (InSAR) techniques have been applied for landslide mapping and monitoring. The current study focuses on the systematic and long-term analysis of a landslide that occurred in Ano Kerassovo village, within the region of Western Greece. To precisely measure the current evolution of the landslide, we performed repetitive UAV campaigns in conjunction with corresponding GNSS surveys, covering a time period between February 2021 and April 2023. The identification of surface modification was based on a change detection approach between the generated point clouds. The results are validated through GNSS measurements and field observations. Added to this, we collected archived Persistent Scatterer Interferometry (PSI) measurements derived from the European Ground Motion Service (EGMS) to extend the observation period and gain a more complete understanding of the phenomenon. It is proven that archived PSI measurements can be used as an indicator of possible landslide initialization points and for small-scale large coverage investigations, while UAVs and GNSS data can precisely identify the microscale deformations (centimeter scale).

As infrastructure faces the consequences of climate change there is an urgent need for monitoring methodologies that can provide accurate and timely information to the stakeholders and decision makers in order to mitigate the risk and ensure the safety. According to the World Meteorological Organization the last decade has been recorded as the warmest period in human history. As a consequence, particularly high temperatures and frequent weather extremes (drought, floods, etc.) jeopardize the infrastructure safety. At the same time, the need for reliable, cost-efficient and globally applied infrastructure monitoring methodologies is even more crucial in areas with high seismicity and or volcanic activity.In this framework the current project, named “PROION”, focuses on the infrastructure monitoring in the “Enceladus” Hellenic supersite. Τhis very active tectonic and seismic area includes geographically:the urban centers of Athens, Corinth and Patras (> 50% of the country's population), some of the most important archaeological monuments (Ancient Olympia and Mycenae) and some very important infrastructures such as Mornos and Evinos dams, Rio-Antirrio Bridge etc. The Enceladus Supersite area presents the highest seismicity in Europe, the highest recorded ground acceleration in Greece(0.77g) and a very high frequency of landslides.The aim of the project is the development of a platform for the continuous monitoring of high importance infrastructures such as public buildings and dams. The methodology combines instrumental and remote sensing measurements along with fuzzy logic networks methods and machine learning algorithms. Specifically, measurements obtained by three-axis accelerometers, low cost GNSS receivers and Persistent Scatterer Interferometry are fused and validated with high-precision 3D reference data derived from TLS surveys and UAV campaigns. The processing is based on soft computing algorithms while very accurate deformation maps are utilized for making decision about the current and the future state of each infrastructure. “PROION” project is financially supported by the European Union and the Hellenic government. «Acknowledgment: This research has been co‐financed by the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH – CREATE – INNOVATE (project code: T2EΔK-02396 Μultiparametric monitoring platform with micro-sensors of eNceladus hellenIc supersite)».

Landslides are among the most dangerous and catastrophic events in the world. The increasing progress in remote sensing technology made landslide observations timely, systematic and less costly. In this context, we collected multi-dated data obtained by Unmanned Aerial Vehicle (UAV) campaigns and Terrestrial Laser Scanning (TLS) surveys for the accurate and immediate monitoring of a landslide located in a steep and v-shaped valley, in order to provide operational information concerning the stability of the area to the local authorities. The derived data were processed appropriately, and UAV-based as well as TLS point clouds were generated. The monitoring and assessment of the evolution of the landslide were based on the identification of instability phenomena between the multi-dated UAV and TLS point clouds using the direct cloud-to-cloud comparison and the estimation of the deviation between surface sections. The overall evaluation of the results revealed that the landslide remains active for three years but is progressing particularly slowly. Moreover, point clouds arising from a UAV or a TLS sensor can be effectively utilized for landslide monitoring with comparable accuracies. Nevertheless, TLS point clouds proved to be denser and more appropriate in terms of enhancing the accuracy of the monitoring process. The outcomes were validated using measurements, acquired by the Global Navigation Satellite System (GNSS).

Volcanic eruptions pose a great threat to humans. In this context, volcanic hazard and risk assessment constitute crucial issues with respect to mitigating the effects of volcanic activity and ensuring the health and safety of inhabitants. Lava flows directly affect communities living near active volcanoes. Nowadays, remote sensing advances make it possible to effectively monitor eruptive activity, providing immediate and accurate information concerning lava evolution. The current research focuses on the mapping of the surface deformation and the analysis of lava flow evolution occurred on the island of La Palma, during the recent (2021) eruptive phase of the volcano. Sentinel-1 data covering the island were collected throughout the entire eruptive period, i.e., September 2021 until January 2022. The processing was based on amplitude-based and phase-based detection methods, i.e., Synthetic Aperture Radar interferometry (InSAR) and offset tracking. In particular, ground deformation occurred on the island, while Line-Of-Sight (LOS) displacements were derived from Sentinel-1 interferograms. Moreover, the evolution of lava flow velocity was estimated using Sentinel-1 imagery along with offset tracking technique. The maximum lava flow velocity was calculated to be 2 m/day. It was proved that both approaches can provide rapid and useful information in emergencies, especially in inaccessible areas. Although offset tracking seems a quite promising technique for the mapping of lava flows, it still requires improvement.

On 17th November 2015, a strong earthquake affected the southern part of the Lefkada Island, Greece. After the earthquake extensive translational debris slides triggered cross most of west coast of the island in a distance of about 15 km. The majority of these slides concentrated at Egremni beach which is a famous touristic destination. The cliff is crossed by the Cephalonia Fault Zone and this is considered as a major factor provoking the steep slope, large-scale co-seismic and post-seismic mass wasting and disturbance of the forest of the cliff. Seven years after the 2015 event, the cliff remains at retreat due to limited forestation, seismicity and storms in the area. Monitoring of the cliff was performed between 2015 and 2021 including extensive field measurements, unmanned aerial vehicle (UAV) flight campaigns and a sediment trap. The high-resolution images acquired by the UAV were used for the creation of orthophoto maps and digital surface models (DSMs) of the cliff. The data indicates that Egremni cliff is slowly entering a stage of equilibrium due to climatic forcing, alongside minor seismicity and absence of forestation. Mass-wasting processes remained significant across the Lefkada west coast seven years after the 2015 earthquake sequence.

It is widely known that water resources are facing several issues, as their limited availability has been affected by climate change, human over-exploitation and environmental pollution. The reduction of the availability of water resources along with the deterioration of water quality could have devastating consequences for human beings and natural environment. Therefore, ensuring the availability, quality and quantity of water resources is a key issue which has attracted the attention of researchers, governments and the public. The construction of dams constitutes a water storage solution in areas suffering from severe water shortage problems. Dams are artificial barriers, constructed across a river in order to hold back the rain water which falls during the wettest months, while a lake or reservoir is being formed behind them. In the current study, we map and monitor the existing water resources within the reservoir of a newly con-structed dam during its gradual filling. In that context, we acquired Sentinel-1 radar data and Sentinel-2 multispectral data which are provided free of charge to all users through the Copernicus programme. Our data sets are covering a period of one and a half year, from the completion of the dam construction and the beginning of the reservoir’s filling until today, wherein the water level is at the highest point. Sentinel-1 data were processed using random forest classifier and dividing the area into water and land sub-parts, while Modified Normalized Difference Water Index (MNDWI) was calculated for Sentinel-2 data. The multi-dated water extents were integrated in an ArcGIS environment in order to evaluate them and investigate if a combined processing of radar and multispectral data of Copernicus programme could be the right choice towards a more accurate and detailed monitoring of water resources in a dam reservoir. Validation of the results has been performed using in situ measurements and observations.

On 3 March 2021, a strong shallow earthquake affected northern Thessaly, Greece, with an epicenter close to Damasi village causing significant destruction of many stone houses. In this contribution, we provide fieldwork observations, satellite radar interferometry, mapping of the active faults exposed in the epicentral area, liquefactions and coseismic surface ruptures, and preliminary geomorphological analyses of the epicentral area. The geomorphological analysis is based on air photographs, digital surface models analysis, Real-Time Kinematik (RTK) measurements with Global Navigation Satellite System (GNSS) receivers, and data from UAV flight campaigns. Although the seismotectonic setting of the area is complex and there is an apparent mismatch between field and interferometric data, the results of our investigations suggest that at least three fault segments were reactivated by the major shocks of the March seismic sequence. These tectonic structureslikely represent the westward propagation of the Tyrnavos Graben, where newly formed and inherited low-angle faults interplay in a complex manner.

Landslide mapping is one of the most important steps which take place in the early stages of a landslide survey, contributing to the immediate assessment of slide’s effects. Nowadays in this direction, different remote sensing techniques have been developed providing effective results. This work deals with the exploitation of optical data as well as radar data aiming at the mapping of a landslide area located in Western Macedonia, Greece. The landslide occurred in June 2017 at the lignite open pit mine of Aminteo. In that context Sentinel-1, Sentinel-2 and Landsat-8 data were acquired in order to be processed appropriately for the imprinting of disturbed areas. In particular, Sentinel-1 images before and after the landslide were processed interferometrically, yielding to the estimation of vertical displacements. Concerning optical data, the images were submitted to diverse digital processing techniques the results were visualized in GIS environment. The derived results were compared and evaluated for their accuracy and identification. It is worth mentioning that the specific methodology may also be applied to more extensive landslides or landslides triggered by different factors. Additionally, it could be assumed that the methodology can be applied to mass movements as a result of earthquakes.

Landslides are posing a significant global hazard as they occur instantaneously with devastating consequences. The development of new remote sensing technologies and innovative processing techniques over the past few years opened up new horizons and perspectives in landslide monitoring research. The purpose of the current research is the integrated monitoring of an active landslide, located in Western Greece, using low-cost and high-repeatability remote sensing data like those obtained by unmanned aerial vehicles (UAVs). Repeated UAV campaigns and global navigation satellite systems (GNSS) surveys were performed to assess the activity of the landslide and determine its kinematic behavior. UAV data were processed using structure from motion (SfM) photogrammetry and the generated high-detailed orthophotos and digital surface models (DSMs) were submitted in further processing procedure in an ArcGIS environment. Regarding the GNSS data, a new low-cost technique for the estimation of the direction and the rate of movement of the displaced material was developed. The repeated measurements were displayed in a vector format in a three-axis diagram. In addition, GNSS measurements were used to verify the results of the photogrammetric processing. The final assessment was carried out taking into account geological data such as petrographic and crystallographic features of the material of the landslide. It was observed that the lithology and consequently the petrographic properties of the material plays a key role regarding the activity of the landslide.

Landslides or rockfalls in mountainous areas in Western Greece are a continuous hazard and thus, observation either in situ or through satellite data is of great necessity. In order to study landslides or rockfalls a very accurate representation of the relief is a prerequisite. In now days diverse remote sensing satellites provides digital surface elevation models (DSMs) with global coverage. The specific data sets present the advantages of covering large areas in a very low cost in comparison with the surveys in the field. In addition, high resolution DSMs enable the analysis of topography with high levels of detail and consequently geomorphometric approach becomes more accurate for studying landlsides or rockfall events. Information which can be extracted from geological and topographic maps in GIS format such as the slope angle distribution, deduced from high resolution DSMs, are substantial in rockfalls survey. In the present work, the accuracy of freely available DSMs are under control for landslides areas in Achaia prefecture in NW Peloponnese. The accuracy of the DSMs in the broader area is investigated using reference points of certified elevation while for the landslide area ground control collected with differential GNSS receiver are used. More specifically, free available DSMs as TanDEMX, ASTER GDEM, SRTM DEM with 30m and 90m spatial resolution, ALOS AW3D30 DEM, DSM from photogrammetric airphoto processing and DSM produced by Interferometric processing of radar images, are under examination in the current study. Furthermore, diverse statistical parameters such as the 2D Root Mean Square Error or the percentile value are computed and presented. The purpose of the aforementioned procedure is to detect the most accurate DSMs which are appropriate for landslide of rockfall monitoring.

Dams are engineering structures with significant social and economic benefits as well as risks. A structural or operating failure of the dam poses a threat to nearby industrial sites, human settlements, and the environment. Usually, the consequence is an immense economic loss for the region. Therefore, it is of great importance to ensure dam health and functionality. The dead load of the dam body itself and the impounded water, among other things, can cause horizontal and vertical displacements of the dam body. If these displacements surpass a critical limit, the structural integrity of the dam is threatened. Therefore, the surface deformations need to be monitored. In this study, we discuss the different mechanisms, which lead to the deformation of a dam and how they can be monitored. First, an overview of the different construction types of dams currently in use is given. Whereby the focus is on embankment dams, since our main observation target, the Parapeiros-Peiros Dam, is an embankment dam. Second, the deformation processes an embankment dam may be subject to during its lifetime are described. Additionally, the conventionally used instruments and methods to measure these deformations, such as geodetic triangulation or optical leveling networks, are discussed. Based on the deformation processes known from the literature, we outlined what characteristics of an embankment dam need to be taken into account when setting up a deformation monitoring system. The monitoring system, we propose, works continuously and semi-automatically. The main task is to accurately map the surface deformations of the dam body and the surrounding area using SAR images and GPS positions of several control points. Afterward, changes in the behavior of the dam need to be identified and analyzed.

Mass movements and therefore rockfalls are common natural hazards that require the development of new methodologies and techniques for an effective research, which could help governments, communities or policy makers in the adoption of the most appropriate practices. In that context different remote sensing data have been used and several methodologies have been tested. In the present study, we initially map a rockfall occurred on the settlement Myloi, which is located near the village of Andritsaina in Western Greece, while later we estimated the volume of rock fragments. The data sets consist of repeated GNSS measurements, laser scanning surveys and UAV campaigns over the study area. The precise mapping of the rockfall was carried out through the processing of GNSS measurements. However, mapping was also performed using orthophotos derived from UAV data and 3D images of laser scanning campaigns. Regarding the volume estimation, three methodologies were applied -two of them were photogrammetric and one was geophysical- using ArcGIS, Cloud Compare and Oasis Montaj from Geosoft respectively. The selection of different types of data and processing methodologies took place within the framework of the comparison of their results in terms of accuracy as well as the achievement of their synergy in the direction of a more detailed research.

This study presents the synergy of multidisciplinary surveys for the monitoring of an active landslide in Western Greece. The aim of this paper is to highlight and validate a methodology based on multiple sensors data integration which can successfully be used to manage natural disasters or to improve the knowledge of a specific phenomenon in order to prevent and mitigate the risk. Photogrammetric and interferometric processing has been applied to a complex set of remote sensing data such as high resolution satellite images, digital airphotos, aerial photos acquired from an Unmanned Aerial Vehicle and radar data. Global Navigation Satellite System measurements and continuous inclinometer measurements are being performed. The multifunctional technology of Geographic Information Systems is used in order to collect, storage, manage, process, analyze and cartographically represent the previously described complex geoscientific information.

In recent years urbanized areas have been expanding more and more into hillside areas, which increases the risk for landslides to destroy or gravely damage human settlements, industrial establishments and important infrastructure. Greece and in particular the northwestern tip of the Peloponnese Peninsula are often affected by landslides. A well-known and documented landslide south-east of Patras is located in that area and was chosen as the main focus for this study. The landslide collapsed and thus submerged the main road connecting the small village Moira and Patras on January 20, 2016. Immediately afterwards the geometry and geology of the affected area have been determined using GNSS Measurements, UAV Campaigns and DInSAR techniques. However, the velocity of the post-collapse movement has not been investigated. In order to make this determination two time series of SAR images acquired by the two Sentinel-1 satellites from an ascending and descending orbit were evaluated using the advanced InSAR technique of persistent scatterer interferometry. The result is a map of the mean velocities the identified persistent scatterers were experiencing in the time period from January 2017 to June 2019. The persistent scatterer density in the rural areas of the region was sufficient enough to identify the landslide within the results. Roughly 80 persistent scatterer with a velocity of more than ± 8 mm/a in the line of sight of the sensor were identified within the outlines of the landslide (approximately 750 m2), indicating that the landslide is experiencing post-collapse movement.

Oil spills, whether those come from tanker ships or offshore platforms, might potentially be disastrous for the environment as well as for the society both socially and economically. Generally, oil spills are spreading quite easily for hundreds of nautical miles at the sea damaging large areas and causing serious ecological disasters. Numerous accidents such as the Exxon Valdez accident in Alaska in 1989, the Prestige oil spill at the coast of Galicia, Spain in 2002 or the Deepwater Horizon platform oil spill accident in 2010 in the Gulf of Mexico have unfortunately demonstrated the dangerousness of an oil accident. Remote sensing constitutes an effective solution in oil mapping and monitoring. Specifically, Synthetic Aperture Radar (SAR) satellites have already proved their effectiveness in the specific research field. Oil identification and mapping constitutes a key point of the oil prevention research since is an essential step for the quantification of the oil volume and thereafter the development of a spread model. As case study of the specific work it was selected the Agia Zoni II oil spill, which resulted from the wreck of the Agia Zoni II tanker on September 10th, 2017. This work focuses on the best possible in terms of accuracy mapping of the Agia Zoni II oil spill using Sentinel-1 and Sentinel-2 imagery. The mapping was based on the application of three different processing approaches: a) using the oil spill tool, provided by SNAP software, b) using a semi-automatic methodology and c) by applying a sort of classification in Sentinel-1 images. The approaches were compared and evaluated regarding the quality (reliability) of the final product and the required processing time. The validation of the results of the oil spill mapping using different approaches implemented by the digitization of the affected areas utilizing Sentinel-2 data in ArcGIS environment.

The detailed and accurate mapping of landscapes and their geomorphological characteristics is a key issue in hazard management. The current study examines whether the image acquisition geometry of unmanned aerial vehicle (UAV) campaigns affects the accuracy of the derived products, i.e., orthophotos, digital surface models (DSMs) and photogrammetric point clouds, while performing a detailed geomorphological mapping of a landslide area. UAV flights were executed and the collected imagery was organized into three subcategories based on the viewing angle of the UAV camera. The first subcategory consists of the nadir imagery, the second is composed of the oblique imagery and the third category blends both nadir and oblique imagery. UAV imagery processing was carried out using structure-from-motion photogrammetry (SfM). High-resolution products were generated, consisting of orthophotos, DSMs and photogrammetric-based point clouds. Their accuracy was evaluated utilizing statistical approaches such as the estimation of the root mean square error (RMSE), calculation of the geometric mean of a feature, length measurement, calculation of cloud-to-cloud distances as well as qualitive criteria. All the quantitative and qualitative results were taken into account for the impact assessment. It was demonstrated that the oblique-viewing geometry as well as the combination of nadir and oblique imagery could be used effectively for geomorphological mapping in areas with complex topography and steep slopes that overpass 60 degrees. Moreover, the accuracy assessment revealed that those acquisition geometries contribute to the creation of significantly better products compared to the corresponding one arising from nadir-viewing imagery.

On 17th November 2015, a strong earthquake affected Lefkada Island, Greece, leading to extensive translational debris slides along the cliff overhanging Egremni beach and the re-activation of previously deposited slope material. The cliff is crossed by the Cephalonia Fault Zone, with mass-wasting processes inducing dry flows occurring in association with long-term tectonic activity. Large-scale co-seismic and post-seismic disturbance of the forest on top of the cliff has also resulted from the seismicity. Three years after the 2015 event, the cliff had retreated due to active translational debris slides and the forest disturbance, which represents a safety concern for the tourist beach below. We aimed to qualitatively assess the transient evolution of debris slides at Egremni and clarify the level of risk posed to the beach below. Annual monitoring was performed between 2015 and 2018 including extensive field measurements and unmanned aerial vehicle (UAV) flight campaigns. Based on the high-resolution images acquired by the UAV, we created orthophoto maps and digital surface models (DSMs) of the cliff using Structure-from-Motion (SfM) photogrammetry. The cliff slope models indicate that the overhanging cliff is progressively entering a stage of decline and approaching equilibrium due to climatic forcing alongside minor seismicity. The DSMs were combined with field survey data to further investigate the role of erosion and deposition across the cliff. Our results indicate that the cliff dynamics at Egremni are primarily controlled by earthquake- and storm-induced debris slides, with rock material moving within the cliff formation via rock falls, and cliff inclination decreasing as a result of primitive slope ‘self-healing’ process. Mass-wasting processes remained widespread across the western part of the Lefkada coast three years after the 2015 earthquake sequence. For safety reasons, we suggest that pre-emptive inspection of the cliffs should be carried annually, after humid and winter periods, and following strong earthquakes using a combination of field surveys and UAV campaigns.

Both Terrestrial Laser Scanner and Structure from Motion photogrammetry are considered as reliable methods for collecting relief elevation data in the form of dense point clouds. The point density is their common big advantage compared to classical survey measurements. Although both methods produce millions of XYZ points, the manner of collecting data is different resulting in point clouds with serious differences. In the current study these two methodologies for 3D point cloud generation are compared. As a test site is considered a part of a well mapped active landslide in western Greece. In this landslide a terrestrial laser scanner was deployed for the collection of 3D information of the steep slopes. At the same time UAVs flights were performed and dense point clouds were also generated. The derived products from the TLS and UAV are compared and the results are presented.

The purpose of this work is to present the detection and qualification of natural karst depressions in southern Ksiromero, SW Aitoloakarnania Prefecture, Western Greece, by the use of freely available digital surface model (DSM) data in line with the geographical information systems—GIS. The study area is a part of the Ionian geotectonic zone whose geological background consists of the Triassic evaporates and Triassic carbonate breccias. The after-Triassic carbonate series, which consist of the Jurassic limestones, the Cretaceous limestones and the Eocene limestones, are also presented in the study area. Several DSMs such as ASTER GDEM, SRTM DEM, ALOS Global DSM, and a DSM generated from Sentinel-1 data were evaluated so as to be used for the automatic karst detection. Furthermore, a karst detection procedure applied on DSMs was performed with the aid of analogue and digital air photos. Additionally, the aforementioned procedure was applied also on DEM with the aid of digitized contours referring to topographic maps characterized by a scale of 1/50,000. All the detected features have been also validated via in situ observations. Finally, all DSMs presented herein are characterized by similar percentage of success in terms of automatic karst detection, regardless their spatial resolution and height accuracy. Their rate varies from 66 to 73%.

Coastline evolution is a proxy of coastal erosion, defined as the wasting of land along the shoreline due to a combination of natural and/or human causes. For countries with a sea border, where a significant proportion of the population lives in coastal areas, shoreline retreat has become a very serious global problem. Remote sensing data and photogrammetry have been used in coastal erosion mapping for many decades. In the current study, multi-date analogue aerial photos, digital aerial photos, and declassified satellite imagery provided by the U.S. Geological Survey (USGS), Pleiades satellite data, and unmanned aerial vehicle images were combined for accurate mapping of the southwestern Lefkada (Ionian Sea, Greece) coastline over the last 73 years. Different photogrammetric techniques were used for the orthorectifation of the remote sensing data, and geographical information systems were used in order to calculate the rates of shoreline change. The results indicated that the southwest shoreline of Lefkada Island is under dynamic equilibrium. This equilibrium is strongly controlled by geological parameters, such as subsidence of the studied shoreline during co-seismic deformation and mass wasting. The maximum accretion rate was calculated at 0.55 m per year, while the respective erosion rate reached &minus, 1.53 m per year.

Interferometry constitutes a technique of acquisition height information with a range of applications, such as Digital Surface Model (DSM) generation in order to monitoring the Earth's surface. This work is focused on interferometric DSM creation utilizing radar data of Sentinel-1 and TerraSAR-X missions, covering the wider area of Northern Peloponnese. This area is characterized of loose geological formations and intense active tectonics resulting in continuous and intense relief changes. In this context, the accuracy and the update of the DSMs is essential in order to detect and map any terrain change. The selection of Sentinel-1 and TerraSAR-X images was based on the fact that both missions provide timely, with short revisiting period and satisfactory spatial resolution data. In particular, two ranges of radar data from both missions were submitted in interferometric process aimed at DSM creation. The produced DSMs were compared both visually and statistically to a very accurate reference DSM produced from airphotos by the Greek Cadastral. Furthermore, in order to estimate the accuracy of the DSMs and detect variations of terrain’s surface, points of known elevation have been used. 2D RMSE, correlation and the percentile value were computed and the results are presented.

The current paper presents the combined use of geological-geotechnical insitu data, remote sensing data and GIS techniques for the evaluation of a subsurface geological model. High accuracy Digital Surface Model (DSM), airphotos mosaic and satellite data, with a spatial resolution of 0.5m were used for an othophoto base map compilation of the study area. Geological – geotechnical data obtained from exploratory boreholes and the 1:5000 engineering geological maps were digitized and implemented in a GIS platform for a three – dimensional subsurface model evaluation. The study is located at the North part of Peloponnese along the new national road.

Floods are suddenly and temporary natural events, affecting areas which are not normally covered by water. The influence of floods plays a significant role both in society and the natural environment, therefore flood mapping is crucial. Remote sensing data can be used to develop flood map in an efficient and effective way. This work is focused on expansion of water bodies overtopping natural levees of the river Evros, invading the surroundings areas and converting them in flooded. Different techniques of flood mapping were used using data from active and passive remote sensing sensors like Sentinlel-1 and Landsat-8 respectively. Space borne pairs obtained from Sentinel-1 were processed in this study. Each pair included an image during the flood, which is called “crisis image” and another one before the event, which is called “archived image”. Both images covering the same area were processed producing a map, which shows the spread of the flood. Multispectral data From Landsat-8 were also processed in order to detect and map the flooded areas. Different image processing techniques were applied and the results were compared to the respective results of the radar data processing.

Space-borne SAR sensors are capable to measure ground elevation using interferometric (InSAR) or radargrammetric techniques. In the first case, the phase content is used while in the second case the amplitude values of SAR image are exploited. This work is focused on the analysis of potentialities of the Interferometric and radargrammetric DSMs generation using high resolution SAR imagery acquired by two of the newer satellite platforms (Sentinel -1 and COSMO-SkyMed). Eleven Sentinel-1 and two COSMO-SkyMed scenes have been processed. A full comparison and analysis has been carried for Myconos Island where a high accuracy DSM from the Greek cadastral and other DEM from digitized contours from the 1/50.000 topographic maps are available. After a first control for random or systematic errors a statistical analysis was done. Points of known elevation have been used to estimate the accuracy of the DSMs. 2D RMSE, correlation and the percentile value were computed and the results are presented.