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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 are recognized as one of the most damaging natural hazards in Western Greece due to the complex geological structure, the intense precipitation and the high seismicity. In that context, the development of low-cost, semiautomatic, monitoring methodologies based on satellite data is a necessity in order to prevent and mitigate the landslide risk and decrease the damages in a future reactivation. The current study focuses on the application of three different processing methodologies on Sentinel-1 data: (a) interferogram generation, (b) comparison of interferometric Digital Surface Model (DSM) before and after the landslide event and (c) another processing technique called “offset tracking”. The selection of Sentinel-1 data was based on the fact that the specific mission provides timely, freely accessible data, with satisfactory spatial resolution for repeated earth observation. The study area is located almost 20 km south of the city of Patras near to the Village Moira. The landslide with a total length of 300 m and a head width of 330 m is being investigating by repeated field campaigns and Global Navigation Satellite System measurements, and thus, the derived results from the Synthetic Aperture Radar (SAR) data processing were evaluated with the in situ measurements.

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.

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.

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.