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During the past few decades, remote sensing has been established as an innovative, effective and cost-efficient option for the provision of high-quality information concerning infrastructure to governments or decision makers in order to update their plans and/or take actions towards the mitigation of the infrastructure risk. Meanwhile, climate change has emerged as a serious global challenge and hence there is an urgent need to develop reliable and cost-efficient infrastructure monitoring solutions. In this framework, the current study conducts a comprehensive review concerning the use of different remote-sensing sensors for the monitoring of multiple types of infrastructure including roads and railways, dams, bridges, archaeological sites and buildings. The aim of this contribution is to identify the best practices and processing methodologies for the comprehensive monitoring of critical national infrastructure falling under the research project named “PROION”. In light of this, the review summarizes the wide variety of approaches that have been utilized for the monitoring of infrastructure and are based on the collection of remote-sensing data, acquired using the global navigation satellite system (GNSS), synthetic aperture radar (SAR), light detection and ranging (LiDAR) and unmanned aerial vehicles (UAV) sensors. Moreover, great emphasis is given to the contribution of the state-of-the-art soft computing methods throughout infrastructure monitoring aiming to increase the automation of the procedure. The statistical analysis of the reviewing publications revealed that SARs and LiDARs are the prevalent remote-sensing sensors used in infrastructure monitoring concepts, while regarding the type of infrastructure, research is orientated onto transportation networks (road and railway) and bridges. Added to this, deep learning-, fuzzy logic- and expert-based approaches have gained ground in the field of infrastructure monitoring over the past few years.

Intense long-duration rainfall or extreme precipitation in a few hours can provoke many simultaneous shallow landslides. In the past, the term multi-occurrence regional landslides (MORLEs) was proposed to describe such phenomena. In the current study, unmanned aerial vehicles in combination with a global navigation satellite system sensor and geographical information systems seem to be the ideal solution for the rapid assessment of many landslides occurring in Aitoloakarnania Prefecture, Western Greece. Fourteen landslides were accurately mapped within a few working days, and precise orthophotos and reports were created and submitted to the local authorities. The analysis of meteorological data proved that there is a peak in precipitation height that triggers the MORLEs in the specific area. Specifically, the value of the daily precipitation was defined at 80 mm.

On 3 March 2021, an important seismic sequence started in northern Thessaly, Greece. The Damasi Seismic Sequence (DSS) deformed the western sector of the Tyrnavos Graben, which includes a major blind normal fault and the Titarisios River Graben (TRG). In this contribution, we provide fieldwork observations across the TRG and satellite radar interferometry of the faults controlling the graben. In addition, we provide a map of the active faults exposed in the TRG and palaeoseismological analyses of the Mesochori Fault, which together contribute to unravelling the seismic history of the area. DInSAR provides clear evidence of the Mesochori Fault surface rupture during the main shocks, while our palaeoseismological analyses document a long seismic history of the fault, with a mean recurrence interval of 1.0–1.5 ka and a mean slip per event of ~15 cm for the last four events reactivating the scarp. Quantitative geomorphological analyses based on real-time kinematic (RTK) measurements with global navigation satellite system (GNSS) receivers and data from UAV flight campaigns also provide evidence of postseismic activity across the Mesochori Fault. Based on these results showing that (at least) the Mesochori Fault has been reactivated several times in the latest Quaternary the seismotectonics of the TRG are discussed.

The current research aims to examine the long-term evolution of the western cliffs of Lefkada Island following the occurrence of the last two strong earthquakes, on 14 August 2003 and 17 November 2015, respectively. Medium resolution satellite data (Landsat) and very high-resolution data (Ikonos, Pleiades, and airphotos) were processed in Google Earth Engine and Erdas imagine software, respectively. The study area covers a 20 km-long region of the western cliffs of Lefkada Island, extending from Egremni beach to the South to Komilio beach to the North. Relief, vegetation, and inclination changes were detected in the ArcGis environment. The results were associated with in situ data provided through the installation of a sediment trap. The analysis of the results proved that seismicity is the main factor that formed the western coastline of Lefkada Island, affecting the integrity of the cliffs. Specifically, large earthquakes cause immediate vegetation and topographic (inclination changes, mass movements) modifications in the western cliffs of the island. Meanwhile, small earthquakes (magnitudes < 4.1) contribute to the cliff’s evolution during the inter-seismic era. The intensity of these aforementioned changes was closely related to the seismic activity that occurred in the vicinity of the study area. In addition, it was found that precipitation and wind do not exert a similar influence on the cliff’s evolution.

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).

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.

Remote sensing constitutes an advantageous tool towards the landslide/rockfall susceptibility mapping by incorporating optical satellite or radar data and photogrammetric data in Geographical Information System environment. A plethora of rockfall data can be derived by gigital surface models (DSMs). This article focuses on the effect of the spatial resolution of DSMs in rockfall investigations solely. DSMs with pixel size ranging from 5 cm to 90 m were taken into account for the study of three different rockfall events occurring in Western Greece, namely, at Moira, Myloi and Platiana settlements. Elevation profiles along the rockfall bodies were created from the diverse DSMs in GIS environment. Then, these profiles were implemented into the RocFall software for 2D rockfall simulations. The produced simulations were evaluated against their spatial resolution of DSMs and were confirmed with field observations and measurements. The ultimate scope of this paper is to conclude to the most appropriate DSM for rockfall simulations via RocFall software. It is observed that DSMs with high spatial resolution depicted a detailed and realistic topography, while DSMs with coarse/low resolution flattened the surface roughness. As rockfall simulations are linked to slope profile, this observation has an impact on RocFall outcomes. According to this study the most appropriate DSM, pertaining to this type of research, is the UAV, which produces the more accurate and realistic results. These results were assessed through the use of in situ measurements taken by the real rockfall events.

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.

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).

Remote sensing data and techniques are widely used for monitoring and managing natural or man-made disasters, due to their timeliness and their satisfactory accuracy. A key stage in disaster research is the detailed and precise mapping of an affected area. The current work examines the relationship that may exist between the acquisition geometry of Unmanned Aerial Vehicle (UAV) campaigns and the topographic characteristics of an investigated area, toward landslide mapping and monitoring that is as accurate as possible. In fact, this work, concerning the systematic research of the acquisition geometry of UAV flights over multiple active landslides, is conducted for the first time and is focused on creating a guideline for any researcher trying to follow the UAV photogrammetric survey during landslide mapping and monitoring. In particular, UAV flights were executed over landslide areas with different characteristics (land cover, slope, etc.) and the collected data from each area were classified into three groups depending on UAV acquisition geometry, i.e., nadir imagery, oblique imagery, and an integration of nadir and oblique imagery. High-resolution orthophotos and Digital Surface Models (DSMs) emerged from the processing of the UAV imagery of each group through structure-from-motion photogrammetry (SfM). Accuracy assessment was carried out using quantitative and qualitative comparative approaches, such as root mean square error calculation, length comparison, and mean center estimation. The evaluation of the results revealed that there is a strong relationship between UAV acquisition geometry and landslide characteristics, which is evident in the accuracy of the generated photogrammetric products (orthophotos, DSMs). In addition, it was proved that the synergistic processing of nadir and oblique imagery increased overall centimeter accuracy.

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.

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.

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.

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 −1.53 m per year.