We present a GIS-based crowdsourcing application that was launched soon after the first COVID-19 cases had been recorded in Greece, motivated by the need for fast, location-wise data acquisition regarding COVID-19 disease spread during spring 2020, due to limited testing. A single question was posted through a web App, to which the anonymous participants subjectively answered whether or not they had experienced any COVID-19 disease symptoms. Our main goal was to locate geographical areas with increased number of people feeling the symptoms and to determine any temporal changes in the statistics of the survey entries. It was found that the application was rapidly disseminated to the entire Greek territory via social media, having, thus, a great public reception. The higher percentages of participants experiencing symptoms coincided geographically with the highly populated urban areas, having also increased numbers of confirmed cases, while temporal variations were detected that accorded with the restrictions of activities. This application demonstrates that health systems can use crowdsourcing applications that assure anonymity, as an alternative to tracing apps, to identify possible hot spots and to reach and warn the public within a short time interval, increasing at the same time their situational awareness. However, a continuous reminder for participation should be scheduled.

The spatial and temporal scale of flash flood occurrence provides limited opportunities for observations and measurements using conventional monitoring networks, turning the focus to event-based, post-disaster studies. Post-flood surveys exploit field evidence to make indirect discharge estimations, aiming to improve our understanding of hydrological response dynamics under extreme meteorological forcing. However, discharge estimations are associated with demanding fieldwork aiming to record in small timeframes delicate data and data prone-to-be-lost and achieve the desired accuracy in measurements to minimize various uncertainties of the process. In this work, we explore the potential of unmanned aerial systems (UAS) technology, in combination with the Structure for Motion (SfM) and optical granulometry techniques in peak discharge estimations. We compare the results of the UAS-aided discharge estimations to estimates derived from differential Global Navigation Satellite System (d-GNSS) surveys and hydrologic modelling. The application in the catchment of Soures torrent in Greece, after a catastrophic flood shows that the UAS-aided approach succeeded in determining peak discharge with high accuracy. The technique proved to be particularly effective, providing flexibility in terms of resources and timing, although there are certain limitations to its applicability. The application highlighted important advantages and certain weaknesses of these emerging tools in indirect discharge estimations, which we discuss in detail.

Remote sensing techniques and laser scanning technology have given us the opportunity to study indoor environments, such as caves, with their complex and unique morphology. In the presented case study, we used a handheld laser scanner for acquiring points with projected coordinate information (X, Y, Z) covering the entire show cave of Koutouki; including its hidden passages and dark corners. The point cloud covers the floor, the walls, and the roof of the cave, as well as the stalactites, stalagmites and the connected columns that constitute the decoration of the cave. The absolute and exact placement of the point cloud within a geographic reference frame gives us the opportunity for three-dimensional measurements and detailed visualization of the subsurface structures. Using open - source software, we managed to make a quantification analysis of the terrain and generated morphological and geometric features of the speleothems. We identified 55 columns by using digital terrain analysis and processed them statistically in order to correlate them to the frame of the cave development. The parameters that derived are the contours, each column height, the speleothem geometry and volume, as well as the volume of the open space cavity. We argue that by the demonstrated methodology, it is possible to identify with high accuracy and detail: the geomorphological features of a cave, an estimate of the speleogenesis, and the ability to monitor the evolution of a karstic system.

The goal of this study is to create a high-resolution grid of precipitation indices for the wider Greek region using real data from meteorological stations for the 1980-2010 period. Under the risk of increased extreme events caused by climate change, it is important to be able to have a high-resolution gridded extreme precipitation indices in order to overcome the lack of density of observations in both time and space. The development of such a grid can be used to validate model outputs and inform decision makers to better mitigate the damage from extreme precipitation. The first step of the analysis is to calculate the extreme precipitation indices based on daily observations derived from more than 100 meteorological stations covering a wide range of altitudes and spatial climate patterns existing in Greece. Thereafter, the extreme indices will be multilinearly downscaled to a 12-meter resolution grid. The geophysical parameters used in the downscaling procedure consists of altitude, latitude, longitude, slope, aspect, solar irradiance and Euclidian distance from the water bodies. The altitude information came from the highly accurate 12-meter resolution TanDEM-X Elevation Model, which is a product generated from the TerraSAR-X satellite mission data. The resulting high-resolution patterns will give insight of the spatial and temporal variability of extreme precipitation, over the complex terrain of the wider Greek region.

The Ionian Islands are located in the northwestern part of the Hellenic Arc and constitute one of the most seismically active areas in the Mediterranean. Building a geospatial database including all the available geo-information layers was the initial step for identifying and delineating the earthquake-related environmental effects by using various mapping algebra techniques and algorithms. Landslide, liquefaction and tsunami related inventories were created. Real time recording network of sensors such as meteorological instruments, seismographs, accelerometers etc was designed to trans pond data telemetrically and feed a dynamically interactive geodatabase, which in turn act as a smart tool for declaring an area as vulnerable to a specific hazard. The abovementioned approach can contribute to the reduction of the consequences after a disastrous event, as it will provide useful information to the civil protection authorities for increased alertness during an ongoing threat. The identification of the risk areas by using various methods has become significant in recent years due to the fact that among others it serves as a valuable tool for revealing and highlighting sites of significant hazards. In this study we present a smart tool, specially developed for recording and taking under consideration any changing parameters that affect the susceptibility of an area to any of the studied geo-hazards and highlight it on a digital real time updateable map.

The state-of-the-art in surveying of open surface the last few decades is based on Point Cloud processing and interpretation. Lately, similar technology tends to be used for indoor surveying as well. One of the extreme applications is the use of the exact same technology in underground karstic cavities, evolving the methodology used in cave mapping. Geometric and morphometric analysis of the caves or any containing components (speleothems) include various techniques aiming at quantifying their dimensions in order to determine the characteristics and consequently the relationship between the cavity morphology and the surrounding structural, lithological and hydrogeological properties. The purpose of this research is to combine high resolution topographic data acquired with different instruments for both the underground morphology of a karstic cave (Koutouki, Peania, Greece) and the open-air surface above it. The described methodology is based on photogrammetric processing of Unmanned Aerial System image data and the extraction of a point cloud recorded with the use of a handheld laser scanning system. The latter resulted a 3D model of the cave and led to the production of a digital relief for the roof of the cave, which in turn was combined with the digital terrain model of the open-air surface above the cave. The final product is a high-resolution information layer with measurements of the rock thickness between the roof of the underground karstic structure and the open-surface topography with high accuracy.

Geological failures from massive rockfall failures to small landslides of few cubic meters are a major geological hazard in many parts of the world. Based on the latest developments, close-range photogrammetry and individually UAV photogrammetry and Light Detection and Ranging systems have become indispensable tools for geo-experts in order to provide ultra high-resolution 3D models of the failure site. TLS suffers from the fact that is sometimes tricky to capture the holistic area of interest from the ground, while some areas may often be obscured by vegetation or negative inclinations. The science of photogrammetry has long been used to accurately detect and characterize landslide and rockfall failures. Due to the continuously increasing spatial resolution capability of new generation sensors, traditional pixel-based approaches are not capable to cope with the level of detail resulted from those sensors. Mostly, landslides present complex and dynamic geomorphological features with great heterogeneity in their spatial, spectral and contextual properties dependent on the specific failure mechanism. In the current study, an object-based 3D approach for the automated detection of landslide and rockfall hazard is presented based on detailed topographic photogrammetric point clouds and 3D analysis. Recent trends show that close photogrammetry will play a vital role on the geological and engineering geological assessments concerning geo-failures. The results show that object-based approach is closer to human interception due to integration of contextual and semantic, spectral and spatial information rather than translating pixel’s spectral information solely. The current procedure provides a detailed objective quantification of landslide characteristics and automated semantic landslide modelling of the case site.

Three main aquifer systems developed on Kythira Island (Greece) include (Pagounis, 1981; Pagounis & Gertsos, 1984, Danamos, 1991; Koumantakis et al., 2006; Filis et al., 2019):

• The porous aquifer system in Neogene and Quaternary formations.
• The karst aquifer system in the carbonate formations of the Pindos and Tripolis Units.
• The aquifer system (both shallow and deep) in the fractured hard rocks mainly of the Phyllites – Quartzites Unit.

The main discharge of the aquifer systems takes place in coastal and submarine brackish springs around the island, except for its northern part where the Phyllites – Quartzites Unit outcrops and its central part where springs of small capacity discharge the carbonate formations of the Pindos Unit. Precipitation is the direct recharge of the three aforementioned aquifer systems while indirectly lateral discharge occurs in places between adjacent and tangential aquifer systems and from the streams runoff as well. In the area of Mylopotamos village four springs discharge the karst aquifer of the Pindos Unit within the channel of Kako Laghadi stream forming downstream the known “Neraida or Fonissa waterfall”. Moreover, along the dell of Kako Laghadi stream 22 watermills were built, among the plane trees and the ivy. The most significant of the aforementioned springs is the Kamari spring (+282.28 meters a.s.l.) which emerge at the thrust fault between the overlying permeable carbonates and the underlying impermeable flysch formation of the Pindos Unit. The discharge of the Kamari spring presents annual fluctuation which varies from app. 45-50 m3/h (during winter) to total recession (during summer), due to restriction of the precipitation and the prolonged drought and overpumping of its recharge area mainly with boreholes. The inactive municipal borehole of Mylopotamos village (+299.15 meters a.s.l.) is located app. 310 meters SSE of the Kamari spring within its recharge area (karst aquifer of the Pindos Unit). This borehole of a total depth of 40 meters penetrates carbonates of the Pindos Unit which thickness exceeds 100 meters in that area. Monthly measurements of the Kamari spring discharge and the water table head in the inactive borehole demonstrate clear and direct hydraulic correlation between them. The Kamari spring presents outflow only in the case when the water level head of the borehole exceeds +282.28 meters. This means that the water level head in the borehole should not exceed 16.87 meters from the earth surface. Taking into account all the aforementioned, the Kamari spring is designated as an overflow spring. Finally, microbiological analysis from the Kamari spring showed qualitative degradation, due to human activities in the wider area (Pagounis, 1981; Filis et al., 2019).

During the period 24-25 November 2019 a low pressure system with organised convective storms has affected Greece as it crossed the country from west to east. The system, which was name Gyrionis, after a name used in the Greek mythology, has produced heavy rainfall, with increased lightning activity and local hailstorms. In the area of western Attica the maximum rainfall has been reported with 92 mm of on 24 November and additional 115 mm in 25 November, adding to a storm total of 206 mm, which caused flash floods in the town of Kineta. The storm caused overflowing of local torrents draining the south slopes of Geraneia Ori, inducing significant damages in property and infrastructure mainly within the town and across the coastal zone. Field surveys showed that a wildfire that burned through almost the entire catchment of the main torrent (named Pikas) on 2018, played a crucial role in flooding and its impact on the town. At critical locations along the river, vegetation debris and eroded material of various grain sizes, including boulders, diminished dramatically the hydraulic capacity of the river, intensifying flooding in the downstream areas, which formed an alluvial fan. Based on comparison of pre- and post-flood aerial photography of the burned area, a major source of this deposited material was identified as burned trees still standing after the fire, uprooted from the river banks of the main channel and carried away together with additional soil debris. The material was jammed at a crucial location near the apex of the alluvial fan causing floodwaters to overflow and inundate significant parts of the fan’s apron, a geomorphological setting that increased the extent and impact of flooding further. Overall, the case of Kineta, is a characteristic case of post-wildfire flash flooding, in which the fire effects are critical in the enhancement of subsequent flooding phenomena.

The general understanding of the major tectonic structures that are traced on Crete Island is of great importance to decipher the geodynamic regime of the leading edge of the overriding Aegean microplate and consequently Eurasia’s southernmost active margin. The aim of this multi-disciplinary methodology is to provide useful information for more reliable mapping of buried structures, which in turn supplement the dynamic and kinematic model of this key area of high interest. Several indicators for the existence of oblique fault block displacement were identified with the use of earth observation data, as strike slip faulting expressions on the surface are more efficiently identified by vertical observations. Tectonic structures which are usually created along lateral displacements require different working scales. Hence, earth observation data (satellite images, aerial photographs) with various spatial characteristics need to be included. Therefore, the methodology presented in this paper involves high spatial resolution digital elevation models and several remote sensing multispectral datasets, in many cases merged with higher spatial resolution panchromatic aerial photographs. The co-registration and ortho-rectification of all datasets proved to be a very significant part of this work in order to produce high resolution coloured 3D scenes at selected sites in central Crete, where the observed N-S trending strike slip fault zones crosscut arc parallel low angle normal faults and higher angle fault scarps. Additionally, deep seismic reflection datasets along the major geomorphic structure of Messara basin were combined and highlighted the strike slip mechanism, since the continuation of the sub-vertical structures in depth has become clearer after the exact positioning of the sections and further interpretation.

Unmanned Aircraft Systems (UAS) can be used to enhance monitoring of a wide range of environmental parameters, including acquiring data on various types of hydro-geomorphic phenomena. Their capabilities to provide on demand images and videos of high resolution, are particularly useful in the case of flash flood phenomena, which occur in spatial and temporal scales that do not favor traditional monitoring processes. In this work, flow velocity is estimated using aerial imaging acquired by means of an Unmanned Aircraft Vehicle (UAV) as well as ground observations during the catastrophic flash flood event of November 2017 in Mandra, Greece. In these imaging detailed tracing of various floating objects and particles such as light trash, debris etc. was carried out using multiple high-resolution video frames with specific time marks. Water velocity estimations were also cross-examined using flood mark-derived velocity hydraulic heads extracted by ground observations after the flood. The analysis was applied at a variety of locations across the study area, leading to a map of velocities for parts of the floodplain. Velocity values varied significantly depending on location, reaching up to 10m/s. The UAS proved to be very useful for the collection of important information for an extended area during the flood since a large portion of it was inaccessible due to road closures and safety issues. Nevertheless, the approach comes with certain limitations, including flight regulations, safety precautions and that rainfall is at a level that allows the deployment of a UAV during a flash flood. The findings show that the integration of aerial with ground observations in post-flood analysis contributes the completeness and accuracy of datasets regarding specific flash flood parameters and in the future could become a useful source of information, especially in data-poor regions.

The improvement of the accuracy of Structure-from-Motion photogrammetric products is discussed in this paper. In most cases it depends on the number and distribution of ground control points (GCPs) for block orientation, although the placement and precise measuring of GCPs are often time-consuming in a UAS project. This paper presents the evaluation of two approaches including Post Process Kinematic (PPK) and Network Real Time Kinematic (NRTK) methods aiming to avoid GCPs establishment, taking advantage of a real time positioning service, where differential corrections are sent from a network of Reference stations directly to the UAS.

The increased development of computer vision technology combined with the increased availability of innovative platforms with ultra-high-resolution sensors, has generated new opportunities and fields for investigation in the engineering geology domain in general and landslide identification and characterization in particular. During the last decade, the so-called Unmanned Aerial Vehicles (UAVs) have been evaluated for diverse applications such as 3D terrain analysis, slope stability, mass movement hazard and risk management. Their advantages of detailed data acquisition at a low cost and effective performance identifies them as leading platforms for site-specific 3D modelling. In this study, the proposed methodology has been developed based on Object-Based Image Analysis (OBIA) and fusion of multivariate data resulted from UAV photogrammetry processing in order to take full advantage of the produced data. Two landslide case studies within the territory of Greece, with different geological and geomorphological characteristics, have been investigated in order to assess the developed landslide detection and characterization algorithm performance in distinct scenarios. The methodology outputs demonstrate the potential for an accurate characterization of individual landslide objects within this natural process based on ultra high-resolution data from close range photogrammetry and OBIA techniques for landslide conceptualization. This proposed study shows that UAV-based landslide modelling on the specific case sites provides a detailed characterization of local scale events in an automated sense with high adaptability on the specific case site.