High resolution digital 3D modelling of subsurface morphological structures of Koutouki Cave, Greece

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.Key words: cave, laser scanner, 3D representation, speleothems, SLAM.  Visokoločljivostno digitalno 3D modeliranje podzemeljskih morfoloških struktur v jami Koutouki, Grčija Daljinsko zaznavne tehnologije in laserji nam omogočajo raziskovanje zaprtih prostorov, kot so jame z njihovo kompleksno in edinstveno morfologijo. Za pridobivanje različno dostopnih podatkov v turistični jami Koutouki smo v študiji uporabljali ročni laserski skener. Točkovni oblak pokriva tla, stene in strop jame ter stalaktite, stalagmite in stebre, ki prispevajo k okrasju jame. Natančna postavitev točkovnega oblaka v referenčnih geografskih okvirjih daje možnost tridimenzionalnih meritev in podrobne vizualizacije struktur v podzemlju. S podrobno analizo terena smo opredelili 55 stebrov in jih uvrstili v okvir razvoja jame. Pridobljeni so bili podatki o strukturiranosti, višini vsakega stebra, obliki in prostornini tamkajšnjih siginih tvorb ter prostornini prostega jamskega prostora. Z uporabljeno metodologijo je torej mogoče podrobno in z veliko natančnostjo opredeliti geomorfološke značilnosti jame, predvideti potek speleogeneze in spremljati razvoj kraškega sistema.Ključne besede: jama, laserski skener, 3D prikaz, sigine tvorbe, SLAM

Hazard identification of the Mediterranean Temporary Mountain Pond ecosystems in Central Greece: Α Geo-environmental approach

Mediterranean Temporary Ponds (MTPs) are shallow water bodies which are characterized from a short wet period and their small size. MTPs of Europe have are under an effective protection status, as a result of their identification as a priority habitat (Annex I code 3170*) in the EU Directive 92/43/EEC (Habitats' Directive). These ponds are very delicate ecosystems regarding their hydrological and geochemical characteristics. Due to their small size, they are open to random destruction or other unpredictable dangers. Although small in size, MTPs are complex ecosystems where topography, soil, water and hydrological conditions and microorganisms are closely connected. The conservation and restoration of such ecosystems is very difficult because of their unique characteristics. The most common threats for MTPs include destruction of the hosting area through human and animal pressures, hydrological disturbance, fire and generally changes in ecological conditions resulting in an increase of competitive plants, nutrition influx, toxic contaminants and wastes, sedimentary deposit filling, exotic-invasive fauna and flora and negative effects from domesticated or hunted fauna. The study was carried out in the MTPs area of the National Forest Park of Mt. Oiti (GR2440004) and Mt. Kallidromo (GR2440006). Overall, the survey has included seven small and independent MTPs of high altitude in the areas of Mt. Oiti (Louka, Livadies, Greveno and Alikaina) and Mt. Kallidromo (Nevropolis, Mourouzos and Souvala). This study aims to present a dataset of the geo-environmental parameters in order to assess the potential hazards for these priority habitats. Furthermore, it is also worth mentioning that MTPs are unevenly studied, regarding their geological, hydrological, hydrochemical, geochemical and mineralogical characteristics and this work provides a first report on an integrated evaluation of these parameters regarding the qualitative and quantitative risk identification of the MTPs in Central Greece

Remote Sensing of Environmental Change in the Antirio Deltaic Fan Region, Western Greece

In the westernmost region of the rapidly widening Corinth rift, Greece, extensive development of roads, bridges and other human infrastructure has caused continuous environmental change over the past twenty years. River networks, the land surface and the coastal environment, have been altered, especially in the areas corresponding to deltaic fans. In this paper we use earth observation systems that have captured these environmental changes, particularly medium (Landsat TM and ETM+) and high (Quickbird) resolution satellite images, to identify environmental changes between the periods 1992, 2000, 2002, and 2005. Six pseudo-color multi-temporal images in different spectral areas were created in order to detect changes to the terrestrial and coastal environment caused mainly by direct or indirect human impact. This methodology provided new data for quantifying significant alterations in the environment on different scales. In many cases this revealed their sequence during the time of observation

p Quantification of cave geomorphological characteristics based on multi source point cloud data interoperability

Structure-from-motion photogrammetric processing and laser scanning technology have given us more tools to study environments such as caves with their complex and unique morphology. In this case study, we combine two innovative techniques to generate the complete 3D model of a show cave (Koutouki, Peania Greece) and calculate the rock thickness between the cave and the open surface. We used a Handheld Laser Scanner (HLS) for acquiring points with coordinate information covering the entire cave and an Unmanned Aerial System (UAS) for acquiring data covering the open-air surface above the cave. The absolute and exact placement of the point cloud within a geographic reference frame allow the three-dimensional measurements and detailed visualization of the subsurface structures. By processing of the multi-source data (UAS and HLS) we managed to make a quantitative analysis of the terrain. After a series of processing steps and analyses we managed to calculate with high accuracy several dimension such as the cavity vacuum, the speleothem volume, the elevation differences across the entire cave etc. The final product is a high-resolution information layer with measurements of the rock thickness between the roof of the underground karstic landform and the open-surface topography

Quantification of Deltaic Coastal Zone Change Based on Multi-Temporal High Resolution Earth Observation Techniques

A series of methodologies are described in this paper aiming to quantify the natural hazard due to the coastal changes at a deltaic fan. The coastline of Istiaia (North Evia, Greece) has been chosen for this study as several areas of accretion and erosion have been identified during the past few decades. We combined different types of datasets, extracted from high resolution panchromatic aerial photographs and traced the contemporary shoreline by high accuracy surveying with Real Time Kinematics (RTK) GPS equipment. The interpretation of all shorelines required geo-statistical analysis in a Geographical Information System. A large number of high resolution morphological sections were constructed normally to the coast, revealing erosional and depositional parts of the beach. Retreating and extension rates were calculated for each section reaching the values of 0.98 m/yr and 1.36 m/yr, respectively. The results proved to be very accurate, allowing us to expand the developed methodology by using more complete time-series of remote sensing datasets along with more frequent RTK-GPS surveying

Combined geophysical techniques for detailed groundwater flow investigation in tectonically deformed fractured rocks

In this paper we present a combination of several near surface geophysical investigation techniques with high resolution remote sensing image interpretations, in order to define the groundwater flow paths and whether they can be affected by future seismic events. A seasonal spring (Amvrakia) located at the foot of Meteora pillars near the village of Kastraki (Greece) was chosen as a test site. The Meteora conglomeratic formations crop out throughout the study area and are characterized by large discontinuities caused by post Miocene till present tectonic deformation [Ferriere et al. 2011, Royden and Papanikolaou 2011]. A network of groundwater pathways has been developed above the impermeable marls underlying the conglomeratic strata. Our research aims to define these water pathways in order to investigate and understand the exact mechanism of the spring by mapping the exposed discontinuity network with classic field mapping and remote sensing image interpretation and define their underground continuity with the contribution of near surface geophysical techniques. Five Very Low Frequency (VLF) profiles were conducted with different directions around the spring aiming to detect possible conductive zones in the conglomeratic formations that the study area consists of. Moreover, two Electrical Resistivity Tomography (ERT) sections of a total length of 140m were carried out parallel to the VLF profiles for cross-checking and verifying the geophysical information. Both techniques revealed important conductive zones (<200 Ohm m) within the conglomerate strata, which we interpret as discontinuities filled with water supplying the spring, which are quite vulnerable to displacements as the hydraulic connections between them might be easily disturbed after a future seismic event

Evaluation of Machine Learning Algorithms for Object-Based Mapping of Landslide Zones Using UAV Data

Landslides are a critical geological phenomenon with devastating and catastrophic consequences. With the recent advancements in the geoinformation domain, landslide documentation and inventorization can be achieved with automated workflows using aerial platforms such as unmanned aerial vehicles (UAVs). As a result, ultra-high-resolution datasets are available for analysis at low operational costs. In this study, different segmentation and classification approaches were utilized for object-based landslide mapping. An integrated object-based image analysis (OBIA) workflow is presented incorporating orthophotomosaics and digital surface models (DSMs) with expert-based and machine learning (ML) algorithms. For segmentation, trial and error tests and the Estimation of Scale Parameter 2 (ESP 2) tool were implemented for the evaluation of different scale parameters. For classification, machine learning algorithms (K- Nearest Neighbor, Decision Tree, and Random Forest) were assessed with the inclusion of spectral, spatial, and contextual characteristics. For the ML classification of landslide zones, 60% of the reference segments have been used for training and 40% for validation of the models. The quality metrics of Precision, Recall, and F1 were implemented to evaluate the models’ performance under the different segmentation configurations. Results highlight higher performances for landslide mapping when DSM information was integrated. Hence, the configuration of spectral and DSM layers with the RF classifier resulted in the highest classification agreement with an F1 value of 0.85

Evaluation of Machine Learning Algorithms for Object-Based Mapping of Landslide Zones Using UAV Data

Landslides are a critical geological phenomenon with devastating and catastrophic consequences. With the recent advancements in the geoinformation domain, landslide documentation and inventorization can be achieved with automated workflows using aerial platforms such as unmanned aerial vehicles (UAVs). As a result, ultra-high-resolution datasets are available for analysis at low operational costs. In this study, different segmentation and classification approaches were utilized for object-based landslide mapping. An integrated object-based image analysis (OBIA) workflow is presented incorporating orthophotomosaics and digital surface models (DSMs) with expert-based and machine learning (ML) algorithms. For segmentation, trial and error tests and the Estimation of Scale Parameter 2 (ESP 2) tool were implemented for the evaluation of different scale parameters. For classification, machine learning algorithms (K-Nearest Neighbor, Decision Tree, and Random Forest) were assessed with the inclusion of spectral, spatial, and contextual characteristics. For the ML classification of landslide zones, 60% of the reference segments have been used for training and 40% for validation of the models. The quality metrics of Precision, Recall, and F1 were implemented to evaluate the models’ performance under the different segmentation configurations. Results highlight higher performances for landslide mapping when DSM information was integrated. Hence, the configuration of spectral and DSM layers with the RF classifier resulted in the highest classification agreement with an F1 value of 0.85

Post-event surface deformation of Amyntaio slide (Greece) by complementary analysis of Remotely Piloted Airborne System imagery and SAR interferometry

International audienceThe results of structure from motion photogrammetry and SAR interferometry as complementary techniques for measuring ground deformation induced by the massive open-pit landslide in Amyntaio, Greece (June 10, 2017), is presented in this paper. This unexpected slide damaged the entire westernmost marginal area of the pit, significant number of buildings, and infrastructures of the nearby village of Anargiri. The described methodology includes the generation of a multi-temporal dataset (from Sept. 2017 to Sept. 2018) of very high-resolution surface topography (at 10 cm), based on the analysis of imagery collected by Remotely Piloted Airborne Systems (RPASs). Satellite observations involved interferometric processing of TerraSAR-X data for a complementary estimation of ground displacement rates. Height differences from consecutive aerial photography campaigns as well as space-borne measurements provided valuable information on the evolution of the deformation and its spatial characteristics during the post-event period, an important aspect for future hazard and risk considerations