Geoinformatics plays an essential role during the recovery phase of a post-earthquake situation. The aim of this paper is to present the methodology followed and the results obtained by the utilization of Unmanned Aircraft Systems (UASs) 4K-video footage processing and the automation of geo-information methods targeted at both monitoring the demolition process and mapping the demolished buildings. The field campaigns took place on the traditional settlement of Vrisa (Lesvos, Greece), which was heavily damaged by a strong earthquake (Mw=6.3) on June 12th, 2017. For this purpose, a flight campaign took place on 3rd February 2019 for collecting aerial 4K video footage using an Unmanned Aircraft. The Structure from Motion (SfM) method was applied on frames which derived from the 4K video footage, for producing accurate and very detailed 3D point clouds, as well as the Digital Surface Model (DSM) of the building stock of the Vrisa traditional settlement, twenty months after the earthquake. This dataset has been compared with the corresponding one which derived from 25th July 2017, a few days after the earthquake. Two algorithms have been developed for detecting the demolished buildings of the affected area, based on the DSMs and 3D point clouds, correspondingly. The results obtained have been tested through field studies and demonstrate that this methodology is feasible and effective in building demolition detection, giving very accurate results (97%) and, in parallel, is easily applicable and suit well for rapid demolition mapping during the recovery phase of a post-earthquake scenario. The significant advantage of the proposed methodology is its ability to provide reliable results in a very low cost and time-efficient way and to serve all stakeholders and national and local organizations that are responsible for post-earthquake management.

Geosites are an important part of geoheritage, thus their detailed mapping is crucial for their management, protection and promotion processes. However, there is no specific approach to three-dimensional (3D) mapping of geosites and a full investigation is required, considering the current advances in the science of Geoinformatics and the need for setting up an integrated system that will suggest a suitable way of mapping areas of geological significance. The main purpose of this study is to explore new approaches to the 3D mapping of geosites, where the unmanned aerial vehicles’ (UAVs) flight planning is based on the digital elevation model (DEM). The case study that is being examined is the tectonic window of Mount Olympus, located in the southeast of Lesvos island, Greece. In this paper, a methodology has been developed to create flight plans for geosite 3D mapping. This methodology consists of three main stages: (a) flight planning based on SRTM-DEM, (b) data acquisition and image-based 3D modelling, and (c) comparison (flight plans and results). A semi-automated algorithm was developed for designing the flights, taking into account the topography of the mapped area (slope, aspect, elevation) and the final cartographic derivatives. The flight plans were compared with each other in levels of data collection, flight characteristics and their results. The results of this study are dense point clouds, DEMs and orthophotomaps. The algorithms that have been used for the comparison of point clouds were (I) surface density, (II) number of neighbours (NN), and (III) roughness and surface profile. The conclusion drawn from this study is that the DEM is a valuable source of information that can be used in designing flight plans specially shaped on the topography of each geosite.

Technological progress in Virtual Reality (VR) and Unmanned Aerial Systems (UASs) offers great advantages in the field of cartography and particularly in the geovisualization of spatial data. This paper investigates the correlation between UAS flight characteristics for data acquisition and the quality of the derived maps and 3D models of geological monuments for VR geovisualization in different scales and timeframes. In this study, we develop a methodology for mapping geoheritage monuments based on different cartographic scales. Each cartographic scale results in diverse orthophotomaps and 3D models. All orthophotomaps and 3D models provide an optimal geovisualization, combining UAS and VR technologies and thus contributing to the multitemporal 3D geovisualization of geological heritage on different cartographic scales. The study area selected was a fossilite ferrous site located in Lesvos Geopark, UNESCO. The study area contains a fossil site surrounding various findings. The three distinct scales that occur are based on the object depicted: (i) the fossilite ferrous site (1:120), (ii) the fossil root system (1:20), and (iii) individual fossils (≥1:10). The methodology followed in the present research consists of three main sections: (a) scale-variant UAS data acquisition, (b) data processing and results (2D–3D maps and models), and (c) 3D geovisualization to VR integration. Each different mapping scale determines the UAS data acquisition parameters (flight pattern, camera orientation and inclination, height of flight) and defines the resolution of the 3D models to be embedded in the VR environment. Due to the intense excavation of the study area, the location was spatiotemporally monitored on the cartographic scale of 1:120. For the continuous monitoring of the study area, four different UASs were also used. Each of them was programmed to fly and acquire images with a constant ground sampling distance (GSD). The data were processed by image-based 3D modeling and computer vision algorithms from which the 3D models and orthophotomaps were created and used in the VR environment. As a result, a VR application visualizing multitemporal data of geoheritage monuments across three cartographic scales was developed.

The purpose of this paper was to study the influence of cartographic scale and flight design on data acquisition using unmanned aerial systems (UASs) to create augmented reality 3D geovisualization of geosites. The relationship between geographical and cartographic scales, the spatial resolution of UAS-acquired images, along with their relationship with the produced 3D models of geosites, were investigated. Additionally, the lighting of the produced 3D models was examined as a key visual variable in the 3D space. Furthermore, the adaptation of the 360° panoramas as environmental lighting parameters was considered. The geosite selected as a case study was the gorge of the river Voulgaris in the western part of the island of Lesvos, which is located in the northeastern part of the Aegean Sea in Greece. The methodology applied consisted of four pillars: (i) scale-variant flight planning, (ii) data acquisition, (iii) data processing, (iv) AR, 3D geovisualization. Based on the geographic and cartographic scales, the flight design calculates the most appropriate flight parameters (height, speed, and image overlaps) to achieve the desired spatial resolution (3 cm) capable of illustrating all the scale-variant details of the geosite when mapped in 3D. High-resolution oblique aerial images and 360° panoramic aerial images were acquired using scale-variant flight plans. The data were processed using image processing algorithms to produce 3D models and create mosaic panoramas. The 3D geovisualization of the geosite selected was created using the textured 3D model produced from the aerial images. The panoramic images were converted to high-dynamic-range image (HDRI) panoramas and used as a background to the 3D model. The geovisualization was transferred and displayed in the virtual space where the panoramas were used as a light source, thus enlightening the model. Data acquisition and flight planning were crucial scale-variant steps in the 3D geovisualization. These two processes comprised the most important factors in 3D geovisualization creation embedded in the virtual space as they designated the geometry of the 3D model. The use of panoramas as the illumination parameter of an outdoor 3D scene of a geosite contributed significantly to its photorealistic performance into the 3D augmented reality and virtual space.

This study aims to create virtual reality (VR) geovisualizations using 3D point clouds obtained from airborne LiDAR technology. These visualizations were used to map the current state of river channels and tributaries in the Thessalian Plain, Greece, following severe flooding in the summer of 2023. The study area examined in this paper is the embankments enclosing the tributaries of the Pineios River in the Thessalian Plain region, specifically between the cities of Karditsa and Trikala in mainland Greece. This area was significantly affected in the summer of 2023 when flooding the region’s rivers destroyed urban elements and crops. The extent of the impact across the entire Thessalian Plain made managing the event highly challenging to the authorities. High-resolution 3D mapping and VR geovisualization of the embarkments encasing the main rivers and the tributaries of the Thessalian Plain essentially provides information for planning the area’s restoration processes and designing prevention and mitigation measures for similar disasters. The proposed methodology consists of four stages. The first and second stages of the methodology present the design of the data acquisition process with airborne LiDAR, aiming at the high-resolution 3D mapping of the sites. The third stage focuses on data processing, cloud point classification, and thematic information creation. The fourth stage is focused on developing the VR application. The VR application will allow users to immerse themselves in the study area, observe, and interact with the existing state of the embankments in high resolution. Additionally, users can interact with the 3D point cloud, where thematic information is displayed describing the classification of the 3D cloud, the altitude, and the RGB color. Additional thematic information in vector form, providing qualitative characteristics, is also illustrated in the virtual space. Furthermore, six different scenarios were visualized in the 3D space using a VR app. Visualizing these 3D scenarios using digital twins of the current antiflood infrastructure provides scenarios of floods at varying water levels. This study aims to explore the efficient visualization of thematic information in 3D virtual space. The goal is to provide an innovative VR tool for managing the impact on anthropogenic infrastructures, livestock, and the ecological capital of various scenarios of a catastrophic flood.

The recovery phase following an earthquake event is essential for urban areas with a significant number of damaged buildings. A lot of changes can take place in such a landscape within the buildings’ footprints, such as total or partial collapses, debris removal and reconstruction. Remote sensing data and methodologies can considerably contribute to site monitoring. The main objective of this paper is the change detection of the building stock in the settlement of Vrissa on Lesvos Island during the recovery phase after the catastrophic earthquake of 12 June 2017, through the analysis and processing of UAV (unmanned aerial vehicle) images and the application of Artificial Neural Networks (ANNs). More specifically, change detection of the settlement’s building stock by applying an ANN on Gray-Level Co-occurrence Matrix (GLCM) texture features of orthophotomaps acquired by UAVs was performed. For the training of the ANN, a number of GLCM texture features were defined as the independent variable, while the existence or not of structural changes in the buildings were defined as the dependent variable, assigning, respectively, the values 1 or 0 (binary classification). The ANN was trained based on the Levenberg–Marquardt algorithm, and its ability to detect changes was evaluated on the basis of the buildings’ condition, as derived from the binary classification. In conclusion, the GLCM texture feature changes in conjunction with the ANN can provide satisfactory results in predicting the structural changes of buildings with an accuracy of almost 92%.