Rapid post-disaster infrastructure damage characterisation enabled by remote sensing and deep learning technologies -- a tiered approach

Critical infrastructure, such as transport networks and bridges, are systematically targeted during wars and suffer damage during extensive natural disasters because it is vital for enabling connectivity and transportation of people and goods, and hence, underpins national and international economic growth. Mass destruction of transport assets, in conjunction with minimal or no accessibility in the wake of natural and anthropogenic disasters, prevents us from delivering rapid recovery and adaptation. As a result, systemic operability is drastically reduced, leading to low levels of resilience. Thus, there is a need for rapid assessment of its condition to allow for informed decision-making for restoration prioritisation. A solution to this challenge is to use technology that enables stand-off observations. Nevertheless, no methods exist for automated characterisation of damage at multiple scales, i.e. regional (e.g., network), asset (e.g., bridges), and structural (e.g., road pavement) scales. We propose a methodology based on an integrated, multi-scale tiered approach to fill this capability gap. In doing so, we demonstrate how automated damage characterisation can be enabled by fit-for-purpose digital technologies. Next, the methodology is applied and validated to a case study in Ukraine that includes 17 bridges, damaged by human targeted interventions. From regional to component scale, we deploy technology to integrate assessments using Sentinel-1 SAR images, crowdsourced information, and high-resolution images for deep learning to facilitate automatic damage detection and characterisation. For the first time, the interferometric coherence difference and semantic segmentation of images were deployed in a tiered multi-scale approach to improve the reliability of damage characterisations at different scales

GIS-Based Assessment of Hybrid Pumped Hydro Storage as a Potential Solution for the Clean Energy Transition: The Case of the Kardia Lignite Mine, Western Greece

Planned decommissioning of coal-fired plants in Europe requires innovative technical and economic strategies to support coal regions on their path towards a climate-resilient future. The repurposing of open pit mines into hybrid pumped hydro power storage (HPHS) of excess energy from the electric grid, and renewable sources will contribute to the EU Green Deal, increase the economic value, stabilize the regional job market and contribute to the EU energy supply security. This study aims to present a preliminary phase of a geospatial workflow used to evaluate land suitability by implementing a multi-criteria decision making (MCDM) technique with an advanced geographic information system (GIS) in the context of an interdisciplinary feasibility study on HPHS in the Kardia lignite open pit mine (Western Macedonia, Greece). The introduced geospatial analysis is based on the utilization of the constraints and ranking criteria within the boundaries of the abandoned mine regarding specific topographic and proximity criteria. The applied criteria were selected from the literature, while for their weights, the experts’ judgement was introduced by implementing the analytic hierarchy process (AHP), in the framework of the ATLANTIS research program. According to the results, seven regions were recognized as suitable, with a potential energy storage capacity from 1.09 to 5.16 GWh. Particularly, the present study’s results reveal that 9.27% (212,884 m2) of the area had a very low suitability, 15.83% (363,599 m2) had a low suitability, 23.99% (550,998 m2) had a moderate suitability, 24.99% (573,813 m2) had a high suitability, and 25.92% (595,125 m2) had a very high suitability for the construction of the upper reservoir. The proposed semi-automatic geospatial workflow introduces an innovative tool that can be applied to open pit mines globally to identify the optimum design for an HPHS system depending on the existing lower reservoir

GIS-Based Subsurface Analysis and 3D Geological Modeling as a Tool for Combined Conventional Mining and In-Situ Coal Conversion: The Case of Kardia Lignite Mine, Western Greece

The development of three-dimensional geological models has proven to be critical for conceptualizing complex subsurface environments. This is crucial for mining areas due to their various hazards and unstable conditions. Furthermore, three-dimensional (3D) models can be the initial step for the development of numerical models in order to support critical decisions and sustainable mining planning. This paper illustrates the results and the development phases of a 3D geological model within the boundaries of the Kardia lignite deposit in western Macedonia, Greece. It also highlights the usefulness of a Geographic Information System (GIS) methodology in the subsurface geological and hydrogeological analysis regarding the Underground Coal Gasification (UCG) methodology. In addition, the work focuses on the integrated geospatial framework that was developed to support the Coal-to-Liquids Supply Chain (CLSC) integration in unfavorable geological settings. A 3D subsurface geological model of the study area was developed to identify a suitable area for in situ coal conversion and UCG considering criteria related to specific coal thickness and depth. In this context, the suggested integrated geomodelling workflow can positively contribute to the implementation of conventional and innovative mining, saving time and reducing the cost to improve the quality of information needed to support decisions related to UCG implementation

Correlation of Ground Deformation Induced by the 6 February 2023 M7.8 and M7.5 Earthquakes in Turkey Inferred by Sentinel-2 and Critical Exposure in Gaziantep and Kahramanmaraş Cities

On 6 February 2023, an M7.8 devastating earthquake started rupturing the East Anatolian fault system in Turkey, resulting in intense shaking that lasted over a minute. A second earthquake of magnitude 7.5 struck near the city of Elbistan a few hours later. Both of these events are associated with the East Anatolian fault system. The earthquake sequence caused widespread damage and collapse of structures in densely populated areas throughout the Southern Turkey and Northern Syria regions and a very large number of human losses. This study focuses on the correlation of the ground deformation with the critical exposure of the infrastructures of Gaziantep and Kahramanmaraş cities. The estimation of the ground deformation of the affected area is achieved with the use of Copernicus Sentinel-2 products and the Normalized Cross Correlation algorithm (NCC) of image matching. The results of the East–West component show that specific sections of the region moved towards the East direction, reaching displacement measurements of 5.4 m, while other sections moved towards the West direction, reaching displacement measurements of 2.8 m. The results of the North–South component show that almost the whole affected area moved towards the North direction, with specific areas reaching displacements of 5.5 m, and a few exemptions, as some areas moved towards the South direction, with displacements reaching even 6.9 m. Regarding the cities of Kahramanmaraş and Gaziantep, their estimated movement direction is North-West and North-East, respectively, and is consistent with the movements of the Arabian and Anatolian Plates in which they are located. Important infrastructures of the study areas (education, museums, libraries, hospitals, monuments, airports, roads and railways) are superimposed on the findings, enabling us to detect the critical exposure rapidly

Assessing Post-Fire Effects on Soil Loss Combining Burn Severity and Advanced Erosion Modeling in Malesina, Central Greece

Earth’s ecosystems are extremely valuable to humanity, playing a key role ecologically, economically, and socially. Wildfires constitute a significant threat to the environment, especially in vulnerable ecosystems, such as those that are commonly found in the Mediterranean. Due to their strong impact on the environment, they provide a crucial factor in managing ecosystems behavior, causing dramatic modifications to land surface processes dynamics leading to land degradation. The soil erosion phenomenon downgrades soil quality in ecosystems and reduces land productivity. Thus, it is imperative to implement advanced erosion prediction models to assess fire effects on soil characteristics. This study focuses on examining the wildfire case that burned 30 km2 in Malesina of Central Greece in 2014. The added value of remote sensing today, such as the high accuracy of satellite data, has contributed to visualizing the burned area concerning the severity of the event. Additional data from local weather stations were used to quantify soil loss on a seasonal basis using RUSLE modeling before and after the wildfire. Results of this study revealed that there is a remarkable variety of high soil loss values, especially in winter periods. More particularly, there was a 30% soil loss rise one year after the wildfire, while five years after the event, an almost double reduction was observed. In specific areas with high soil erosion values, infrastructure works were carried out validating the applied methodology. The approach adopted in this study underlines the significance of using remote sensing and geoinformation techniques to assess the post-fire effects of identifying vulnerable areas based on soil erosion parameters on a local scale

The Volcanic Relief within the Kos-Nisyros-Tilos Tectonic Graben at the Eastern Edge of the Aegean Volcanic Arc, Greece and Geohazard Implications

The active Kos-Nisyros-Tilos volcanic field is located in the eastern sector of the Aegean Volcanic Arc resulting from the subduction of the African plate beneath the Aegean plate. The volcanic activity is developed since Middle Pleistocene and it occurs within a tectonic graben with several volcanic outcrops both onshore and offshore. Data obtained from previous offshore geophysical surveys and ROV exploration, combined with geospatial techniques have been used to construct synthetic maps of the broader submarine area. The volcanic relief is analyzed from the base of the volcanic structures offshore to their summits onshore reaching 1373 m of height and their volumes have been computed with 24.26 km(3) for Nisyros Island and a total volume of 54.42 km(3) for the entire volcanic area. The volcanic structures are distinguished in: (1) volcanic cones at the islands of Nisyros (older strato-volcano), Pergousa, Yali and Strongyli, (2) volcanic domes at the islands of Pachia, East Kondeliousa and Nisyros (younger Prophitis Ilias domes), (3) submarine volcanic calderas (Avyssos and Kefalos). Submarine volcanic debris avalanches have been also described south of Nisyros and undulating features at the eastern Kefalos bay. Submarine canyons and channels are developed along the Kos southern margin contrary to the Tilos margin. Ground truth campaigns with submarine vessels and ROVs have verified the previous analysis in several submarine volcanic sites. The geohazards of the area comprise: (1) seismic hazard, both due to the activation of major marginal faults and minor intra-volcanic faults, (2) volcanic hazard, related to the recent volcanic structures and long term iconic eruptions related to the deep submarine calderas, (3) tsunami hazard, related to the seismic hazard as well as to the numerous unstable submarine slopes with potential of gravity sliding

Detecting subsidence spatial risk distribution of ground deformation induced by urban hidden streams

A plethora of subsidence events has been repeatedly reported in high density urban environments. The purpose of this study is to introduce specific areas around the riverbeds of the urban hidden streams in the city of Athens presenting high risk in terms of ground subsidence. The study area comprises the centre of Athens and more specifically the Municipalities of Athens, Tavros, Kallithea, Daphne, Hymettus and Ilisia where the ancient rivers of Ilissos and Eridanus naturally flow through a heavily populated city. It wasn’t until the early 1960s that the two rivers were completely channelled and partly covered along their course during the urbanization process which allowed the construction of the modern boulevards, roads, recreation and open space areas as long as parking areas. The route of today's concealed rivers and streams poses a serious risk of potential ground subsidence concerning the erosion of streams’ bank permeable soil formations. Following this approach, areas of influence (buffer zones) were determined on each side of the subterranean urban rivers Ilissos and Eridanus. In particular, an inventory of literature and references such as, historical maps and drawings, technical studies as well as modern topographic and geological maps, land use/land cover maps were created and collected in a geospatial database. It is worth mentioning that a main part of this study was the utilization and analysis of satellite radar data of the time period 2012–2016, in order to detect vertical displacements (mm/year) and correlate these with the above-mentioned spatial data of Athens city

Geospatial Intelligence and Machine Learning Technique for Urban Mapping in Coastal Regions of South Aegean Volcanic Arc Islands

Coastal environments are globally recognized for their spectacular morphological characteristics as well as economic opportunities, such as fisheries and tourism industries. However, climate change, growth in tourism, and constant coastal urban sprawl in some places result in ever-increasing risk in the islands of the South Aegean Volcanic Arc (SAVA), necessitating thoughtful planning and decision making. GEOspatial INTelligence (GEOINT) can play a crucial role in the depiction and analysis of the natural and human surroundings, offering valuable information regarding the identification of vulnerable areas and the forecasting of urbanization rates. This work focuses on the delineation of the coastal zone boundaries, semi-automatization of Satellite-Derived Bathymetry (SDB), and urban mapping using a machine learning algorithm. The developed methodology has been implemented on the islands of Thira (Santorini island complex) and Milos. This study attempts to identify inaccuracies in existing open-source datasets, such as the European Settlement Map (ESM), as a result of the unique combination of the architectural style and bare-soil characteristics of the study areas. During the period 2016–2021, the average accuracy of the developed methodology for urban mapping in terms of the kappa index was 80.15% on Thira and 88.35% on Milos. The results showed that the average urbanization expansion on specified settlements was greater than 22% for both case studies. Ultimately, the findings of this study could contribute to the effective and holistic management of similar coastal regions in the context of climate change adaptation, mitigation strategies, and multi-hazard assessment

Geospatial Intelligence and Machine Learning Technique for Urban Mapping in Coastal Regions of South Aegean Volcanic Arc Islands

Coastal environments are globally recognized for their spectacular morphological characteristics as well as economic opportunities, such as fisheries and tourism industries. However, climate change, growth in tourism, and constant coastal urban sprawl in some places result in ever-increasing risk in the islands of the South Aegean Volcanic Arc (SAVA), necessitating thoughtful planning and decision making. GEOspatial INTelligence (GEOINT) can play a crucial role in the depiction and analysis of the natural and human surroundings, offering valuable information regarding the identification of vulnerable areas and the forecasting of urbanization rates. This work focuses on the delineation of the coastal zone boundaries, semi-automatization of Satellite-Derived Bathymetry (SDB), and urban mapping using a machine learning algorithm. The developed methodology has been implemented on the islands of Thira (Santorini island complex) and Milos. This study attempts to identify inaccuracies in existing open-source datasets, such as the European Settlement Map (ESM), as a result of the unique combination of the architectural style and bare-soil characteristics of the study areas. During the period 2016–2021, the average accuracy of the developed methodology for urban mapping in terms of the kappa index was 80.15% on Thira and 88.35% on Milos. The results showed that the average urbanization expansion on specified settlements was greater than 22% for both case studies. Ultimately, the findings of this study could contribute to the effective and holistic management of similar coastal regions in the context of climate change adaptation, mitigation strategies, and multi-hazard assessment