The escalating frequency and severity of extreme weather events, induced by climate change, pose significant threats to global societies, economies, and ecosystems. Europe, and more specifically the Mediterranean area, has witnessed a surge in natural disasters resulting in substantial human casualties and economic losses. Despite advancements in disaster risk management, inadequate investment in early warning and detection systems have led to prolonged, costly, and frequent emergency responses, straining resources.

The UNICORN project, started in October 2024, focuses on the development of Copernicus emergency applications, using Earth Observation technologies and data to address the increasing frequency and intensity of extreme events (fires, floods) and geohazards (volcanoes) and their impact on society, the economy and the environment. UNICORN develops tools and applications for early warning, forecasting, and hazard monitoring that enable a resilient society, better-informed emergency services, and effective short-term recovery. It proposes innovative solutions for local authorities, policy makers, citizens, and industries which will increase their preparedness for extreme events and geohazards. UNICORN's approach involves creating state-of-the-art, scalable and transferable services tailored to user needs, pushing technological boundaries for precise, timely, and actionable results from data and knowledge. UNICORN is based on four use cases from different European regions, hazards, target stakeholders, and technologies, through an end user validation method to build a resilient European landscape.

UNICORN's foundation lays on the development of four strategically selected Copernicus emergency applications corresponding in 4 use cases which incorporate specific areas, regions, and countries from the Mediterranean area of Europe that has a long history of natural hazards and extreme events. These use cases through which the applications are implemented, monitored and validated in real world conditions are diverse due to the scale of operation (local, regional, sub-national), the hazards, the type of engaged stakeholders and the applied technologies:

• Flood forecasting integrating Copernicus data and weather forecast fusion - Attica region, Greece.
• Copernicus-based wildfire early detection, mapping and nowcasting - Corsica Island, France.
• High resolution fire danger forecasting - Northwestern Spain and Northern Portugal.
• Lava flow emergency management tool based on Copernicus data merged with numerical modelling - Sicily Island, Italy.

Acknowledgement: "This work has been supported by the European research project UNICORN. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 101180172. This article reflects only the authors’ views and the EU Agency for the Space Programme (EUSPA) and the European Commission are not responsible for any use that may be made of the information it contains."

How to cite: Kontoes, C., Kaskara, M., and Pissaridi, K.: Copernicus emergency Applications for Resilience addressing businesses’ needs and policy making, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1293, https://doi.org/10.5194/egusphere-egu25-1293, 2025.

Our research institute has been promoting the national disaster monitoring and recovery support projects funded by Japanese government. Final goal of these projects is to establish the resilient social system in both before and after phase of national hazards. In this project, integrated system called "One stop system for disaster management" is under development, which enables us the optimum target observation and disaster situation assessment. With the rapid development of the small satellite industry, the use of remote sensing is dramatically changing in disaster monitoring. One of the key concepts is satellite constellation within or beyond single satellite series. Among this aspect, Japanese flagship satellite, ALOS-2 and -4, and small satellites from Japanese companies, are working together for effective observations under "One stop system". The effectiveness of this cooperative observation was evaluated in natural disasters caused by the Noto Peninsula earthquake (Jan. 2024), and other typical large-scale flooding in 2024. This paper summarizes the past research results and discusses future developments.

How to cite: Rokugawa, S., Taguchi, H., Sakai, N., and Boriigin, H.: Disaster monitoring initiative in Japan by the earth observation of multi satellite-series constellation., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8691, https://doi.org/10.5194/egusphere-egu25-8691, 2025.

In Italy, "Telecommunications, Earth Observation, and Navigation" (TLC/EO/NAV) assets are currently exploited to realize services and applications (the so-called downstream) providing benefits to citizens and public institutions, translating space technology investments into significant social and economic gains. Among the downstream satellite-based services and products of most interest for the Italian institutions, there was the support to civil protection and environmental safeguard from natural and anthropogenic hazards.

In this context, the Italian Space Agency (ASI) promotes the development of downstream services through the "Innovation for Downstream Preparation" (I4DP) program. I4DP foresees an active engagement of the user community in the demonstration projects since the user requirement consolidation phase, until the testing of the developed technological solutions in real-world scenarios. The I4DP_SCIENCE stream, addressed to the Scientific User Community (i.e., Italian Universities and Public Research Bodies) and designed to develop joint projects with ASI, is aimed at demonstrating the usefulness of novel methods and algorithms in supporting applications of user's interest regarding topics of national relevance (e.g., defined by the National Copernicus User Forum), and/or international agendas (e.g., the UN Sustainable Development Goals). The I4DP_SCIENCE program has been developed through the issue of two Calls for Ideas, focused on the themes of "Sustainable Cities" and "Agriculture and Sustainable Use of Water Resources" [1]. Among the selected projects, three address the theme of natural and anthropogenic hazard assessment and mitigation: GEORES, SatellOmic, and GRAW. GEORES (Geospatial Application to Support the Improvement of Environmental Sustainability and Resilience to Climate Change in Urban Areas, Agreement n. 2023-42-HH.0) [2], led by the University of Bari and CNR-IREA, aims at developing a geospatial application to improve environmental sustainability in urban areas, through a multi-risk platform, with the synergistic use of EO data, machine learning techniques, and artificial intelligence. SatellOmic (Integration of Satellite and Metagenomic Systems for the Monitoring and Safeguarding of Water Basins, Agreement n. 2023-36-HH.0) [3], led by the Istituto Superiore di Sanità (ISS) and the Scuola di Ingegneria Aerospaziale (SIA) of Sapienza University of Rome, aims at combining EO-based products with metagenomics analyses, to evaluate and monitor the quality of inland and coastal waters, assessing the presence of oil spills or algal blooms. GRAW (Geomatics for Resilience Against Water Scarcity, Agreement n. 2023-52-HH.0) [4], led by Sapienza University of Rome, aims at developing specific approaches and algorithms to monitor and forecast hazards due to hydrological and agricultural drought. The paper outlines how the three I4DP_SCIENCE projects are addressing natural hazard and risk using EO and geospatial technologies and accounting for the specific user requirements and needs.

[1] D. Tapete et al. (2024) The Italian Space Agency’s programs of scientific downstream applications for water resources and hydraulic hazard management. 14° Workshop tematico di Telerilevamento “Telerilevamento applicato alla gestione delle risorse idriche”, ENEA, Bologna, Italy, pp. 5-9. https://www.eventi.enea.it/images/presentazioni2024/2024_06_06_telerilevamento/Abstract_AIT2024_def.pdf

[2] R. Lafortezza et al. (2024), doi: 10.1109/IGARSS53475.2024.10642728.

[3] E. D’Ugo et al. (2024), doi: 10.1109/IGARSS53475.2024.10642700.

[4] F. Bocchino et al. (2024), doi: 10.1109/IGARSS53475.2024.10641154

How to cite: Ursi, A., Tapete, D., Sacco, P., Virelli, M., Coletta, A., Guarini, R., Licciardi, G., Longo, F., Siciliani de Cumis, M., and Zoffoli, S.: Italian Space Agency's Program for the Development of Novel EO-based Scientific Products for Natural Hazards Applications, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10904, https://doi.org/10.5194/egusphere-egu25-10904, 2025.

Remote sensing data is a key tool in disaster response and preparedness. For fire detection and monitoring, however, public satellite missions have significant coverage gaps in the afternoon. As most fires start in the afternoon, however, many can burn potentially undetected for a long period of time. 

This is why OroraTech is building the Forest Constellation to close this afternoon gap. With two successful launches completed and an additional 9 satellites scheduled to be in orbit by the time of EGU 25, the constellation will achieve a 12-hour revisit time for any location on Earth focusing on late afternoon orbits. FOREST-2, the current sensor generation in orbit covers a swath of 410km in a single scan at a resolution of 200m per pixel. Future launches will further enhance the system, eventually enabling a global revisit time of just 30 minutes. This increased temporal and spatial coverage will allow for significantly earlier fire detection. 

The fire detection is run on board on a GPU to keep latencies minimal. This is because downlink bottlenecks are easier to circumvent with bites of fire location files then GB size satellite images. Otherwise, the file transfer of a satellite image to the ground would introduce a significant bottleneck. To cut down communication latencies further, we rely on a dedicated ground station network with OroraTech’s Fire Link technology. With the upcoming satellite launches, we therefore enable fire detection within minutes after the satellite overpass. At EGU, we aim to showcase current and future capabilities of our constellation to detect fires with first impressions from upcoming launches.

How to cite: Laux, D., Wahbe, J., Liesenhoff, L., Bereczky, M., Spichtinger, A., Würl, K., Gottfriedsen, J., and Langer, M.: Near-Real Time Active Fire Detection from Space with the Forest-Constellation, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18898, https://doi.org/10.5194/egusphere-egu25-18898, 2025.

Coastal erosion and accretion remain critical challenges for sustainable coastal zone management, particularly in regions facing intensified environmental changes and human interventions. With rising sea levels projected to exacerbate these challenges, this study investigates the shoreline dynamics of Ghana’s eastern coastline over a nearly four-decade period. Using automated shoreline extraction via CoastSat and change analysis with the Digital Shoreline Analysis System (DSAS), the research quantified erosion and accretion rates and revealed significant spatial variability across the study area.

To facilitate a focused analysis, the coastline was divided into three zones (Zone A, Zone B, and Zone C), categorized based on geomorphological characteristics and coastal management practices. Three statistical models—Linear Regression Rate (LRR), End Point Rate (EPR), and Net Shoreline Movement (NSM)—were employed to quantify shoreline changes. Zone A exhibited a balance of erosion and accretion, with rates ranging from −10.5 m/year to +10.8 m/year (EPR) and −10.4 m/year to +12.0 m/year (LRR). Zone B showed relatively stable dynamics, with EPR values from −3.1 m/year to +4.1 m/year and LRR values from −1.6 m/year to +5.0 m/year. Zone C displayed the most pronounced variability, with erosion rates peaking at −30.5 m/year (EPR) and −28.7 m/year (LRR), alongside accretion rates up to +9.7 m/year (LRR) and +8.8 m/year (EPR). Cumulative shoreline movements (NSM) averaged 15.2 m, 20.42 m, and 33.5 m for Zones A, B, and C, respectively.

This study underscores the value of remote sensing and GIS in monitoring shoreline dynamics. By automating shoreline extraction with CoastSat, human error is minimized, and reproducibility is enhanced. The findings provide actionable insights into shoreline management and highlight the potential of these techniques for broader applications in coastal monitoring. This approach can empower stakeholders to devise effective, data-driven strategies for resilience against coastal erosion and sustainable coastal management practices.

How to cite: Asare-Bediako, B. and Boateng, C.: Spatiotemporal Analysis of Coastal Erosion and Accretion Patterns in the Keta Region, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-376, https://doi.org/10.5194/egusphere-egu25-376, 2025.

Extreme meteorological events, such as heat and drought, can induce significant damage to vegetation and ecosystems. The frequency and intensity of extreme events are subject to change due to anthropogenic global warming. It is therefore crucial to quantify the impact of such events for better preparedness.

Here, we focus on forest damage in Europe, defined as negative anomalies of the normalized difference vegetation index (NDVI, a measure of vegetation greenness). Compound drought and heat wave events are known to trigger low NDVI events in summer. A dry summer combined with moist conditions during the previous autumn can also have a negative impact. Hence, the goal of our study is to find the most relevant predictors for forest damage in Europe at monthly to annual timescales. Using a Random Forest approach, we pinpoint hydro-meteorological conditions associated with low NDVI events. We train the model using remote sensing observations of NDVI (from the Advanced Very High-Resolution Radiometers, AVHRR) as the predictand, and a range of variables from the ERA5 and ERA5-Land reanalysis as hydro-meteorological predictors.

We provide an automated procedure with strong predictive performance for identifying low-greenness events during summer based on prior hydro-meteorological conditions. The most essential preceding periods and variables are location and forest-type dependent. Notably, warm and dry conditions in spring and early summer emerge as essential predictors. Additionally, we emphasize a longer-term relationship between hydro-meteorological conditions and forest damage. For instance, low dewpoint temperatures one year before the studied summer impact broad-leaved forests, while soil moisture during the preceding autumn influences low greenness events in coniferous forests, albeit with location-specific variations.

How to cite: Rivoire, P., Dupuis, S., Guisan, A., Vittoz, P., and Domeisen, D.: Hydro-Meteorological Drivers of Forest Damage over Europe, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16296, https://doi.org/10.5194/egusphere-egu25-16296, 2025.

This study focuses on the fifth eruption of the Sundhnúkur volcano on the Reykjanes Peninsula, Iceland, which occurred between May 29 and June 22, 2024. Multi-satellite imaging techniques were used to analyze the activity of this volcano, which erupted a total of seven times between 2023 and 2024. Multiple Landsat-9 satellite images were acquired before and after the eruption, and Support Vector Machine (SVM) techniques were applied to calculate changes in the volcanic plateau. In addition, a series of Sentinel-1 satellite images was used to detect coherence changes during the eruption period and compared with the expanded volcanic plateau derived from Landsat-9 to determine the area of change. The results show that the fifth eruption was characterized by a large number of lava flows and significant volcanic plateau expansion in the early stages, with relatively little lava eruption in the later stages. This study may contribute to the calculation of changes caused by volcanic eruptions in the Icelandic region and could potentially help determine the affected area using a combination of different satellite images. This approach might be useful for future volcanic activity monitoring and disaster management.

Acknowledgment: This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. NRF–2023R1A2C1007742).

How to cite: Kim, B. and Lee, C.-W.: Analysis of the May 2024 Iceland Volcano Eruption Using Coherence Change Detection Techniques, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14167, https://doi.org/10.5194/egusphere-egu25-14167, 2025.

Remotely sensed nighttime lights (NTL) are widely used as a proxy for human activity. A key application is assessing disaster impacts, but its potential has been limited by uncertainties in estimating baseline NTL intensity (the counterfactual without disasters) and challenges in isolating disaster impacts from other factors influencing NTL variation. To address these challenges, we used a synthetic control modeling framework with daily NTL images from NASA's Black Marble VIIRS product suite. We enhanced the traditional model by optimizing donor selection with the Dynamic Time Warping algorithm and incorporating random forest regression to better capture target-donor relationships. Testing on 20 severe disasters across diverse contexts, our model outperformed existing methods, achieving a correlation coefficient of 0.94 and a covariate difference of just 0.47%. It also excelled at detecting low-intensity and short-term disaster impacts often missed by other methods. The resulting metrics—impact duration, intensity, and severity—revealed significant regional variations in disaster resilience and coping capacity. This model provides valuable insights for disaster relief and supports broader climate resilience and sustainability efforts.

How to cite: Mu, T., Zheng, Q., and He, S. Y.: Robust disaster impact assessment with synthetic control modeling framework and daily nighttime light time series images, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2264, https://doi.org/10.5194/egusphere-egu25-2264, 2025.

Mapping of neotectonic faults is critical to the scientific study of earthquake processes and surface rupture hazard analysis. Geologists commonly map fault traces from remote sensing datasets by interpreting tectonic landforms formed from past earthquakes. However, the evidence for faulting is not always straightforward to observe and interpret. Even experts map faults differently. We seek to understand the variability in fault trace mapping by mappers with different experience, ranging from undergraduate students to professional geologists with decades of experience. An individual’s understanding of faulting is impacted by their experience, yet people with similar experiences can interpret areas differently. No matter their experience level, mappers all have gaps in knowledge, and faults can rupture in unexpected ways. We anticipate that the results will improve the development of standardized mapping practices.

To evaluate the effect of differing knowledge on mapped fault trace locations, 23 mappers of varying experience levels produced fault maps from pre-rupture topography and imagery acquired before the earthquake of interest. Mappers include four undergraduate students, eleven graduate students, two postdocs, and three mid- and three senior-level professional geologists. The mappers used a systematic approach to map faults based on geomorphology.

To assess map quality, we compared the pre-rupture fault maps to published coseismic rupture maps. We evaluated 1) the percentage of coseismic ruptures that were predicted by the mapped faults, 2) the percentage of the mapped faults that ruptured in the recent earthquake, 3) the distribution of mapped faults around indicative geomorphic landforms, and 4) the impact of data type and the use of a geologic map. We found slight improvement by experience level in the portion of ruptures predicted and mapped faults that ruptured. For ruptures near geomorphic landforms, professional geologists best predicted the rupture location, and undergraduate students mapped with the highest error.  Less experienced mappers tended to misinterpret some geomorphology. Despite these differences in experience level, all participants mapped some faults that did not rupture. Mappers of all experience levels were most successful with the high-resolution topography (~1m/pix). Aerial imagery was less useful in areas with high vegetation and anthropogenic activity. Using a geologic map did not improve the maps.

While experience level has a small effect on fault trace mapping accuracy, with our results we can start defining the epistemic uncertainty for geomorphic fault mapping. Our results also suggest that mapping fault traces remains challenging regardless of expertise and highlight the need for improved and standardized mapping practices.

How to cite: Zuckerman, M., Scott, C., Arrowsmith, R., Madugo, C., Koehler, R., and Kottke, A.: Variability in the location of mapped fault traces based on geomorphic mapping of remote-sensing datasets from 23 mappers, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14423, https://doi.org/10.5194/egusphere-egu25-14423, 2025.