The Anatolian–Aegean region, located at the convergence of the Eurasian, African, and Arabian plates, is one of the most tectonically active deformation zones on Earth that is primarily controlled by the African slab rollback beneath the Hellenic–Cyprus Subduction Zone (HCSZ) and the movement of the North Anatolian Fault Zone (NAFZ). The Mw7.0 2020 Samos earthquake, for instance, is an expression of the N-S directed extensional tectonic regime developed in response to the African slab rollback. This study quantitatively evaluates the respective contributions of the NAFZ kinematics and the rollback of the subducting African slab along the HCSZ to the present-day deformation of the Anatolian–Aegean domain to better elucidate the tectonic development and its potential seismic hazard in this region. Using a two-layer elastic–viscoelastic Earth model and GPS velocity data, we decomposed the observed velocity field into the rotational motion of the Anatolian–Aegean system and the residual effects associated with slab rollback. The Anatolian–Aegean region is enclosed by the circuit of the NAFZ, the East Anatolian Fault Zone, and the HCSZ. We assigned slip rates over the circuit according to the rotation pole located off Egypt and estimated the velocities at each GPS station with varied angular velocities. We performed a series of forward and inverse calculations to determine the optimal slip rates along the NAFZ and HCSZ that minimize the misfit between the estimated and observed velocities. Our results indicate an optimal right-lateral slip rate of 31 mm/yr along the NAFZ, which is consistent with the sum of the observed slip rates along the northern and southern strands of the NAFZ, as well as an average slip rate of 50 mm/yr for the HCSZ, peaking around western and eastern Crete. These findings confirm that the westward extrusion of Anatolia is predominantly driven by the NAFZ slip, while the southwestward motion and N-S extension across the Aegean Sea are governed by Hellenic slab rollback. The stress accumulation rates derived from the optimum model demonstrate strong consistency with regional focal mechanism solutions, reproducing strike-slip stress patterns across central Anatolia and extensional stresses within the Aegean domain.

In Turkey, forest fires pose a serious threat to the environment since they persistently destroy infrastructure, lives and forest ecosystems. The General Directorate of Forestry's official statistics indicate a rising trend in the frequency of wildfires, highlighting the need for better risk assessment and sustainable land management techniques. Adequate identification of areas that are fire-prone via a reliable modelling framework is therefore important for mitigation planning and resource distribution. Based on historical forest fire record coupled with other anthropogenic and environmental conditioning factors, this research performs a detailed assessment of the I(center dot)zmir region's susceptibility to forest fires. The evaluated variables include climatic variables (wind speed, precipitation, temperature), topographic factors (altitude, slope, aspect, curvature, topographic wetness index (TWI), terrain ruggedness index (TRI), topographic position index (TPI)), land features (land use/land cover (LULC), geology, tree cover density, forest types), and closiness variables (distance to settlements, roads, and rivers). The influence of each parameter was evaluated through feature importance analysis to determine the key factors driving wildfire susceptibility. Fire susceptibility modelling was carried out employing three different machine learning algorithms, which are eXtreme Gradient Boosting (XGBoost), Decision Tree (DT), and Support Vector Machine (SVM). Model performance was carefully analyzed and compared to determine which one exhibits the highest predictive framework accuracy. The one with the best outcome was finally selected to produce a high-resolution susceptibility map and to forecast future wildfires under amended temperature and precipitation conditions. Feature importance analysis indicated that geology, temperature, aspect, and precipitation are the most important factors influencing current wildfire susceptibility patterns in the study zone. The socioeconomic exposure was also evaluated by intersecting areas of high fire probability predicted by the XGBoost model with spatial data on vulnerable assets. This combined analysis provides practical insights to support regional wildfire management and mitigation strategies. Nonetheless, the generated susceptibility maps present an effective decision-support tool for authorities, enabling the identification of priority zones for intervention, strengthening early prevention strategies, and enhancing the spatial distribution of monitoring and fire suppression efforts. This research generates a scientific framework for well-informed decision-making and aimed interventions, amplifying disaster risk mitigation and long-term environmental sustainability.

Landslides represent a significant natural hazard, causing widespread human, infrastructure, and environmental losses. Geospatial technologies have become essential for monitoring, detection, and risk assessment of landslides. This review provides a comprehensive examination of the evolution and application of geospatial technologies in landslide research, addressing a significant gap in the current literature. First, we focus on landslide monitoring and detection, covering spaceborne and airborne Earth Observation (EO) technologies, ground-based remote sensing, mobile Geographic Information System (GIS) applications, and data processing methodologies, including traditional image and Artificial Intelligence (AI)-based approaches. Second, we examine landslide analysis, which includes susceptibility mapping, vulnerability and risk assessments. Our bibliometric analysis reveals that landslide susceptibility is the most extensively studied category, followed by risk, while vulnerability remains significantly underexplored. China, India, South Korea, Iran, and the United States are the most active contributors across all three categories. China leads in susceptibility research due to high publication volume. A similar pattern is observed in risk studies, where China, Italy, India, and the United States have the most publications. However, the notable underrepresentation of vulnerability research suggests a gap in understanding the socio-economic and infrastructure impacts of landslides. These findings highlight the need for greater emphasis on vulnerability studies to improve landslide risk mitigation. Our results emphasize the need for increased focus on vulnerability studies to strengthen landslide risk mitigation strategies. In addition, we identify key challenges in landslide management and discuss emerging trends aimed at improving prediction, monitoring, and disaster response.

30 Ekim 2020 tarihinde Sisam adası kuzeyinde Mw:6.9 büyüklüğünde bir deprem meydana gelmiştir. Bu deprem İzmir şehir merkezinde ve bazı ilçelerinde can ve mal kayıplarına yol açmıştır. Deprem sonrası İzmir ve güneyinde yapılan çalışmalar, en büyüğü Seferihisar'da olmak üzere İzmir ve güneyinde 4-14 cm arasında değişen miktarlarda yatay atım meydana geldiğini göstermiştir. İzmir ve güneyinde ise Mw:6.1 ile Mw:6.9 arasında deprem üretme potansiyeline sahip olan diri faylar yer almaktadır. Meydana gelen bir depremin civardaki fayların neden olabileceği depremleri etkileyebilmesi nedeniyle bu bölgede postsismik deformasyonun takip edilmesi amacıyla 27 noktalık bir GNSS ağı kurulmuştur. Bu ağda 2020-2022 arasında 6 aylık periyotlar halinde 4 kampanya GNSS ölçümü gerçekleştirilmiştir. GNSS verileri kullanılarak tüm noktaların Avrasya sabit hızları elde edilmiştir. Elde edilen sonuçlar ağdaki noktaların hem deprem sonrasında kendi aralarındaki hem de deprem öncesi hızlarla aralarındaki farkların 6 mm'ye ulaştığını, buna bağlı olarak bölgede postsismik etkinin devam ettiğini göstermektedir.

The Istanbul Natural Gas Distribution Company has started monitoring seismic activity within the Sea of Marmara using a fiber-optic (F/O) cable integrated with a Distributed Acoustic Sensing (DAS) system in order to mitigate secondary disasters that may occur after earthquakes and to protect critical infrastructures, such as pipelines. The monitored F/O cable, originally designed for telecommunications purposes, extends over a length of 60 kilometers beneath the Sea of Marmara. In 2022 October, this cable is integrated with a DAS system through an interrogator unit, installed at Tavşantepe Metro Station. The system consists of an analyzer that allows detection up to 40 kilometers, operates with a spatial channel spacing of 10 meters, in total 3910 channels, and a sampling rate of 200 Hz, enabling high-resolution seismic data acquisition. The cable’s route follows several critical regions: it enters the Sea of Marmara, traverses Büyükada, runs behind the Princes' Islands parallel to the Marmara Fault, intersects the fault at multiple locations, and ultimately terminates on land at Ambarlı. This strategic placement provides extensive coverage for monitoring seismic activity along this geologically active region.Since the beginning of 2023, more than 500 earthquakes, with magnitudes ranging from 0.7 to 7.8, have been recorded using the F/O cable. Our analysis reveals that the quality of recorded seismic signals is strongly influenced by two factors: the incidence angle of wave on the cable and the cable's coupling with the ground. Poor coupling reduces the energy transfer from the ground to the cable, leading to weaker or distorted signals, while unfavorable incidence angles of wave, affect the strain response detected by the DAS system. These findings highlight the importance of optimizing cable placement and ensuring effective coupling for reliable seismic monitoring.The developed algorithms have enabled the real-time automatic detection of earthquakes occurring within and around the Sea of Marmara using the F/O cable, and the initial results have been promising. The first real-time detection is accomplished for the M3.9 Çanakkale earthquake occurred on 19 November 2024 at 07:46:15 UTC. The F/O cable detects the earthquake 33 seconds following its occurrence, and the system sent an automatic detection notification approximately 1 second later after detection.As part of our project, at the beginning of January 2025, a vessel-based survey is conducted to determine the submarine position of the F/O cable passing beneath the Sea of Marmara. This study contributes to improving the application of DAS in submarine seismic observation and highlights potential challenges in data acquisition from F/O cables.

Abstract Tectonic features of Türkiye are mainly controlled by the relative northward movements of the Arabian and subducting African plates with respect to the Anatolian and Eurasian plates. Resultant extensional and collisional tectonics lead to a westward material extrusion accommodated along the right- and left-lateral strike-slip North Anatolian and East Anatolian Fault Zones (NAFZ and EAFZ), respectively. This lateral motion continues southward along the Dead Sea Fault Zone (DSFZ) at the southeastern of Türkiye. February 20, 2023, Mw 6.3 Hatay Earthquake occurred two weeks after the seismic energy release of the February 6, 2023, Kahramanmaraş earthquakes at the intersection of EAFZ, DSFZ, and the onshore extension of the Cyprus Arc. The N-S trending DSFZ starts from the south of the EAFZ and continues through Syria, Lebanon, and Israel. Although the broken segment in Hatay is not as active as the northern segments of the EAFZ, it has accumulated strain leading to significant seismic activity in the past in this region, i.e., the 1872 M7.2 earthquake occurred on the Karasu Fault. 2023 Kahramanmaraş and Hatay earthquakes caused severe damage in Hatay and the surrounding area. To determine the co-seismic deformation during the February 20, 2023, Hatay Earthquake, we applied the Interferometric Synthetic Aperture Radar (InSAR) technique on the Sentinel-1 data. Ascending and descending track SAR images before and after the Kahramanmaraş and Hatay earthquakes were analyzed using the TopsApp module of the InSAR Scientific Computing Environment (ISCE) software to obtain Interferograms of co-seismic deformation in and around Hatay region. Finally, we investigated source parameters by performing an inversion on geodetic constraints considering the Okada elastic dislocation model.

Landslides are a formidable natural geological hazard that impose significant disruptions on societal and economic functions. The magnitude of impact of landslides on human life makes early detection imperative in landslide-prone areas. The aims of this study were to detect landslide locations triggered by the Taiwan Morakot typhoon in 2009 using Sentinel-2 imagery. The fully convolutional network; image cascade network; red, green, blue plus depth (RGB-D) fusion network (RDFNet); and segmented neural network algorithms were developed to more accurately detected historical landslide locations and afterward generate a landslide susceptibility map using standard and optimized deep learning models (convolutional neural network [CNN], CNN-whale optimization algorithm, and CNN-Harris hawk optimization [HHO]). Analysis using frequency ratio to evaluate the relationship between classes of different causative factors and landslide occurrence revealed that slope length and land cover were most strongly correlated with landslide occurrence. Among the algorithms tested, RDFNet demonstrated superior accuracy in detecting historical landslide locations, achieving the highest F1-score (0.67), precision (0.55), recall (0.84), and accuracy (0.92). The landslide inventory dataset derived from RDFNet was used in landslide susceptibility modeling, and was divided into 70 % and 30 %, respectively, for training and testing the CNN-based models. Mean square error (MSE), root mean square error (RMSE), standard deviation (StD), and area under the receiver operating characteristic curve (AUROC) were used to evaluate goodness-of-fit and predictive ability of the CNN-based models. The most reliable outcome was obtained using CNN-HHO, with AUROC = 0.85, MSE = 0.017, RMSE = 0.132, and StD = 0.129 during the testing step. By leveraging insights provided by modeling into areas with high landslide susceptibility, authorities can proactively implement measures to mitigate the potential consequences of landslides and promote sustainable stewardship of natural resources.

The Anatolian Plate, surrounded by the Eurasian, African and Arabian plates, represents a great laboratory for geoscientists with its all complicated tectonic settings. The region is located at a widely spread active tectonic deformation zone that has primarily been controlled by the African plate subduction beneath the Hellenic Trench and the movement of the North Anatolian Fault Zone (NAFZ). The effect of crustal thinning due to the extensional regime gave rise to the formations of horst and graben systems leading to large earthquakes (e.g. The Mw7.0 2020 Samos earthquake) with normal faulting mechanisms in western Türkiye. A precise evaluation of tectonic deformation process and the potential seismic risk in this area requires a comprehensive understanding of the quantitative impact of both the Hellenic subduction and the NAFZ to the surface movement. To distinguish these individual contributions, we examine the published regional GPS data along Greece-Türkiye region. Considering a basic elastic-viscoelastic layered earth model, our first step is to estimate the contribution of the NAFZ to the GPS velocity at each station under various average slip rare conditions. We then perform an inversion on the residual velocities obtained by subtracting the calculated velocity from the observed data. This inversion allows us to derive the subduction rate along the Hellenic Trench. Our modelling indicates an optimal slip rate of

Abstract Türkiye has a complex tectonic structure resulting from the northward movement of the African and Arabian plates towards the Anatolian plate relative to the Eurasian plate. Seismic energy is primarily released within the Anatolian plate by earthquakes along the North Anatolian Fault Zone (NAFZ), which is oriented east-west with a right-lateral strike-slip motion. Historical earthquake records suggest a westward migration of seismic energy release along this fault system through a series of earthquakes, beginning with the 1939 M7.9 Erzincan earthquake and culminating in the 1999 M>7 Izmit-Düzce ruptures. The 1999 Mw7.2 Düzce earthquake occurred three months after the 1999 Mw7.4 Izmit earthquake to the east leading to an eastward supershear rupture. We examine the potential correlation between crustal features, fault mechanisms, and inter-seismic loading parameters that impact surface deformation in Düzce. We analyzed spatio-temporal variation of the long-term surface deformation along the Düzce segment. We evaluated Sentinel-1 InSAR data for both ascending and descending orbits from 2014 to 2022, utilizing the InSAR Small Baseline Subset time series analysis technique to calculate horizontal and vertical displacements and the locking depth. Our findings indicate 25 mm/yr of slip rate on the Düzce Fault. We further utilize the previously estimated geoelectric characteristics of the crust by magnetotelluric data modeling that show strong resistivity variations from east to west on the Düzce rupture. Incorporating geodetic (e.g., InSAR-derived surface deformation) and geophysical (electrical resistivity, seismic velocity) constraints on the fault zone and its adjacent shed light on the impact of the physical characteristics of the crustal structure on the inter-seismic loading and surface creep parameters. This project is funded by the Bogazici University with the BAP Project No SUP-18161.

The Istanbul Natural Gas Distribution Company (İGDAŞ) has recently embarked on utilizing existing Fiber-Optic (F/O) cables to enhance disaster prevention and mitigation efforts in Istanbul. We are exploring the potential of a novel technology called F/O Distributed Acoustic Sensing (DAS) for earthquake early warning systems. The strategic placement of the F/O cable, which crosses the North Anatolian Fault in the Marmara Sea, presents a unique opportunity for monitoring seismic activity. While seismic stations exist around the Marmara Sea, the absence of online operating Ocean Bottom Seismometer (OBS) stations makes the F/O cable the only sensor positioned across the fault lines expected to rupture during a major earthquake.The monitored F/O cable, originally intended for telecommunications, spans 60 kilometers in the Sea of Marmara. Over the past 7 months starting in June 2023, more than 160 earthquakes ranging from magnitudes 1.0 to 7.5 have been recorded through the F/O cable. Notably, the F/O DAS system successfully captured significant distant events, notably the February 6, 2023, M7.8 and M7.5 earthquakes in Kahramanmaraş. This initiative highlights the critical stages, obstacles, and best practices associated with deploying this technology. It underscores the importance of precise cable layout, optimal sensor density, range optimization, and the conduction of shaking table tests.Shaking table experiments were conducted to compare noise levels across various sampling rates. By subjecting a Force-Balanced Accelerometer (FBA) and F/O cable to simulated seismic activity resembling the 1999 Sakarya Earthquake (M6.9) with sine signals at frequencies of 0.25 Hz, 0.5 Hz, 1.5 Hz, 2 Hz, and 3 Hz, observations revealed that reducing the sample rate to 200 sps significantly lowered the interrogator's instrumental noise compared to 2000 sps. Hence, a lower sample rate proved advantageous in achieving a better Signal-to-Noise Ratio (SNR).Through the analysis of acoustic signal variations along the F/O cable, the DAS systems can accurately pinpoint and characterize earthquake events, facilitating timely warnings. F/O DAS technology boasts distinct advantages in earthquake detection due to its capacity to capture a broad spectrum of seismic signals, ranging from low-frequency tectonic shifts to high-frequency ground vibrations. The effectiveness of F/O DAS measurements relies on proper coupling, ensuring the efficient transfer of acoustic signals to the optical fiber, thereby ensuring precise detection and interpretation of seismic activity.

Türkiye is known as one of the most seismically active regions in the world due to its rapidly deforming tectonic properties that has been developed by the northward movement of the African and Arabian plates relative to the Eurasian plate. These plate movements caused the Anatolian plate to be compressed in the east and move westward, resulting in the formation of the most important tectonic structures in the region, the North Anatolian Fault Zone (NAFZ) with ∼1500 km length and right-lateral strike-slip motion in the east-west direction, and the East Anatolian Fault Zone (EAFZ) with ∼700 km length and left-lateral strike-slip motion in the northeast direction. Historical records show that seismic energy release along the NAFZ migrated westward with large earthquakes, i.e., the 1939 Erzincan earthquake (Mw7.9), 1942 Erbaa-Niksar earthquake (Mw7.0), 1999 İzmit earthquake (Mw7.4), and 1999 Düzce earthquake (Mw7.2). However, two significant seismic gaps exist throughout the NAFZ; Marmara and Yedisu. We, in particular, examined the Yedisu Seismic Gap (YSG) in this study, by investigating the interrelationships between seismicity, Coulomb stress changes, seismotectonic b-values, and surface deformation with the aim of understanding the characteristics and seismic hazard potential in and around the YSG. More specifically, we analyzed the seismic activity of the eastern NAFZ extending from the Erzincan basin to the Karlıova Triple Junction (KTJ) using earthquake catalogs from 1900 to 2024, which include both Mw≥1 earthquakes and Mw≥4 earthquakes. 3D Coulomb stress change behavior was compared with the background seismicity pattern in the region. We further performed a joint interpretation of lateral variation of statistical b-values, seismic P- and S-wave speeds, and InSAR-based surface deformation in order to understand possible regions of asperities or high pore-pressure where the accumulated stress often released due to the decreasing normal stress on the fault. Our preliminary results indicate that the stress has been transferred to the YSG following the 14 June 2020 Mw5.7 Karlıova earthquake. The results of our multi-data analysis will provide invaluable insight into the current seismic hazard potential of the YSG, which will be essential for future urban planning in this region.

Effective shelter location-allocation is critical in nuclear emergencies to ensure rapid, safe evacuation and resource access for affected populations. This study presents a multi-dimensional optimization model for shelter allocation within humanitarian logistics, balancing evacuation time, supply accessibility, and shelter capacity. Using Geographic Information Systems (GIS) and Multi-Criteria Decision Analysis (MCDA), the model optimizes trade-offs among competing objectives. The first objective minimizes evacuation time, the second ensures adequate supply access, and the third prevents shelter overcrowding. Validated through k-fold cross-validation, the model reveals spatial biases: evacuees often cluster in nearby shelters, leading to overcrowding in dense areas and underuse in others. This analysis suggests adding flexible shelters in high-density zones to enhance response efficiency. Overall, the research supports more balanced shelter allocations in nuclear emergencies, improving both immediate and long-term disaster response strategies for affected populations

This paper examines neighborhood-scale social vulnerability to nuclear accidents in Turkiye, focusing on identifying the most at-risk areas and demographic groups across several dimensions: demographics, buildings and environment, preparedness, emergency response, and coping capacity. The study has three main objectives: (1) improving the social vulnerability model by emphasizing criteria specific to nuclear accidents, (2) developing an assessment model for identifying vulnerable communities using a worst-case nuclear accident scenario, and (3) helping emergency managers pinpoint community sub-groups most susceptible to reduced resilience. Social vulnerability was assessed using both the Best–Worst Method (BWM) and Analytic Hierarchy Process (AHP), with comparisons highlighting slight differences due to their distinct methodologies. The findings reveal significant vulnerability, with many neighborhoods lacking adequate emergency preparedness programs such as public education, access to emergency supplies, and established evacuation routes. Comparing BWM and AHP helps researchers select the most suitable method, while the developed SVI offers a valuable tool for improving nuclear disaster risk management and community resilience.

Abstract We developed a model integrating 28 criteria spanning social, economic, community, environmental, and physical dimensions to evaluate earthquake resilience of Istanbul, a city with a population of 16 million and significant seismic risk, at both district and subdistrict/neighborhood levels. The resilience assessment uses the Bayesian Best-Worst Method, a multi-criteria decision-making framework that combines expert knowledge and statistical assessments. The results reveal that Istanbul’s overall Resilience Score (RS) is 0.48, on a 0-1 scale, suggesting a moderate capacity to endure and recover from seismic events. Catalca, Adalar, and Arnavutkoy rank among the most resilient districts, whereas Esenler and Gungoren exhibit lower resilience. On a subdistrict level, Suleymaniye (Fatih) has the highest RS at 0.59, while Yavuz Sultan Selim (Fatih) ranks the lowest with 0.22. These findings provide actionable and practical data-driven insights for policymakers and urban planners, underscoring the need for targeted interventions to improve resilience in high-risk areas in Istanbul.

This study conducted a regional assessment of the environmental and health consequences due to the release of radionuclides, including the most harmful, such as Cs-137 and I-131, from a hypothetical reactor accident at the first Nuclear Power Plant (NPP), Akkuyu Nuclear Power Plant, in Turkiye under different meteorological conditions. Simulations of the atmospheric flow were done using a Gaussian-based probabilistic model. Based on the estimated air and land contamination, radiation doses and cancer risks to the population were calculated. The assessment results were then compared with the criteria for protective actions in the event of a radioactive release and were subsequently used to assess the sufficiency of the Precautionary Action Zone (PAZ) and Urgent Protective Zone (UPZ) provided by regulations. The assessment indicated that evacuation outside the UPZ would likely be required during the early phase of the emergency, while sheltering indoors might be necessary up to 80 km. Protective actions such as restrictions on being outdoors or iodine prophylaxis are needed far beyond the radius of the UPZ. These results provide important insights into safe protective measures to reduce the risk of radiation-related cancer when considering a hypothetical severe nuclear accident. In addition, the results of this study aim to improve the current nuclear emergency response program and support nuclear decision-making.

The North Anatolian Fault Zone (NAFZ), that represents a transform plate boundary between the Anatolian and Eurasian plates, generated several devastating earthquakes in the 20th century. The well-known seismic sequence along the NAFZ has begun with the 1939 M7.9 Erzincan Earthquake and followed a westward migrating pattern until the 1999 M>7 Izmit-Düzce ruptures. Although there have been extensive efforts on modeling co-seismic slip properties of the recent large events along the NAFZ, possible interplay of crustal properties with fault mechanics and inter-seismic loading parameters characterized by surface deformation behavior is less known. This study aims to determine the spatio-temporal behavior of long-term surface deformation along the Düzce Fault segment of the NAFZ. We examine the effect of physical properties of the crustal structure on the inter-seismic loading and surface creep parameters in this actively deforming area. For this purpose, we adopted the well-known InSAR timeseries method using publicly available Sentinel-1 data. Sentinel-1 observations covering our study area has a time span of 8 years between 2014 and 2022. We exploit geoelectrical properties and other available seismological observations/models of the crust to be evaluated with the velocity fields inferred from InSAR time series analysis. We further compare variations in the surface deformation prior to and after the most recent November 23rd, 2022, Mw6.0 Gölyaka-Düzce earthquake by using data obtained from the analysis of both ascending and descending InSAR datasets. Our preliminary results show the slip rate of ~25 mm/yr on the Duzce Fault.

The increasing risk of earthquakes in urban areas has made it crucial to develop accurate vulnerability models for city infrastructure and systems. We aimed to assess and compare the effectiveness of different models and vulnerability analysis techniques in predicting earthquake vulnerability in the specific context of Izmir, Turkey. One central hypothesis in this research aimed to determine whether integrating Eigenvector Spatial Filtering (ESF) into both regression models and machine learning algorithms would yield a comparable enhancement in model performance. We performed earthquake vulnerability modeling (EVM) by considering (ⅰ) only seismic-related variables (SRV) and (ⅱ) integrating ESF by using Moran's eigenvector maps (MEMs). For each approach, we evaluated the predictive performance of two simple regression-based models; generalized linear model (GLM) and generalized additive model (GAM), and two complex machine learning ones; generalized boosting model (GBM), and random forest (RF). The study utilized five primary indicators encompassing geotechnical, physical, structural, social, and facilities data. The predictive performance of the models was assessed using evaluation metrics including Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and adjusted R2. The results indicated that the optimal candidate model consisted of five key variables: altitude, building height, distance to safety gathering places, Peak Ground Acceleration (PGA), and population density. We found that decision-tree-based methods performed better than regression-based methods for both modeling schemes. RF exhibited the highest predictive performance for the training data (RMSE = 0.59, adjusted R2 = 0.71), while GBM outperformed other models for the test data (RMSE = 0.79, adjusted R2 = 0.78). However, incorporating ESF to the EVM analysis revealed that regression-based methods, particularly the GLM, obtained highest improvement in accuracy (RMSE 0.94 vs 0.76 and adjusted R2 0.56 vs 0.71 for the SRV and SRV + MEMs modeling approach). Significant differences were observed between GLM-GBM and GLM-RF comparisons, as well as GAM-GBM and GAM-RF comparisons. The findings of this research are expected to be helpful for informed decision-making, targeted risk reduction, and the development of effective policies and strategies to enhance preparedness and resilience in the face of seismic events in highly susceptible urban systems.

Bu çalışmada 6 Şubat 2023 tarihinde sırasıyla yerel saat ile 04:17 ve 13:24’te artarda meydana gelen Sofalaca-Şehitkamil Gaziantep (Mw:7.7) ve Ekinözü Kahramanmaraş (Mw:7.6) depremlerinin öncül jeodezik sonuçları verilmiştir. Öncül jeodezik sonuçları elde etmek için deprem odak merkezleri etrafındaki ve etkili olduğu alandaki TUSAGA-Aktif istasyonlarına ait GNSS alıcılarından 30 sn (0,033 Hz) ve 1 sn’lik (1 Hz) GNSS gözlemleri kullanılmıştır. Deprem kaynaklı kosismik yer değiştirmeleri belirlemek için bağıl statik çözümler GAMIT/GLOBK yazılım takımında 30 sn’lik RINEX verileri kullanılarak yapılmıştır. Statik çözümlerde değerlendirmeye alınan istasyonlarda Sofalaca-Şehitkamil Gaziantep depreminde doğu bileşende atımın 1.1-23.4 cm, kuzey bileşende 1.1-30.9 cm aralığında değiştiği görülmüştür. Ekinözü Kahramanmaraş depreminde ise atım miktarı doğu bileşende 1.2-440.4 cm, kuzey bileşende 1.4-69.6 cm aralığında değişmiştir. Kinematik çözümler ise PPP yöntemiyle CSRS-PPP ve PRIDE PPP-AR yazılımları ile 1 sn’lik RINEX verileri kullanılarak elde edilmiştir. Her iki yazılımda seçilen istasyonlardaki deprem anı yer değiştirmeler (deplasman) ve ardışık epok farkları (hız) hesaplanmıştır. Seçilen tüm istasyonlarda hızlar Sofalaca-Şehitkamil Gaziantep depreminde doğu bileşen için 3-12.5 cm/sn, kuzey bileşen için 3.8 - 37.7 cm/sn aralığında; Ekinözü Kahramanmaraş depreminde ise doğu bileşende 3.7-20.5 cm/sn, kuzey bileşende 4.1-20.1 cm/sn tespit edilmiştir. Öncül sonuçların elde edilmesinden sonra bölgenin daha yakından takibi ve yeni noktalarda atımların tespiti için yeni bir GNSS ağı kurulmuştur. Kurulan yeni ağda TÜBİTAK 1002-C Doğal Afetler Odaklı Saha Çalışması Acil Destek Programı çağrısı kapsamında arazi çalışmalarına başlanmıştır.

Aim: Generate fire susceptibility maps for the present and 2070, to identify the threat wildfires pose to koalas now and under future climate change. Location: Australia. Time period: Present and 2070. Major taxa studied: 60 main tree species browsed by koalas. Method: The Decision Tree machine learning algorithm was applied to generate a fire susceptibility index (a measure of the potential for a given area or region to experience wildfires) using a dataset of conditioning factors, namely: altitude, aspect, rainfall, distance from rivers, distance from roads, forest type, geology, koala presence and future dietary sources, land use-land cover (LULC), normalized difference vegetation index (NDVI), slope, soil, temperature, and wind speed. Results: We found a general increase in susceptibility of Australian vegetation to bushfires overall. The simulation for current conditions indicated that 39.56% of total koala habitat has a fire susceptibility rating of "very high"or "high", increasing to 44.61% by 2070. Main conclusions: Wildfires will increasingly impact koala populations in the future. If this iconic and vulnerable marsupial is to be protected, conservation strategies need to be adapted to deal with this threat. It is crucial to strike a balance between ensuring that koala habitats and populations are not completely destroyed by fire while also allowing for forest rejuvenation and regeneration through periodic burns.& COPY; 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).