As offshore wind power development has expanded towards deeper and more distant waters, accurately understanding the geotechnical characteristics of thick Quaternary unconsolidated sediments has become a major challenge in engineering geological investigations. Reliable stratigraphic classification of such deposits is essential for ensuring safe and effective foundation design, but traditional drilling-based methods face significant limitations in complex offshore environments. To address this issue, high-resolution seismic profiles are integrated with piezocone penetration test (CPTu) data from an offshore wind farm off Lianjiang, Fujian in this study. Within the range of penetration depth common to both methods, Quaternary deposits were classified into seven seismic units and twelve CPTu units. The correspondence between the units defined by these two methods was analysed, and sedimentary facies and systems tracts were interpreted on the basis of the fundamental principles of sedimentology and sequence stratigraphy. The results demonstrated that the integration of seismic and CPTu data effectively combines the strengths of both techniques, thereby providing reliable and efficient engineering geological stratification of late Quaternary deposits offshore Fujian. This integrated approach facilitates both generalised and detailed stratigraphic interpretations, accounting for not only the engineering properties of the deposits but also their geological age and genetic origin.

The significant deformations of collapsible loess have caused numerous geotechnical failures, severely compromising the safety and serviceability of infrastructure. In this paper, watermelon seed-urease induced calcium carbonate precipitation (WSICP) was used to treat collapsible loess. The study was conducted using different concentrations of Urea-CaCl2 mixture solution (0.2, 0.4, 0.6, 0.8 and 1 mol/L) on five soil samples with different moisture contents (14, 16, 18, 20 and 22%). The compression of the treated soil samples with 14, 16, 18, 20 and 22 % moisture content decreased by 8.3, 11.2, 20.2, 11.9 and 27.9 %, respectively. The void of the treated soil samples was the smallest after compression stability. This is attributed to the fact that the generated calcium carbonate optimizes the pore structure and limits the movement of particles. The optimum treatment concentration was 0.6 mol/L. At this concentration, the compressive deformation resistance of soil samples with different moisture contents was strong, and the collapsibility grade gradually changed from ‘strong’ to ‘moderate’ and ‘non-collapsible’. The Scanning Electron Microscope Test (SEM) of the treated soil samples showed that the generated calcium carbonate existed in two crystal forms of calcite and vaterite. They realised the solidification of soil by bridging, adhesion and coating.

This paper proposes BACA-Net, a Band-Adaptive Collaborative Attention Network for hyperspectral image classification. The proposed method addresses the challenge of effectively extracting discriminative spectral-spatial features through a novel collaborative attention framework. BACA-Net integrates three parallel attention modules – global, local, and channel attention – with an interaction matrix to enable adaptive learning of significant spectral bands and spatial features. The architecture implements a dynamic feedback mechanism that enhances feature representation through multi-level fusion and adaptive feature optimisation. Additionally, the method introduces a multi-dimensional statistical band representation approach that comprehensively characterises spectral properties by integrating mean, root mean square, and maximum value features, capturing subtle spectral differences effectively. Experimental validation on four benchmark datasets (Indian Pines, Pavia University, Salinas Valley, and Houston2013) demonstrates that BACA-Net significantly outperforms existing CNN-based and attention-based methods, achieving overall accuracies of 93.21%, 96.47%, 96.54%, and 93.13%, respectively. The method exhibits exceptional performance in classifying spectrally similar categories and those with limited training samples. Computational efficiency analysis shows that BACA-Net maintains low inference times (0.228–0.887 ms) and moderate GPU memory consumption while delivering superior classification performance, making it a promising solution for practical hyperspectral remote sensing applications.

The July – September 2023 monsoon season in Himachal Pradesh, India, triggered a cascade of hydro-meteorological hazards – primarily floods and landslides – resulting in 428 fatalities (over 40% due to slope failures), displacement of more than 50,000 people, and economic losses exceeding INR 5,000 crore. Kangra, Kullu, and Chamba districts recorded rainfall over 1,800 mm – more than 150% above long-term averages. This study adopts a mixed-methods design, integrating high-resolution satellite imagery (Sentinel-2, Landsat-8), geospatial modelling (Kriging, Inverse Distance Weighting, Kernel Density Estimation, Getis-Ord Gi*), and terrain analysis with advanced statistical techniques, including Mann-Kendall trend tests, Pearson’s correlation, multiple and geographically weighted regressions, and spatial autocorrelation (Moran’s I). A flood severity model explained 85% of observed variance, identifying vegetation loss ( > 40%), steep slopes, and extreme precipitation as primary disaster predictors. Stratified household surveys (n = 240) revealed systemic deficiencies in early warning dissemination, evacuation logistics, and post-disaster recovery – particularly in remote, high-altitude, and rain-fed communities. These findings inform a spatially targeted, evidence-based disaster risk reduction framework. The study recommends district-specific strategies – such as lope stabilisation, floodplain zoning, and green infrastructure – that align with key Sustainable Development Goals and offer a scalable model for climate resilience in mountainous regions.

Understanding the dynamic mechanical properties and damage mechanisms of the surrounding rock during blasting and mining is crucial for preventing engineering accidents. In this study, triaxial and uniaxial impact compression experiments were conducted on paste phyllite using a Split Hopkinson Pressure Bar (SHPB) device under various confining pressures and strain rates. The effects of confining pressure and strain rate on the dynamic mechanical properties of paste phyllite, including stress-strain behaviour, dynamic compressive strength, and energy evolution characteristics, were investigated. The results reveal that the stress-strain curve in the triaxial state exhibits more prominent plasticity characteristics compared to the uniaxial state. The dynamic compressive strength and energy vary to different extents with increasing confining pressure and strain rate. As the confining pressure increases, the microscopic damage characteristics of the rock gradually transition from mixed tensile-shear cracks to predominantly shear cracks. Furthermore, the influence factor of confining pressure and the plasticity element were incorporated into the Zhu-Wang-Tang (ZWT) constitutive model. A dynamic damage constitutive model considering the effects of confining pressure and plasticity was established and validated using experimental data. The model demonstrated good agreement with the experimental results and could predict the stress-strain behaviour.

This comprehensive study seeks to assess the upper Jurassic Alif reservoir within the Halewah oil field in the Marib-Shabwa (Sab’atayn) Basin of Yemen. The Halewah oil field is considered one of the most promising areas for petroleum production and is greatly favoured by exploration activities. The study’s data set consists of digitised wireline logs for four wells and ten lines of 2D seismic profiles. Several faults affected the upper and lower salt members of the Sab’atayn Formation, which caused the Red Sea and Gulf of Aden tectonic activity. Results show that sandstone, shaly sandstone, calcite, and anhydrite comprise most of the Alif reservoir. Halewah well No. 02 has a high porosity of 21% and permeability of 1073 mD, with the highest net thickness of about 71.17 m. In contrast, Halewah well No. 06 has the lowest percentage in net thickness of 21.8 m with porosity of 15% and permeability of 511.2 mD. Alif reservoir exhibits promising characteristics, particularly in the upper reservoir unit. Intensifying exploration and prospecting operations in this unit is recommended.

Topographic influences of the ground motions in 3D geological configurations have been addressed using Spectral Element Method as implemented in SPECFEM3D code developed to simulate seismic wave propagation. Hexahedral mesh model was constructed to which the 1987 Jinka earthquake source characteristics were applied. The simulation results have shown that topography has significant effects on ground motion and changes PGA values by ± 55% compared to the flat topography. PGA amplification variation between valley and hill/ridge top is observed to be in the order of 1.6. The study indicates that there is PGA amplification on top of hills and de-amplifications occur at the base. Valleys and flat areas generally show low and negative amplification factors. It is observed that topographic features play significant roles in concentrating or diffusing seismic energy. This was confirmed by observing the behaviour of PGA values along selected profiles and by comparing PGA maps with and without topography. The study shows that topography has serious consequences and must be taken into account to minimise damage to infrastructures and safeguard human lives and suggests the importance of incorporating the effects of topographic features in any seismic hazard analysis schemes in densely populated mountainous regions.

ABSTRACTGlacial lakes in the Himalayas are increasing in size and number at an alarming rate, with the majority of lakes concentrated in the eastern and central parts of the mountain range. This research focuses on the future prediction of regional-scale glacial lake size in the entire Himalayan mountain range to avoid future glacial lake outburst flood (GLOF). Here, we used Landsat TM and OLI images, Google Earth imageries, Cartosat DEM, and SRTM DEM, and used some techniques: average lake size change rate, Markov model and glacial surface topography to extract glacial lake size change and future prediction of lake size. A total of 9675 individual glacial lakes were noticed during the study period (1990–2020), out of which the lakes present constantly throughout the study period (with size > 0.01 km2) were added in this study.1This study used two methods (i.e., Markov model and Glacier surface topography) to predict future lake size and identified 191 and 94 critical lakes that are most at risk of enlargement in Markov and glacial surface topography, respectively. Moreover, 443 critical lakes in Himalaya is distributed as 227 in the eastern Himalayas, 195 in the central Himalayas, and 21 in the western Himalayas. The findings suggest that the number and size of glacial lakes will continue to increase, posing an even greater risk of GLOFs in the future.

This study aims to explore the relationships between public and private sectors in tourism disaster management and assess the criteria for the realisation of public and private collaborations in tourism disaster management in terms of their priorities. This research, conducted in two regions in Indonesia, employed in-depth interviews, focus group discussions and an Analytical Hierarchy Process (AHP) survey participated by representatives of relevant government agencies and tourism industry associations. Findings show that each stakeholder play bigger roles compared to others in the different phase of tourism disaster management. The study also identifies six possible criteria for public private collaborations in tourism disaster management, namely the formation of special organisation for crisis management, certification for disaster preparedness, the availability of guidelines for disaster management, regulation for critical facilities in disaster management, tourism planning which considers disaster risk awareness, and tourism industry associations’ enhanced role in improving disaster risk awareness. Through AHP surveys involving experts, it is found that there is different level of disaster preparedness between regions and different priorities chosen by their stakeholders. Higher level of disaster preparedness and a more practical implementation of disaster management in Bali is likely due to the influence of international market demand.

Techniques for the semantic segmentation of remotely sensed imageries for building footprint identification have been widely studied and several supervised and unsupervised techniques have been proposed. The ability to perform online mapping and accurate segmentation on a large scale by taking into account the multifariousness inherent in aerial images has important implications. In this paper we propose a new method for building footprint identification using multiresolution analysis based self-attention technique. The scheme is promising to be robust in the face of variability inherent in remotely sensed images by virtue of the capability to extract features at multiple scales and focusing on areas containing meaningful information. We demonstrate the robustness of the proposed method by comparing it against several state-of-the-art techniques using aerial imagery with varying spatial resolution and building clutter and it achieves better accuracy around 95% even under widely disparate image characteristics. We also evaluate the ability for online mapping on an embedded graphic processing unit (GPU) and compare it against different compute engines and it is found that the proposed method on GPU outperforms the other methods in terms of accuracy and processing time.