Search Results (854)

Floods are considered one of the most devastating natural hazards, frequently resulting in substantial loss of lives and widespread damage to infrastructure. In the period of 4–7 September 2023, the region of Thessaly experienced unprecedented rainfall rates due to Storm Daniel, which caused significant flooding and many damages and fatalities. The southeastern areas of Trikala were among the many areas of Thessaly that suffered the effects of these rainfalls. In this research, a flood susceptibility assessment (FSA) of the broader area surrounding the settlement of Megala Kalyvia is carried out through the analytical hierarchy process (AHP) as a multicriteria analysis method, using Geographic Information Systems (GIS). The purpose of this study is to evaluate the prolonged flood susceptibility indicated within the area due to the past floods of 2018, 2020, and 2023. To determine the flood-prone areas, seven factors were used to determine the influence of flood susceptibility, namely distance from rivers and channels, drainage density, distance from confluences of rivers or channels, distance from intersections between channels and roads, land use–land cover, slope, and elevation. The flood susceptibility was classified as very high and high across most parts of the study area. Finally, a comparison was made between the modeled flood susceptibility and the maximum extent of past flood events, focusing on that of 2023. The results confirmed the effectiveness of the flood susceptibility assessment map and highlighted the need to adapt to the changing climate patterns observed in September 2023. Full article

This paper presents a geomechanical characterization for unwelded volcanic bimrock materials. Bimrocks are geological materials consisting of blocks of rock of different sizes embedded in a finer matrix. Many volcanic deposits and outcrops can be classified as bimrocks, and some of them correspond to unwelded bimrocks, i.e., with the absence of strong bonds between blocks of rock and matrix. The geomechanical characterization proposed is oriented towards bimrocks slopes, their stability and landslide hazard occurrence. It consists of five steps which includes the material description, the volcanic deposit classification, the definition of block size range, the computation of the volumetric block percentage, the geotechnical characterization of the blocks of rock, and the geological and geotechnical analysis of the matrix that surrounds the blocks. The geomechanical characterization proposed is applied to four slopes at the Western Cordillera of Ecuador, where slopes instabilities are common. Results show that the geomechanical characterization sets a reliable framework for geotechnically describing bimrocks materials, explaining the actual stability state of the slopes. It also enables taking appropriate and optimum decisions in the design and management of volcanic slopes, thus contributing to a sustainable approach of landslide mitigation. Full article

Landslide susceptibility modelling represents an efficient approach to enhance disaster management and mitigation strategies. The focus of this paper lies in the development of a landslide susceptibility evaluation in northwestern Tunisia using the Analytical Hierarchy Process (AHP) and Artificial Neural Network (ANN) approaches. The used database covers 286 landslides, including ten landslide factor maps: rainfall, slope, aspect, topographic roughness index, lithology, land use and land cover, distance from streams, drainage density, lineament density, and distance from roads. The AHP and ANN approaches were applied to classify the factors by analyzing the correlation relationship between landslide distribution and the significance of associated factors. The Landslide Susceptibility Index result reveals five susceptible zones organized from very low to very high risk, where the zones with the highest risks are associated with the combination of extreme amounts of rainfall and steep slope. The performance of the models was confirmed utilizing the area under the Relative Operating Characteristic (ROC) curves. The computed ROC curve (AUC) values (0.720 for ANN and 0.651 for AHP) convey the advantage of the ANN method compared to the AHP method. The overlay of the landslide inventory data locations of historical landslides and susceptibility maps shows the concordance of the results, which is in favor of the established model reliability. Full article

The Mayanghe National Nature Reserve, a key habitat for the endangered François’ langur (Trachypithecus francoisi), faces significant anthropogenic disturbances, including extensive distribution of croplands, roads, and settlements. These human-modified features are predominantly concentrated at elevations between 500 and 800 m and on slopes of 10–20°, which notably overlap with the core elevation range utilized by François’ langur. Spatial analysis revealed that langurs primarily occupy areas within the 500–800 m elevation band, which comprises only 33% of the reserve but hosts a high density of human infrastructure—including approximately 4468 residential buildings and the majority of cropland and road networks. Despite slopes >60° representing just 18.52% of the area, langur habitat utilization peaked in these steep regions (exceeding 85.71%), indicating a strong preference for rugged karst terrain, likely due to reduced human interference. Habitat type analysis showed a clear preference for evergreen broadleaf forests (covering 37.19% of utilized areas), followed by shrublands. Landscape pattern metrics revealed high habitat fragmentation, with 457 discrete habitat patches and broadleaf forests displaying the highest edge density and total edge length. Connectivity analyses indicated that distribution areas exhibit a more continuous and aggregated habitat configuration than control areas. These results underscore François’ langur’s reliance on steep, forested karst habitats and highlight the urgent need to mitigate human-induced fragmentation in key elevation and slope zones to ensure the species’ long-term survival. Full article

During the period from 2020 to 2024, 900 springs were mapped on the southern slopes of Medvednica Mountain Nature Park. Physicochemical parameters (temperature, pH, and electrical conductivity) were measured at 701 of these springs using a portable multimeter, and results were analyzed in relation to local lithology and human activities. This research provides the first results of this kind in this study area, aiming to expand the knowledge on local springs and to support the future protection and management of spring ecosystems. Springs on the Medvednica mountain showed substantial variation in measured parameters. The temperature ranged from 3.4 to 18.9 °C, reflecting local hydrological conditions, aquifer characteristics, and seasonal variability. Electrical conductivity (EC) ranged between 41 μS/cm and 2062 μS/cm, determined by both hydrogeological settings and anthropogenic impacts such as winter road salting. The pH values showed moderate variability, remaining mostly within neutral levels. These results emphasize the importance of continued monitoring and further research of Medvednica springs, in order to highlight their importance and to preserve their ecological and hydrological roles. Full article

This paper presents a data-driven energy management scheme for fuel cell and battery electric vehicles, formulated as a constrained optimal control problem. The proposed method employs a co-state network trained using real-time measurements to estimate the control law without requiring prior knowledge of the system model or a complete dataset across the full operating domain. In contrast to conventional reinforcement learning approaches, this method avoids the issue of high dimensionality and does not depend on extensive offline training. Robustness is demonstrated by treating uncertain and time-varying elements, including power consumption from air conditioning systems, variations in road slope, and passenger-related demands, as unknown disturbances. The desired state of charge is defined as a reference trajectory, and the control input is computed while ensuring compliance with all operational constraints. Validation results based on a combined driving profile confirm the effectiveness of the proposed controller in maintaining the battery charge, reducing fluctuations in fuel cell power output, and ensuring reliable performance under practical conditions. Comparative evaluations are conducted against two benchmark controllers: one designed to maintain a constant state of charge and another based on a soft actor–critic learning algorithm. Full article

The Chinese red panda (Ailurus styani) is a rare and endangered animal in China; the increase in global temperature and the interference of human activities have caused irreversible effects on the suitable habitat of wild red pandas and threatened their survival. Therefore, it is necessary to carry out scientific research and protection for Chinese red pandas. In this study, the MaxEnt model was used to predict and analyze the suitable habitats of Chinese red pandas in the large and small Xiangling Mountains. The results showed that the main ecological factors affecting the suitable habitat distribution of Chinese red pandas in the Daxiangling Mountains are the average slope (45.6%, slope), the distance from the main road (24.2%, road), and the average temperature in the coldest quarter (11%, bio11). The main ecological factors affecting the suitable habitat distribution of Chinese red pandas in the Xiaoxiangling Mountains are bamboo distribution (67.4%, bamboo), annual temperature range (20.7%, bio7), and the average intensity of human activities (8.7%, Human Footprint). The predicted suitable habitat area of the Daxiangling Mountains is 123.835 km², and the predicted suitable habitat area of the Xiaoxiangling Mountains is 341.873 km². The predicted suitable habitat area of the Daxiangling Mountains accounts for 43.45% of the total mountain area, and the predicted suitable habitat area of the Xiaoxiangling Mountains accounts for 71.38%. The suitable habitat area of the Xiaoxiangling Mountains is nearly three times that of the Daxiangling Mountains, and the proportion of suitable habitat area of the Xiaoxiangling Mountains is much higher than that of the Daxiangling Mountains. The suitable habitat of Chinese red pandas in the Daxiangling Mountains is mainly distributed in the southeast, and the habitat is coherent but fragmented. The suitable habitat of Chinese red panda in Xiaoxiangling Mountains is mainly distributed in the east, and the habitat is more coherent. The results of this study can provide a scientific basis for the protection of the population and habitat of Chinese red pandas in Sichuan. Full article

This study applies the Weighted Overlay Analysis (WOA) method integrated with GIS to assess landslide susceptibility along Al Figrah Road in Al-Madinah Al-Munawarah, western Saudi Arabia. Seven key conditioning factors, elevation, slope, aspect, drainage density, lithology, soil type, and precipitation were integrated using high-resolution remote sensing data and expert-assigned weights. The output susceptibility map categorized the region into three zones: low (93.5 million m²), moderate (271.2 million m²), and high risk (33.1 million m²). Approximately 29% of the road corridor lies within the low-risk zone, 48% in the moderate zone, and 23% in the high-risk zone. Ten critical sites with potential landslide activity were detected along the road, correlating well with the high-risk zones on the map. Structural weaknesses in the area, such as faults, joints, foliation planes, and shear zones in both igneous and metamorphic rock units, were key contributors to slope instability. The findings offer practical guidance for infrastructure planning and geohazard mitigation in arid, mountainous environments and demonstrate the applicability of WOA in data-scarce regions. Full article

On 20 April 2024, an extreme rainfall event occurred in Jiangwan Town Shaoguan City, Guangdong Province, China, where a historic 24 h precipitation of 206 mm was recorded. This triggered extensive landslides that destroyed residential buildings, severed roads, and drew significant societal attention. Rapid acquisition of landslide inventories, distribution patterns, and key controlling factors is critical for post-disaster emergency response and reconstruction. Based on high-resolution Planet satellite imagery, landslide areas in Jiangwan Town were automatically extracted using the Normalized Difference Vegetation Index (NDVI) differential method, and a detailed landslide inventory was compiled. Combined with terrain, rainfall, and geological environmental factors, the spatial distribution and causes of landslides were analyzed. Results indicate that the extreme rainfall induced 1426 landslides with a total area of 4.56 km², predominantly small-to-medium scale. Landslides exhibited pronounced clustering and linear distribution along river valleys in a NE–SW orientation. Spatial analysis revealed concentrations on slopes between 200–300 m elevation with gradients of 20–30°. Four machine learning models—Logistic Regression, Support Vector Machine (SVM), Random Forest (RF), and Extreme Gradient Boosting (XGBoost)—were employed to assess landslide susceptibility mapping (LSM) accuracy. RF and XGBoost demonstrated superior performance, identifying high-susceptibility zones primarily on valley-side slopes in Jiangwan Town. Shapley Additive Explanations (SHAP) value analysis quantified key drivers, highlighting elevation, rainfall intensity, profile curvature, and topographic wetness index as dominant controlling factors. This study provides an effective methodology and data support for rapid rainfall-induced landslide identification and deep learning-based susceptibility assessment. Full article

This study proposes a design method for near-slope roads along multi-level slopes that integrates excavation requirements and post-construction ecological restoration through sprayed eco-protection. Firstly, the design principles and procedural steps for near-slope roads are established. The planar layouts of multi-level slopes are categorized, including mixing areas, turnaround areas, berms, and access ramps. Critical technical parameters, such as curve radii and widths of berms and ramps, as well as dimensional specifications for turnaround areas, are systematically formulated with corresponding design formulas. The methodology is applied to the ecological restoration project of multi-level slopes in the Huamahu mountainous area, and a comparative technical-economic analysis is conducted between the proposed design and the original scheme. Results demonstrate that the optimized design reduces additional maintenance costs caused by near-slope roads by 6.5–8.0% during the curing period. This research advances the technical framework for multi-level slope governance and enhances the ecological design standards for slope protection engineering. Full article

Water migration occurs in unsaturated loess subgrade due to extreme rainfall, making it prone to subgrade subsidence and other water damage disasters, which seriously impact road safety and sustainable development of the Loess Plateau. The study performed a rainfall test using a compacted loess subgrade model based on a self-developed water migration test device. The effects of extreme rainfall on the water distribution, wetting front, and infiltration rate in the subgrade were systematically explored by setting three rainfall intensities (4.6478 mm/h, 9.2951 mm/h, and 13.9427 mm/h, namely J1 stage, J2stage, and J3 stage), and a lateral water migration model was proposed. The results indicated that the range of water content change areas constantly expands as rainfall intensity and time increase. The soil infiltration rate gradually decreased, and the ratio of surface runoff to infiltration rainfall increased. The hysteresis of lateral water migration refers to the physical phenomenon in which the internal water response of the subgrade is delayed in time and space compared to changes in boundary conditions. The sensor closest to the side of the slope changed first, with the most significant fluctuations. The farther away from the slope, the slower the response and the smaller the fluctuation. The bigger the rainfall intensity, the faster the wetting front moved horizontally. The migration rate at the slope toe is the highest. The migration rate of sensor W3 increased by 66.47% and 333.70%, respectively, in the J3 stage compared to the J2 and J1 stages. The results of the model and the measured data were in good agreement, with the R² exceeding 0.90, which verifies the reliability of the model. The study findings are important for guiding the prevention and control of disasters caused by water damage to roadbeds in loess areas. Full article

Xylosalsola chiwensis (Popov) Akhani & Roalson is listed in the Red Data Book of Kazakhstan as a rare species with a limited distribution, occurring in small populations in Kazakhstan, Uzbekistan, and Turkmenistan. The aim of this study is to deepen the understanding of the ecological conditions of its habitats, the floristic composition of its associated plant communities, the species’ morphological and anatomical characteristics, and its molecular phylogeny, as well as to identify the main threats to its survival. The ecological conditions of the X. chiwensis habitats include coastal sandy plains and the slopes of chinks and denudation plains with gray–brown desert soils and bozyngens on the Mangyshlak Peninsula and the Ustyurt Plateau at altitudes ranging from −3 to 270 m above sea level. The species is capable of surviving in arid conditions (less than 100 mm of annual precipitation) and under extreme temperatures (air temperatures exceeding 45 °C and soil surface temperatures above 65 °C). In X. chiwensis communities, we recorded 53 species of vascular plants. Anthropogenic factors associated with livestock grazing, industrial disturbances, and off-road vehicle traffic along an unregulated network of dirt roads have been identified as contributing to population decline and the potential extinction of the species under conditions of unsustainable land use. The morphometric traits of X. chiwensis could be used for taxonomic analysis and for identifying diagnostic morphological characteristics to distinguish between species of Xylosalsola. The most taxonomically valuable characteristics include the fruit diameter (with wings) and the cone-shaped structure length, as they differ consistently between species and exhibit relatively low variability. Anatomical adaptations to arid conditions were observed, including a well-developed hypodermis, which is indicative of a water-conserving strategy. The moderate photosynthetic activity, reflected by a thinner palisade mesophyll layer, may be associated with reduced photosynthetic intensity, which is compensated for through structural mechanisms for water conservation. The flow cytometry analysis revealed a genome size of 2.483 ± 0.191 pg (2n/4x = 18), and the phylogenetic analysis confirmed the placement of X. chiwensis within the tribe Salsoleae of the subfamily Salsoloideae, supporting its taxonomic distinctness. To support the conservation of this rare species, measures are proposed to expand the area of the Ustyurt Nature Reserve through the establishment of cluster sites. Full article

The Cao’e-Jiaojiang-Oujiang River Basin possesses abundant vernacular architectural heritage with significant historical–cultural value. However, challenges like dispersed distribution and inconsistent conservation hinder its systematic protection and utilization within territorial spatial planning, necessitating a deeper understanding of its spatiotemporal patterns. Utilizing 570 identified heritage sites, this study employed ArcGIS spatial analysis (Kernel Density Estimation, Nearest Neighbor Index), correlation analysis with DEM data, and suitability analysis (Minimum Cumulative Resistance model, Gravity Model) to systematically examine spatial distribution characteristics, their evolution, and relationships with the geographical environment and historical context. Results revealed a distinct “four cores and three belts” spatial pattern. Temporally, distribution evolved from “discrete” (Song-Yuan) to “aggregated” (Ming-Qing) and then “diffused” (Modern era). Spatially, heritage showed density in plains, preference for low slopes, and settlement along waterways. Suitability analysis indicated higher corridor potential in the northern section (Cao’e-Jiaojiang) than the south (Oujiang), leading to the identification of a “Northern Segment (Shaoxing-Ningbo-Shengzhou-Taizhou)” and “Southern Segment (Wenzhou-Lishui)” corridor structure. This research provides a scientific basis for systematic conservation and integrated heritage corridor construction of vernacular architectural heritage in the basin, supporting Zhejiang’s Poetry Road Cultural Belt initiatives and cultural heritage protection within territorial spatial planning. Full article

Knowledge of the habitat characteristics of endangered species is an important basis for in situ conservation, release-site selection, and habitat modification. Although the Chinese pangolin (Manis pentadactyla) is one of the world’s most endangered species, little is known about its habitat preferences, and the results of past studies differ greatly. To clarify the habitat characteristics of the Chinese pangolin, we conducted habitat surveys in Guangdong, Jiangxi, and Zhejiang provinces of China using the transect method. A total of 520 burrow sites of Chinese pangolins were recorded in three study areas. The resulting data were analyzed using a generalized additive model, principal coordinate analysis, and Kruskal–Wallis tests. Nine ecological factors (elevation, slope, soil type, canopy coverage, surface coverage, number of trees, number of logs, tree diameter at breast height, and distance to a settlement) were found to affect pangolins’ distribution. Burrows were preferentially distributed at elevations of 50–150 m (62.3%), in silty soil (88.1%), on 20–40° slopes (83.3%), within young and medium-aged broadleaved forests with a canopy coverage exceeding 70% (65.8%), and close to water (less than 300 m). Among the three study regions, pangolin habitats differed significantly in seven environmental factors: elevation, canopy coverage, surface coverage, number of trees, distance to water, distance to a road, and distance to a settlement. Our findings imply that the Chinese pangolin appears to tolerate a broad range of ecological characteristics; however, food resources may be the key factor affecting its habitat selection, and other factors may indirectly affect its distribution by affecting food abundance. Finally, aside from hunting, a low level of human disturbance does not affect the presence of this species. Full article

This study investigates rural settlement patterns and land suitability in Rwanda’s Western Highlands, a mountainous region highly vulnerable to geohazards like landslides and flooding. Its primary aim is to inform sustainable, climate-resilient development planning in this fragile landscape. We employed high-resolution satellite imagery, a Digital Elevation Model (DEM), and comprehensive geospatial datasets to analyze settlement distribution, using Thiessen polygons for influence zones and Kernel Density Estimation (KDE) for spatial clustering. The Analytic Hierarchy Process (AHP) was integrated with the GeoDetector model to objectively weight criteria and analyze settlement pattern drivers, using population density as a proxy for human pressure. The analysis revealed significant spatial heterogeneity in settlement distribution, with both clustered and dispersed forms exhibiting distinct exposure levels to environmental hazards. Natural factors, particularly slope gradient and proximity to rivers, emerged as dominant determinants. Furthermore, significant synergistic interactions were observed between environmental attributes and infrastructure accessibility (roads and urban centers), collectively shaping settlement resilience. This integrative geospatial approach enhances understanding of complex rural settlement dynamics in ecologically sensitive mountainous regions. The empirically grounded insights offer a robust decision-support framework for climate adaptation and disaster risk reduction, contributing to more resilient rural planning strategies in Rwanda and similar Central African highland regions. Full article