Advances in Space Research, Journal Year: 2024, Volume and Issue: unknown
Published: Nov. 1, 2024
Language: Английский
Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)
Published: March 6, 2025
The increasing occurrence of geological hazards along roadway infrastructures presents a significant concern. Evaluating hazard susceptibility roads is critical aspect disaster emergency response and rescue efforts. Accurate evaluation outcomes are essential as they play crucial role in mitigating potential financial losses. However, previous studies on treated all samples independent entities, overlooking their spatial interactions. This study introduces novel assessment model termed the multi-kernel density information (MKDI) method. MKDI method integrates value with kernel estimation, effectively capturing dependencies among samples. Furthermore, distinct bandwidths prescribed for various scales disasters to facilitate estimation hazards. integration enables development comprehensive map, complexities distribution. To validate effectiveness proposed method, area selected investigation was G219 National Highway within Zayu County. Various factors were considered mapping, including slope, aspect, profile plan curvature, river road linear densities, peak ground acceleration, seismic spectrum characteristics, lithology, elevation, rainfall, landform. results show that outperformed methods, achieving an AUC 0.99. derived map expected offer scientific basis urban planning, construction, risk management area.
Language: Английский
Citations
1
Advances in Space Research, Journal Year: 2024, Volume and Issue: 74(8), P. 3765 - 3785
Published: July 6, 2024
Language: Английский
Citations
6
Earth Science Informatics, Journal Year: 2025, Volume and Issue: 18(2)
Published: Feb. 1, 2025
Language: Английский
Citations
0
Geological Journal, Journal Year: 2025, Volume and Issue: unknown
Published: Feb. 19, 2025
ABSTRACT Creating accurate and effective Landslide Susceptibility (LS) maps can aid disaster prevention mitigation efforts provide sufficient public safety. The primary aim of this study is to develop an LS map for the Garo Hills region in Meghalaya, India, using weight evidence (WoE), frequency ratio (FR), Shannon entropy (SE) methods. A comprehensive landslide inventory catalogued 98 events from 2000 2023 analysis, nine key geographical environmental parameters were prepared. Conducted multicollinearity correlation analysis identify mitigate collinearity issues between factors. model's performance was analysed through area under curve (AUC) value receiver operating characteristic (ROC) curves three recent landslides. results showed that FR method achieved highest accuracy, with successive rate (SRC) AUC predictive (PRC) values 0.860 0.940, respectively, classified susceptibility at sites as high, moderate, low. WoE effectively identified landslides site high very zones, achieving SRC PRC 0.844 0.915, respectively. SE robust predicting landslide‐prone areas, comparable other methods (0.913), though its (0.771) lower. Developed revealed zones account approximately 10% 3% area, predominantly near roads, steep slopes, higher elevations. information valuable civilians government authorities involved hazard monitoring management.
Language: Английский
Citations
0
Land, Journal Year: 2025, Volume and Issue: 14(3), P. 577 - 577
Published: March 10, 2025
Geological hazards in Southern Sichuan have become increasingly frequent, posing severe risks to local communities and infrastructure. This study aims predict the spatial distribution of potential geological using machine learning models ArcGIS-based analysis. A dataset comprising 2700 known hazard locations Yibin City was analyzed extract key environmental topographic features influencing susceptibility. Several were evaluated, including random forest, XGBoost, CatBoost, with model optimization performed Sparrow Search Algorithm (SSA) enhance prediction accuracy. produced high-resolution susceptibility maps identifying high-risk zones, revealing a distinct pattern characterized by concentration mountainous areas such as Pingshan County, Junlian Gong while plains exhibited relatively lower risk. Among different types, landslides found be most prevalent. The results further indicate strong overlap between predicted zones existing rural settlements, highlighting challenges resilience these areas. research provides refined methodological framework for integrating geospatial analysis prediction. findings offer valuable insights land use planning mitigation strategies, emphasizing necessity adopting “small aggregations multi-point placement” approach settlement Sichuan’s regions.
Language: Английский
Citations
0
Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)
Published: March 21, 2025
Rock collapses induced by extreme rainfall frequently occur along highways in Changbai County, posing serious threats to traffic safety and regional sustainable development. This study introduces a slope-unit zoning approach into the hazard assessment of collapses, integrating UDEC (Universal Distinct Element Code) numerical simulation GIS (Geographic Information System) technology reveal failure mechanism affected areas slopes under conditions. By employing AHP-CV (Analytic Hierarchy Process-Coefficient Variation) combined weighting method, weights nine critical indicators, including elevation, slope, slope direction, NDVI (Normalized Difference Vegetation Index), were quantified. Pearson Type III frequency analysis was used estimate recurrence periods, collapse distribution different probabilities evaluated. The results indicate that extremely high susceptibility are primarily distributed steep with fault development sparse vegetation, accounting for 19.74% total area. Under 100-year return condition, proportion high-hazard increases 38.68%. Increased pore water pressure reduced shear strength joint planes identified as primary causes tensile-collapse composite slopes. model achieved an AUC value 0.908, demonstrating reliability. overcomes limitations traditional grid-unit methods provides scientific insights technical support analysis, assessment, prevention geological disasters
Language: Английский
Citations
0
Remote Sensing of Environment, Journal Year: 2025, Volume and Issue: 322, P. 114712 - 114712
Published: March 23, 2025
Language: Английский
Citations
0
Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)
Published: April 10, 2025
The study of susceptibility to geological hazards is crucial not only for local risk assessment but also understanding global patterns in disaster-prone regions. Geological such as landslides and subsidence are a common threat worldwide, affecting millions people causing significant economic losses annually. Landslides major hazard the Tongling City, Tongguan District, Anhui, China, posing risks infrastructure human activity. This assesses using seven influencing factors, including elevation, slope, aspect, distance faults. Both information value certainty factor (CF) models were applied evaluate region's landslide susceptibility, resulting classification area into five levels. While primary focus, ground collapses observed, though much lesser extent. focuses on interest District. found that: (1) predominantly concentrated within 300 m faults along cut slopes adjacent mountain roads buildings. distribution indicates that both construction activities factors contributing frequent occurrence region; (2) proportion classified high-prone City significant, indicating need focused mitigation efforts. (3) CF can effectively region. under curve (AUC) receiver operating characteristic (ROC) curves used models' performance, with model demonstrating superior evaluation accuracy. emphasizes areas District susceptible landslides, offering critical insights strategies decision-making prevention, treatment, emergency response regions similar conditions.
Language: Английский
Citations
0
Advances in Space Research, Journal Year: 2025, Volume and Issue: unknown
Published: April 1, 2025
Language: Английский
Citations
0
Advances in Space Research, Journal Year: 2024, Volume and Issue: 74(11), P. 5395 - 5416
Published: Aug. 15, 2024
Language: Английский
Citations
1