International journal of disaster risk reduction最新文献

{"title":"Corrigendum to “High-resolution flood susceptibility mapping and exposure assessment in Pakistan: An integrated artificial intelligence, machine learning and geospatial framework” [Int. J. Disaster Risk Reduct. 121 (2025) 105442]","authors":"Mirza Waleed , Muhammad Sajjad","doi":"10.1016/j.ijdrr.2025.105842","DOIUrl":"10.1016/j.ijdrr.2025.105842","url":null,"abstract":"","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":"130 ","pages":"Article 105842"},"PeriodicalIF":4.5,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145217826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Social work during the management of socio-environmental risk: Tensions between the professional and the caring spheres","authors":"María Teresa Alonso Moro ,&nbsp;Lena Dominelli ,&nbsp;María Aránzazu Fernández Rodríguez ,&nbsp;Sandra Dema Moreno","doi":"10.1016/j.ijdrr.2025.105843","DOIUrl":"10.1016/j.ijdrr.2025.105843","url":null,"abstract":"<div><div>The role played by social work in socio-environmental disasters has been studied since the 1970s, although the challenges faced by social workers in carrying out their professional role while also dealing with their care responsibilities in the family context has received insufficient attention. That said, feminist theory demonstrates that the tensions between the professional and family spheres have an impact on both the physical and mental health of women as well as their personal relationships. These effects may be exacerbated when working in disaster contexts. This study explores the work-family tensions experienced by professionals involved in the social work response to the eruption of the Tajogaite volcano on the island of La Palma (Spain, 2021). Qualitative research was carried out to this end through in-depth interviews with 19 participants who worked at different levels of the social intervention system. The findings provide details of the tensions between work and family life, their consequences, and the various personal and collective strategies used by respondents to mitigate them.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":"130 ","pages":"Article 105843"},"PeriodicalIF":4.5,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145217773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A risk-informed approach for combined functionality analysis of buildings and road network under flooding: A case study at Silchar, India","authors":"Mrinal Kanti Sen ,&nbsp;Prem Kumar ,&nbsp;Jahir Iqbal Laskar ,&nbsp;Subhrajit Dutta","doi":"10.1016/j.ijdrr.2025.105845","DOIUrl":"10.1016/j.ijdrr.2025.105845","url":null,"abstract":"<div><div>This study proposes a risk-informed framework to assess the combined functionality of buildings and road network under flooding, with a focus on Silchar, India, during the extreme 2022 flood event. The novel contribution lies in integrating hydrodynamic simulation with spatially distributed functionality state classification and fragility analysis to evaluate infrastructure interdependencies. Results indicate that while 59 % of buildings remained operational, approximately 33 % fell under restricted or non-functional states. Over 70 % of road network nodes and links were classified as Functionality State 3, indicating restricted entry, highlighting critical connectivity disruptions. The combined functionality analysis revealed 78 % of infrastructure being non-functional near failure nodes. Implementation of a levee system reduced non-functional infrastructure by 82 %, demonstrating the model's utility in mitigation planning. Fragility analysis, based on digital elevation model data, reveals the probability of infrastructure functionality with varying ground elevations under flood conditions. The proposed framework offers a scalable tool for flood resilience planning in urban areas by incorporating interdependent infrastructure functionality.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":"130 ","pages":"Article 105845"},"PeriodicalIF":4.5,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145217771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of experiencing the destructive 6 February 2023 earthquakes in Türkiye on household preparedness and its determinants: A quasi-experimental study in Istanbul","authors":"Sidika Tekeli-Yesil ,&nbsp;Ayse Nuray Karanci ,&nbsp;Canay Doğulu ,&nbsp;Gözde Ikizer ,&nbsp;Yasemin Erol ,&nbsp;Bülent Özmen","doi":"10.1016/j.ijdrr.2025.105841","DOIUrl":"10.1016/j.ijdrr.2025.105841","url":null,"abstract":"<div><div>This study investigates how the February 6, 2023, earthquakes affected household preparedness and its psychosocial factors in İstanbul while also identifying factors that influence taking further precautions afterwards. Utilising a quasi-experimental design, the dataset includes pre- and post-earthquake measurements across various socioeconomic backgrounds and earthquake risk zones.</div><div>A 2 x 2 Mixed Design ANOVA was performed to determine the effect of time (before/after the February 6, 2023 earthquakes) on preparedness and psychosocial factors related to preparedness, considering differences in the perceived impact of the earthquakes (Affected and Not Affected). To further explore the impact of the earthquakes on preparedness and to identify which group of factors had the greatest influence on this impact, regression analyses were conducted.</div><div>A significant main effect of time (before/after the February 6, 2023, earthquakes) was found on overall preparedness and its components, except for psychological preparedness. Furthermore, the main effect of time on nearly all psychosocial factors was significant, except for community participation and trust.</div><div>The interaction effect of time and the perceived impact of the disaster on earthquake preparedness was found to be statistically significant in relation to several aspects of earthquake preparedness.</div><div>Taking additional precautions in the aftermath of the disaster was most strongly associated with residing in high-risk areas and having better socioeconomic conditions. Women were more likely to take additional precautions. Action coping was the only psychosocial factor associated with additional precautions.</div><div>These findings highlight a critical opportunity to enhance community resilience and household preparedness following disasters.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":"130 ","pages":"Article 105841"},"PeriodicalIF":4.5,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145217772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"BanglaCalamityMMD: A comprehensive benchmark dataset for multimodal disaster identification in the low-resource Bangla language","authors":"Fatema Tuj Johora Faria ,&nbsp;Mukaffi Bin Moin ,&nbsp;Busra Kamal Rafa ,&nbsp;Swarnajit Saha ,&nbsp;Md. Mahfuzur Rahman ,&nbsp;Khan Md Hasib ,&nbsp;M.F. Mridha","doi":"10.1016/j.ijdrr.2025.105800","DOIUrl":"10.1016/j.ijdrr.2025.105800","url":null,"abstract":"<div><div>The abundance of social media datasets with crisis messages has greatly impacted disaster response and assessment. Extracting vital information from this data is crucial for enhancing situational awareness and enabling rapid decision-making, necessitating robust techniques to filter out misleading and irrelevant content. This study introduces a hybrid multimodal fusion technique that integrates text and image data to identify relevant disaster-related images from social media. It represents a pioneering effort in multimodal disaster identification for the Bangla language, addressing a significant gap where previous research has focused exclusively on English text. To facilitate this leap, We curated the “BanglaCalamityMMD” dataset, which includes 7,903 data points distributed across seven disaster categories such as Earthquake, Flood, Landslides, Wildfires, Tropical Storms, Droughts, and Human Damage, along with a non-disaster category. Our technique employs advanced deep learning methodologies: DisasterTextNet for text-based disaster detection, DisasterImageNet for image-based disaster categorization, and DisasterMultiFusionNet, which combines text and image modalities using fusion techniques like Early Fusion, Late Fusion, and Intermediate Fusion. The system uses Vision Transformer variations to extract visual data and pre-trained BERT models for textual insights. Our multimodal architecture (DisasterMultiFusionNet) significantly outperforms unimodal approaches. The unimodal text-based approach achieves 79.90% accuracy with mBERT, also the image-based approach reaches 78.65% accuracy using Swin Transformer. In comparison, our multimodal technique achieves 85.25% accuracy with Swin Transformer and mBERT (DisasterMultiFusionNet), showing a 5.35% improvement over the best unimodal approach. This highlights the effectiveness of our fusion technique and the reliability of our multimodal framework in enhancing disaster identification accuracy. To our knowledge, this is the first research on multimodal disaster identification in the low-resource Bangla language context.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":"130 ","pages":"Article 105800"},"PeriodicalIF":4.5,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145217753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Alignment between top-down disaster indices and local views on disaster preparedness","authors":"David W. Johnston ,&nbsp;Sundar Ponnusamy ,&nbsp;Rebecca Wickes","doi":"10.1016/j.ijdrr.2025.105840","DOIUrl":"10.1016/j.ijdrr.2025.105840","url":null,"abstract":"<div><div>This study examines whether top-down indices of disaster resilience and vulnerability align with individuals' perceptions of preparedness and coping capacity. Using data from a nationally representative survey of Australians in 2021, we match individuals' self-reported perceptions to two indices: the Vulnerability Index and the Australian Natural Disaster Resilience Index. Regression analyses reveal that these indices, including most of their sub-components, are weakly or inconsistently associated with perceived preparedness and coping capacity. These patterns persist across demographic groups and for individuals with recent disaster experience. The misalignment appears to stem partly from the indices’ strong correlation with area-level socioeconomic status. Although socioeconomic advantage is typically assumed to improve resilience and reduce vulnerability, we find it is not a strong predictor of how prepared or capable people feel. These findings raise questions about how resilience and vulnerability are measured and interpreted, particularly when used to guide policy and funding decisions. We argue that top-down indices and local perceptions capture different dimensions of resilience, and using both in parallel could improve the targeting and effectiveness of resilience-building strategies.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":"130 ","pages":"Article 105840"},"PeriodicalIF":4.5,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145217748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards reliable deep learning for post-disaster damage Assessment: An XAI-based evaluation","authors":"Umut Lagap,&nbsp;Saman Ghaffarian,&nbsp;Sophie Gelinas-Gagne,&nbsp;Jasmin Jilma,&nbsp;Zhiyu Liu,&nbsp;Zhiyuan Luo","doi":"10.1016/j.ijdrr.2025.105839","DOIUrl":"10.1016/j.ijdrr.2025.105839","url":null,"abstract":"<div><div>The increasing frequency and severity of natural hazard-induced disasters necessitate rapid and reliable post-disaster damage detection (PDD) to inform disaster response and recovery. Deep learning (DL) models, when paired with remote sensing (RS) data, have shown potential in this domain, but challenges persist due to limited interpretability and inconsistent reliability, particularly for high-severity damage classes. This study investigates the use of attention mechanisms—Channel Attention (CA), Spatial Attention (SA), and Multihead Attention (MA)—to enhance the accuracy and interpretability of state-of-the-art DL models. Utilizing the xBD dataset, we evaluated eight DL architectures and their attention-augmented configurations, in total 32 model, using explainable AI (XAI) models, i.e., Grad-CAM and Saliency Maps to visualize decision-making processes. Results indicate that models enhanced with MA achieve the highest reliability, with MA_ShallowNetV2 and MA_InceptionV3 achieving accuracies of 81.9 % and 80.0 %, respectively. Grad-CAM analysis demonstrated precise localization of damaged areas, while Saliency Maps revealed well-concentrated pixel-level focus. Specifically, MA generally improved interpretability abd reliability in our evaluation, particularly for identifying high-severity damage levels in post-disaster scenarios. In contrast, models with CA or certain SA configurations struggled with misplaced or diffused attention. These findings underscore the importance of incorporating explainable and interpretable AI approaches in disaster risk management.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":"130 ","pages":"Article 105839"},"PeriodicalIF":4.5,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145217751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing agricultural drought hazard, vulnerability and risk over India","authors":"Gaurav Ganjir ,&nbsp;Manne Janga Reddy ,&nbsp;Subhankar Karmakar","doi":"10.1016/j.ijdrr.2025.105830","DOIUrl":"10.1016/j.ijdrr.2025.105830","url":null,"abstract":"<div><div>India is an agrarian country, and its economy heavily relies on the successful harvest of crops to ensure food security and economic stability. Frequent droughts in different parts of the country have detrimental effects on agriculture by impeding crop productivity and causing huge economic losses to the farming community and associated sectors. Effective management of long-term drought necessitates a thorough evaluation and delineation of drought hazard, vulnerability, and risk. Existing drought analyses over India are often localized, focusing on small regions or specific basins. Hence, there is a critical need to comprehensively understand drought at a national level to develop effective mitigation and adaptation strategies. This study addresses this gap by conducting an extensive, district-level, nationwide assessment of drought risk over India by integrating the drought hazard and vulnerability. The drought hazard estimated by novel kernel density based Modified Multivariate Standardized Drought Index (<em>MMSDI</em>_<em>k</em>), with proposed modified weight and rating schemes, and utilizing data of rainfall, soil moisture and potential evapotranspiration for the study area over a period of 43 years (1980–2022). The drought vulnerability estimated by employing reliable indicators that consider both sensitivity and adaptive capacity. The results of the drought risk study highlighted that Indo-Gangetic plains, parts of the North-India, Central India, and specific regions in the Gujarat, Odisha, and Chhattisgarh states as high-risk areas. Conversely, numerous districts exhibited low to moderate drought risk. The bivariate choropleth risk map highlighted that many regions encounter low hazard and high vulnerability due to the high impact of societal developments rather than climate-invoked changes. The study found that agricultural drought is higher in non-arid regions of India because of the high variability and decreasing trend in the rainfall. The findings can support policymakers in planning region-specific actions for effective drought management, and the proposed framework is generic, can be applied to any other region.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":"130 ","pages":"Article 105830"},"PeriodicalIF":4.5,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145156192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimated average annualized losses from potential building damage and fatalities due to earthquake-generated tsunamis in the United States","authors":"Nathan Wood ,&nbsp;Anne Sheehan ,&nbsp;Doug Bausch ,&nbsp;Cadie Goulette Yeager ,&nbsp;Casey Zuzak ,&nbsp;Jennifer Sims ,&nbsp;Ashley Hoke","doi":"10.1016/j.ijdrr.2025.105838","DOIUrl":"10.1016/j.ijdrr.2025.105838","url":null,"abstract":"<div><div>Earthquake-generated tsunamis represent substantial economic threats to states and territories in the United States (U.S.), but we are unaware of any effort to quantify potential impacts at the national level. This gap is partially due to the lack of nationally consistent data on tsunamigenic sources and associated return periods. This study addresses this issue and provides estimates of average annualized losses (AAL) for potential residential fatalities and capital stock losses associated with building damage (i.e., structural, non-structural, contents, and inventory damage) in the U.S. by curating tsunami-hazard information based on deterministic scenarios and probabilistic approaches, calculating potential losses, and estimating return periods where necessary. This assessment was done for the U.S. West Coast, Alaska, Hawaii, U.S. Pacific Territories, and U.S. Atlantic Territories. We estimate that earthquake-generated tsunamis that could affect these states and territories collectively represent $1 billion in potential AAL with 79 % of losses due to residential fatalities and 21 % of losses due to capital stock losses from building damage. We identify AAL variations based on county and county equivalents, states and territories, geographic regions, return periods, and departure-delay assumptions for evacuating residents. Results include high AAL values for potential fatalities in Puerto Rico and the U.S. Pacific Northwest region, high AAL values for potential building-related damage in Hawaii and California, and high building- and population-loss ratios for county equivalents in Alaska and U.S. territories.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":"130 ","pages":"Article 105838"},"PeriodicalIF":4.5,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145156182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"LCP-GIS method for preventive conservation of heritage structures under wind action","authors":"Elena López-Ortiz ,&nbsp;Jianfei Dong ,&nbsp;Shuang Li ,&nbsp;Paloma Pineda","doi":"10.1016/j.ijdrr.2025.105836","DOIUrl":"10.1016/j.ijdrr.2025.105836","url":null,"abstract":"<div><div>This work provides a new insight by combining LCP tools and GIS techniques to determine wind action flows that allows for identifying vulnerable areas in heritage structures under environmental risky conditions. The method is developed in a GIS environment by using an open-access software that enables transformation and management of environmental data as input layers, the application of assessment tools and open-access plugins to simplify the data processing, and the possibility of easily updating the data. From this LCP-GIS method, graphic representation of at-risk areas and vulnerable structures is obtained. The procedure has been validated by applying it to the Archaeological Ensemble of Baelo Claudia (Cádiz, Spain), a singular Roman city located in one of the windiest coastal areas of Europe. The main outcomes of this research are: (i) new application of LCP analysis for the assessment and simulation of wind flows which can be used to analyse complex heritage structures or sites; (ii) new method to evaluate environmental factors for heritage preventive conservation and risk mitigation; (iii) advances in rapid assessment methods to identify structural vulnerabilities under environmental conditions in large-scale heritage sites and structures; (iv) digital transformation of numerical data into graphical input layers within a GIS environment. The method can be extrapolated and applied in different heritage sites, as an efficient and accurate tool to enhance the resilience of at-risk structures.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":"130 ","pages":"Article 105836"},"PeriodicalIF":4.5,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145217749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}