Articles tagged with Disaster Management
Researchers have introduced laser reflective tomography to overcome the speed-resolution trade-off in NLOS imaging, achieving kilometer-scale high-resolution imaging without scanning mechanisms. This innovative approach combines single-point detection with multi-angle projection data for accurate scene reconstruction.
A University of Houston engineering professor developed a mathematical model to help decision-makers decide where to spend limited dollars on infrastructure resilience. The model accounts for real-world uncertainty and identifies critical assets to invest in, providing the greatest benefit before disaster strikes.
A study by researchers at Science Tokyo found that non-structural disaster measures in Macau significantly improved coastal resilience and reduced storm-surge impacts. The city's emphasis on evacuation guidance, communication, monitoring systems, and public awareness helped build trust and reduce disaster impacts.
A new study from UC Santa Barbara reveals that the number of roads out of a community may be one of the strongest predictors of wildfire fatalities. Communities with six or fewer exits have a sharp drop in fatalities, while additional roads offer little further protection.
A study using real-time data from the 2024 Noto Peninsula earthquake response found that unclear tasks, command structures, and lack of meal and rest breaks significantly contributed to self-reported fatigue among disaster responders. Fatigue can compromise decision-making, lead to poor care outcomes, and affect public safety.
A new open-source trajectory-planning system, MIGHTY, has been developed by researchers at MIT and the University of Pennsylvania. The system enables robots to generate smooth flight paths while reacting to obstacles in real-time, making it suitable for applications such as search-and-rescue, last-mile delivery, and industrial inspection.
Researchers at the University of Houston have developed an AI-driven framework to extract and analyze historical flood insurance maps, uncovering significant changes in flood hazard areas. The study reveals that flood risks have expanded in two areas and reduced in one, with critical consequences for resilience and exposure.
Researchers from Kyoto University developed a numerical model to evaluate mangrove wave attenuation, revealing that root submersion and water depth significantly impact wave reduction. The study's findings suggest that mangroves can mitigate disasters and help communities adapt to climate change.
A University of Kansas engineer is conducting research on outdated manufactured housing wind-safety codes, which have remained unchanged since 1994. The study uses a hurricane simulator to test the structural response and failure points of manufactured homes under varying wind conditions.
Researchers use machine learning to characterize recovery processes, predict outcomes, and optimize strategies for restoring critical infrastructure systems. The review highlights the potential of reinforcement learning to identify effective repair sequences.
Researchers developed a dynamic optimization model to help NGOs in rural Africa optimize maintenance schedules, reducing downtime and logistics costs. The model achieved significant reductions in maintenance downtime, ranging from 47-62% in Ethiopia and 53% in Malawi.
Researchers have developed a new framework to detect possible damage in concealed cold-formed steel construction framing materials, utilizing ground-penetrating radar and artificial intelligence. The technology allows for rapid detection of damage, enabling inspectors to verify only flagged spots without removing walls or cladding.
Researchers developed a color-guided depth recovery method for non-repetitive LiDAR images to improve real-time crowd monitoring during disasters. The method reconstructs continuous depth structures while preventing over-smoothing and overfilling gaps, achieving improved depth accuracy and structural consistency.
Current early warning systems often fail to lead to action due to varied reactions to general messages. Researchers propose EW4All+U with personalized information based on location, mobility and circumstances. The technology exists, but challenges remain in scaling up solutions.
A Brazilian study developed a new statistical analysis method that better predicts landslide risk. The approach uses the Gaussian distribution to define the weight of each contributing factor objectively. It was validated based on an inventory of landslides in São Paulo, where 65 people were killed.
A new 3D model of the fault beneath the Marmara Sea reveals where a future major earthquake could take place, helping improve earthquake forecasts. The study uses magnetotelluric measurements to identify distinct high-resistivity and low-resistivity zones, shedding light on ongoing processes of fault mechanics.
Nature-based solutions can significantly reduce flood impacts by slowing and absorbing runoff, offering added benefits such as improved air quality and biodiversity. Public awareness and education are key to expanding support for these approaches, with communities needing clear communication about flood risks and benefits.
A newly designed mechanophore, called DAANAC, was developed to provide early warning against mechanical failure while resisting heat and UV. It features a stable and fluorescent diarylacetonitrile radical coupled to an alkoxycarbonyl radical that quenches fluorescence.
A recent study recreated the July 4 flood conditions and found multiple spots upstream where local communities could have placed water level monitors to give early warnings about rising water. The research aims to make those sensors cheap, easily accessible, and open source so anyone can use them.
A study analyzing Medicare claims data found that older adults who lived through Hurricane Harvey had a 3% elevated risk of dying within 1 year. Mortality risk was highest among those with chronic health conditions like Alzheimer's disease, and Black and Hispanic/Latino populations experienced higher mortality risks than other groups.
Researchers developed a three-stage framework to analyze uncertainties in energy transitions, focusing on climate change and institutional inefficiency. The Puerto Rico case study shows that these factors are crucial in determining total system costs.
Researchers will develop strategies to stabilize eroding channels and enhance flood-warning capabilities using artificial intelligence. The partnership aims to improve stormwater management and environmental protection in the region with forecasts suggesting population growth could double by 2050.
Research shows that flooding in delta cities like Shanghai can expand by up to 80% and be much deeper by 2100 due to extreme climate events, sea-level rise and land subsidence. A major adaptation effort is required to raise defences and construct mobile flood barriers.
A comprehensive review of 19 multi-day events found that nearly 70% of reported emergencies were infectious disease outbreaks, with influenza, measles, and meningococcal disease being the top causes. Foodborne illnesses accounted for over one in five incidents, often linked to poor food handling practices.
Researchers develop a novel integrated data model that merges construction and geospatial information standards to manage bridges' 3D geometry data and maintenance records. This framework enables accurate damage location assessment, repair prioritization, and predictive maintenance, leading to improved infrastructure safety and longevity.
The Kansas Flood Mapping Dashboard uses stream gauge data and terrain-based models to generate flood inundation maps, providing critical information for emergency management. The dashboard is a result of collaborative research efforts between KU researchers and state agencies, utilizing science and research for the benefit of the state.
Researchers propose a novel approach to ensure uniform backfilling throughout borehole depth, addressing immediate safety concerns and long-term sustainability. The circulating mixing method improves process parameters and quality control through advanced numerical simulations.
Researchers warn of structural weakening in urban areas as a result of groundwater overexploitation, posing risks to millions of people. Satellite radar data reveals nearly 1.9 million people exposed to subsidence rates greater than 4 millimeters per year.
The game, developed in partnership with Polk County Emergency Management, will force players to grapple with uncertainty and trade-offs in their actions. It aims to add intensity and engagement to traditional training methods, allowing emergency responders to make timely and relevant decisions.
Researchers analyzed power outage data and weather records to identify planning vulnerabilities and criticality as drivers of prolonged local outages. Targeted interventions, such as isolating critical nodes and improving operational flexibility, can reduce customer outages by up to 49.5%.
The CERCat consortium aims to improve the field of catastrophe modeling by uniting academic rigor with practical expertise, driving real-world solutions that enhance disaster resilience. The consortium is prioritizing projects on multihazard fragility curves, wildfire fragility curves, and AI-powered post-disaster damage assessment.
A new framework developed by Cranfield University aims to balance AI's benefits with safety and fairness concerns in disaster response. The study shows the framework outperforms human operators and conventional AI systems, providing 39% higher accuracy across various scenarios.
A team led by Joe Ripberger from the University of Oklahoma aims to create a unified national approach to wildfire warnings. The project will focus on understanding fire and atmospheric interactions, social and behavioral science questions, and building a transdisciplinary network with practitioners and researchers.
The University of Oklahoma is developing an AI-driven framework to predict tree failures before extreme weather events. The TREE-CARE project will integrate advanced technologies with local knowledge to develop solutions that directly benefit communities.
A new UC Berkeley-led study demonstrates how home hardening and defensible space can significantly reduce wildfire risk. The research found that these strategies, when combined, can double the number of homes that survive a blaze and reduce structure losses by up to 50%.
A study by University of New Hampshire researchers found that communities with higher walkability scores experienced a 4% reduction in average pandemic-related mental health deterioration. The study analyzed national census and survey data to measure the impact of walking on mental health during the pandemic.
Climate-related disasters pose significant disruptions to US drug manufacturing facilities, affecting nearly two-thirds of production sites. Researchers assessed the impact of disaster events on counties with US drug production facilities and found that nearly two-thirds were located in areas affected by at least one disaster declaration.
University of Houston researchers are developing an AI-powered dashboard for Florida food pantries, aiming to streamline stakeholder collaboration and distribute resources to families in need. The tool will enable emergency coordinators to respond quickly to spikes in demand, prioritizing the needs of vulnerable populations.
A new study by University of Virginia researchers reveals high rates of posttraumatic stress disorder (PTSD) and major depression among residents exposed to the 2023 chemical spill. The survey of 1,000 adults found elevated psychological toll with half reporting worsening physical health symptoms.
Researchers from Shibaura Institute of Technology used machine learning algorithms to predict bearing layer depth and assess liquefaction risk. The study found that random forest models outperformed others, especially with increasing spatial data density.
A Texas A&M University study reveals that community cohesion prior to a natural disaster is significantly linked to perceived resilience afterward. The research found that explicit strategies for building community trust and increasing volunteerism rates should be added to emergency preparedness programs.
A new framework developed by Northwestern University and UCLA scientists integrates various water-related processes with a machine-learning model to predict landslide threats. The framework identifies three main pathways leading to landslides: intense rainfall, rain on already saturated soils, and melting snow or ice.
The University of Tokyo researchers developed an unmanned aerial vehicle (UAV) that can withstand ocean currents and wind, enabling the acquisition of reliable seafloor measurements. The system achieved a horizontal root mean square error of approximately 1–2 cm, comparable to existing vessel-based systems.
The WUI-NITY simulator, developed by a global collaboration of researchers, visualises bushfire spread and people movement to calculate evacuation times. It has been validated in large-scale community evacuation drills and is freely available online for use by authorities and researchers.
Researchers developed a new equation to predict seismic wave propagation in magma containing crystals and bubbles, revealing how crystal content influences wave velocity and waveform properties. The analysis also showed that bubble content affects attenuation effects, with discernible differences emerging between models.
Researchers developed a new nanomaterial and fiber structure that improves power output of piezoelectric fibers, generating enough electricity to light LEDs or run small devices. The fiber sensor can detect external forces and transmit data wirelessly for real-time landslide detection systems.
A study proposes five action fronts for civil defense units to increase their organizational capacity, including professionalization and resource allocation. Municipalities face challenges such as monitoring urban expansion, lack of financial resources, and social participation.
Researchers from the Norwegian University of Science and Technology built three embankment dams to divert lava flows in Iceland, delaying the molten lava by up to 16 days. The dams were constructed using in situ material and showed promising results in protecting civil society and critical infrastructure.
Exposure to high levels of smoke pollution increases hospitalizations for respiratory diseases in older adults. The study highlights the need for interventions to mitigate the health impacts of wildfire smoke exposure.
A recent analysis found that rates of colorectal cancer diagnoses dropped during Hurricanes Irma and Maria and the COVID-19 pandemic in Puerto Rico, but late-stage diagnoses eventually exceeded expectations. Limited access to cancer screening services due to these disasters likely hindered timely CRC diagnoses.
A new AI-powered training platform is being developed to simulate pipeline incidents and provide real-world scenarios for pipeline operators. The platform will use artificial intelligence to create a realistic environment where teams can practice handling hazardous conditions and responding to emergencies.
A new study reveals that 81% of O’ahu's coastline could experience erosion by 2100, with a further 40% loss happening by 2030. The research used computer models incorporating satellite imagery to predict the seasonal movement of sand, resulting in more severe erosion projections than previous studies.
A new study reveals that two dam failures and flawed risk assessment amplified the Derna Flood, which was nearly twentyfold more destructive than expected. The research highlights the urgent need for improved flood mitigation strategies, especially in dryland regions.
Researchers have shown that earthquakes in the Marmara region transport a large amount of energy towards Istanbul, with most quakes exhibiting an eastward rupture direction. This finding has important implications for urban planning, emergency response, and seismic hazard maps, which will be taken into account in future studies.
A new book by Komla Dzigbede explores the ability of local governments to learn, adapt, and innovate in the face of major crises. The book analyzes disaster preparedness, response, and economic development post-disaster, offering practical lessons for local leaders.
A new study suggests that artificial intelligence can effectively detect wildfires in the Amazon rainforest, using satellite imaging and deep learning. The technology achieved a 93% success rate in training models via datasets of images with and without wildfires.
Researchers at Mizzou have developed a proactive approach using artificial intelligence to address evolving threats against smart grids. The CIBR-Fort system can predict cyberattacks with 91.88% accuracy and defend against them in real-time, enabling scalable security for power grids of the future.