Works matching IS 0921030X AND DT 2022 AND VI 114 AND IP 3
Results: 63
Changes in rainfall rates and increased number of extreme rainfall events in Rio de Janeiro city.
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- Natural Hazards, 2022, v. 114, n. 3, p. 3833, doi. 10.1007/s11069-022-05545-y
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Study of the impact of ash fallout from the Icelandic volcano Eyjafjöll (2010) on vegetation using MODIS data.
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- Natural Hazards, 2022, v. 114, n. 3, p. 3811, doi. 10.1007/s11069-022-05544-z
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From goods to goats: examining post-disaster livelihood recovery in the aftermath of the Nepal earthquake 2015.
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- Natural Hazards, 2022, v. 114, n. 3, p. 3787, doi. 10.1007/s11069-022-05543-0
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Developing landslide hazard scenario using the historical events for the Kashmir Himalaya.
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- Natural Hazards, 2022, v. 114, n. 3, p. 3763, doi. 10.1007/s11069-022-05542-1
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Hurricane risk perceptions and housing market responses: the pricing effects of risk-perception factors and hurricane characteristics.
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- Natural Hazards, 2022, v. 114, n. 3, p. 3743, doi. 10.1007/s11069-022-05541-2
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CrowdBIG: crowd-based system for information gathering from the earthquake environment.
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- Natural Hazards, 2022, v. 114, n. 3, p. 3719, doi. 10.1007/s11069-022-05540-3
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Controlled blasting design for efficient and sustainable underwater excavation: art meets science!
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- Natural Hazards, 2022, v. 114, n. 3, p. 3701, doi. 10.1007/s11069-022-05539-w
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Experimental study on consolidation and strength properties of tailings with different particle size distribution characteristics.
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- Natural Hazards, 2022, v. 114, n. 3, p. 3683, doi. 10.1007/s11069-022-05537-y
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Community-based assessment of coastal erosion in Lagos, Nigeria.
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- Natural Hazards, 2022, v. 114, n. 3, p. 3657, doi. 10.1007/s11069-022-05536-z
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Spatiotemporal distribution analysis of extreme precipitation in the Huaihe River Basin based on continuity.
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- Natural Hazards, 2022, v. 114, n. 3, p. 3627, doi. 10.1007/s11069-022-05534-1
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Numerical assessment of coastal multihazard vulnerability in Tokyo Bay.
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- Natural Hazards, 2022, v. 114, n. 3, p. 3597, doi. 10.1007/s11069-022-05533-2
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Using short-interval landslide inventories to build short-term and overall spatial prediction models for earthquake-triggered landslides based on machine learning for the 2018 Lombok earthquake sequence.
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- Natural Hazards, 2022, v. 114, n. 3, p. 3575, doi. 10.1007/s11069-022-05532-3
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IEEE 802.11 Wireless sensor network for hazard monitoring and mitigation.
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- Natural Hazards, 2022, v. 114, n. 3, p. 3545, doi. 10.1007/s11069-022-05531-4
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Hotspot and trend analysis of forest fires and its relation to climatic factors in the western Himalayas.
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- Natural Hazards, 2022, v. 114, n. 3, p. 3529, doi. 10.1007/s11069-022-05530-5
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Ground-motion simulation using stochastic finite-fault method combined with a parameter calibration process based on historical seismic data.
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- Natural Hazards, 2022, v. 114, n. 3, p. 3509, doi. 10.1007/s11069-022-05529-y
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A new approach to spatial risk analysis in the long-term (1950–2020) assessment of natural disasters (avalanche, landslide, rockfall, flood) in Turkey.
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- Natural Hazards, 2022, v. 114, n. 3, p. 3471, doi. 10.1007/s11069-022-05528-z
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Effect of model data availability on scour risk of bridges.
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- Natural Hazards, 2022, v. 114, n. 3, p. 3445, doi. 10.1007/s11069-022-05527-0
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Material point method analysis of fluid–structure interaction in geohazards.
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- Natural Hazards, 2022, v. 114, n. 3, p. 3425, doi. 10.1007/s11069-022-05526-1
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Integration of convolutional neural networks for flood risk mapping in Tuscany, Italy.
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- Natural Hazards, 2022, v. 114, n. 3, p. 3409, doi. 10.1007/s11069-022-05525-2
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A first step towards a IoT-based local early warning system for an unsaturated slope in Norway.
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- Natural Hazards, 2022, v. 114, n. 3, p. 3377, doi. 10.1007/s11069-022-05524-3
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Natural hazards and disasters around the Caspian Sea.
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- Natural Hazards, 2022, v. 114, n. 3, p. 2435, doi. 10.1007/s11069-022-05522-5
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Sand liquefaction during the 2021 M 7.4 Maduo earthquake, China.
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- Natural Hazards, 2022, v. 114, n. 3, p. 3359, doi. 10.1007/s11069-022-05521-6
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Modeling landslide susceptibility using data mining techniques of kernel logistic regression, fuzzy unordered rule induction algorithm, SysFor and random forest.
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- Natural Hazards, 2022, v. 114, n. 3, p. 3327, doi. 10.1007/s11069-022-05520-7
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Rockfall danger and risk analysis around a granite inselberg in the Vila Velha city (southeastern Brazil).
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- Natural Hazards, 2022, v. 114, n. 3, p. 3309, doi. 10.1007/s11069-022-05519-0
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Investigation of accidents in the infrastructure triggered by debris flows in Russia.
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- Natural Hazards, 2022, v. 114, n. 3, p. 3293, doi. 10.1007/s11069-022-05518-1
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Determinants of households' livelihood diversification strategies to adapt to natural hazards: evidence from ecologically vulnerable haor region of Bangladesh.
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- Natural Hazards, 2022, v. 114, n. 3, p. 3255, doi. 10.1007/s11069-022-05514-5
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Morphometric analysis of low mountains for mapping flash flood susceptibility in headwaters.
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- Natural Hazards, 2022, v. 114, n. 3, p. 3235, doi. 10.1007/s11069-022-05513-6
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Drought risk assessment in the coupled spatial–temporal dimension of the Sichuan Basin, China.
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- Natural Hazards, 2022, v. 114, n. 3, p. 3205, doi. 10.1007/s11069-022-05512-7
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Flood vulnerability characteristics considering environmental justice and urban disaster prevention plan in Seoul, Korea.
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- Natural Hazards, 2022, v. 114, n. 3, p. 3185, doi. 10.1007/s11069-022-05511-8
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Study on forest fire risk in Conghua district of Guangzhou city based on multi-source data.
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- Natural Hazards, 2022, v. 114, n. 3, p. 3163, doi. 10.1007/s11069-022-05510-9
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Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR) reveals continued ground deformation in and around Metro Manila, Philippines, associated with groundwater exploitation.
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- Natural Hazards, 2022, v. 114, n. 3, p. 3139, doi. 10.1007/s11069-022-05509-2
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Dynamic monitoring of flood disaster based on remote sensing data cube.
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- Natural Hazards, 2022, v. 114, n. 3, p. 3123, doi. 10.1007/s11069-022-05508-3
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Flood risk management in Khorramabad watershed using the DPSIR framework.
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- Natural Hazards, 2022, v. 114, n. 3, p. 3101, doi. 10.1007/s11069-022-05507-4
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Dynamic agricultural drought risk assessment for maize using weather generator and APSIM crop models.
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- Natural Hazards, 2022, v. 114, n. 3, p. 3083, doi. 10.1007/s11069-022-05506-5
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Groundwater-induced seasonal slumps in gullies of the Bação Complex, Southeastern Brazil.
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- Natural Hazards, 2022, v. 114, n. 3, p. 3061, doi. 10.1007/s11069-022-05505-6
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Peak ground acceleration prediction using artificial neural networks for Kachchh, Gujarat, India.
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- Natural Hazards, 2022, v. 114, n. 3, p. 3043, doi. 10.1007/s11069-022-05504-7
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Flood susceptible surface detection using geospatial multi-criteria framework for management practices.
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- Natural Hazards, 2022, v. 114, n. 3, p. 3015, doi. 10.1007/s11069-022-05503-8
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Interpretation of the reactivation of slow-moving landslides based on ring shear tests and monitoring.
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- Natural Hazards, 2022, v. 114, n. 3, p. 2991, doi. 10.1007/s11069-022-05502-9
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Better understanding of climate catastrophe insurance in China: issues and opportunities, international insights, and directions for development.
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- Natural Hazards, 2022, v. 114, n. 3, p. 2969, doi. 10.1007/s11069-022-05501-w
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Meteorological and hydrological drought risks under changing environment on the Wanquan River Basin, Southern China.
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- Natural Hazards, 2022, v. 114, n. 3, p. 2941, doi. 10.1007/s11069-022-05500-x
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An integrated methodology for post-processing ensemble prediction systems to produce more representative extreme water level forecasts: the case of the Río de la Plata estuary.
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- Natural Hazards, 2022, v. 114, n. 3, p. 2927, doi. 10.1007/s11069-022-05499-1
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The role of new-emerging lands on sources of aeolian sand deposits driven by shrinking of the Urmia salt lake.
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- Natural Hazards, 2022, v. 114, n. 3, p. 2901, doi. 10.1007/s11069-022-05498-2
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Assessment of vegetation damage by three typhoons (Bavi, Maysak, and Haishen) in Northeast China in 2020.
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- Natural Hazards, 2022, v. 114, n. 3, p. 2883, doi. 10.1007/s11069-022-05497-3
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A study on the spatial and temporal variation of urban integrated vulnerability in Southwest China.
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- Natural Hazards, 2022, v. 114, n. 3, p. 2855, doi. 10.1007/s11069-022-05496-4
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Who are the actors and what are the factors that are used in models to map forest fire susceptibility? A systematic review.
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- Natural Hazards, 2022, v. 114, n. 3, p. 2417, doi. 10.1007/s11069-022-05495-5
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A fine subsidence information extraction model based on multi-source inversion by integrating InSAR and leveling data.
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- Natural Hazards, 2022, v. 114, n. 3, p. 2839, doi. 10.1007/s11069-022-05494-6
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Seismic and geomorphic assessment for coseismic landslides zonation in tropical volcanic contexts.
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- Natural Hazards, 2022, v. 114, n. 3, p. 2811, doi. 10.1007/s11069-022-05492-8
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Assessment of agricultural drought loss using a skewed grey cloud ordered clustering model.
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- Natural Hazards, 2022, v. 114, n. 3, p. 2787, doi. 10.1007/s11069-022-05491-9
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Sea level perturbations caused by Bora in the northern Adriatic.
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- Natural Hazards, 2022, v. 114, n. 3, p. 3849, doi. 10.1007/s11069-022-05490-w
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Resident perceptions of riverbank erosion and shoreline protection: a mixed-methods case study from Bangladesh.
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- Natural Hazards, 2022, v. 114, n. 3, p. 2767, doi. 10.1007/s11069-022-05489-3
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