Search results for "Natural Hazard"
showing 10 items of 49 documents
Modeling Fire Danger in Galicia and Asturias (Spain) from MODIS images
2014
Forest fires are one of the most dangerous natural hazards, especially when they are recurrent. In areas such as Galicia (Spain), forest fires are frequent and devastating. The development of fire risk models becomes a very important prevention task for these regions. Vegetation and moisture indices can be used to monitor vegetation status; however, the different indices may perform differently depending on the vegetation species. Eight different spectral indices were selected to determine the most appropriate index in Galicia. This study was extended to the adjacent region of Asturias. Six years of MODIS (Moderate Resolution Imaging Spectroradiometer) images, together with ground fire data…
Conduit dynamics and post explosion degassing on Stromboli: A combined UV camera and numerical modeling treatment.
2016
Abstract Recent gas flux measurements have shown that Strombolian explosions are often followed by periods of elevated flux, or “gas codas,” with durations of order a minute. Here we present UV camera data from 200 events recorded at Stromboli volcano to constrain the nature of these codas for the first time, providing estimates for combined explosion plus coda SO2 masses of ≈18–225 kg. Numerical simulations of gas slug ascent show that substantial proportions of the initial gas mass can be distributed into a train of “daughter bubbles” released from the base of the slug, which we suggest, generate the codas, on bursting at the surface. This process could also cause transitioning of slugs i…
A comparison of statistical methods and multi-criteria decision making to map flood hazard susceptibility in Northern Iran
2018
In north of Iran, flood is one of the most important natural hazards that annually inflict great economic damages on humankind infrastructures and natural ecosystems. The Kiasar watershed is known as one of the critical areas in north of Iran, due to numerous floods and waste of water and soil resources, as well as related economic and ecological losses. However, a comprehensive and systematic research to identify flood-prone areas, which may help to establish management and conservation measures, has not been carried out yet. Therefore, this study tested four methods: evidential belief function (EBF), frequency ratio (FR), Technique for Order Preference by Similarity To ideal Solution (TOP…
Using topographical attributes to evaluate gully erosion proneness (susceptibility) in two mediterranean basins: advantages and limitations
2015
Empirical multivariate predictive models represent an important tool to estimate gully erosion susceptibility. Topography, lithology, climate, land use and vegetation cover are commonly used as input for these approaches. In this paper, two multivariate predictive models were generated for two gully erosion processes in San Giorgio basin (Italy) and Mula River basin (Spain) using only topographical attributes as independent variables. Initially, nine models (five for San Giorgio and four for Mula) with pixel sizes ranging from 2 to 50 m were generated, and validation statistics were calculated to estimate the optimal pixel size. The best models were selected based on model performance using…
Assessing and mapping multi-hazard risk susceptibility using a machine learning technique
2020
AbstractThe aim of the current study was to suggest a multi-hazard probability assessment in Fars Province, Shiraz City, and its four strategic watersheds. At first, we construct maps depicting the most effective factors on floods (12 factors), forest fires (10 factors), and landslides (10 factors), and used the Boruta algorithm to prioritize the impact of each respective factor on the occurrence of each hazard. Subsequently, flood, landslides, and forest fire susceptibility maps prepared using a Random Forest (RF) model in the R statistical software. Results indicate that 42.83% of the study area are not susceptible to any hazards, while 2.67% of the area is at risk of all three hazards. T…
Les comportements de protection face au risque naturel : de la résistance à l’engagement
2011
An adequate risk management requires taking into account all the categories of stakeholders, including the exposed populations. Nowadays, one difficulty is to involve these populations and consequently to understand their reactions face to the eventuality of a disaster's occurrence. Several issues must be addressed: how is the representation of risk built up ? How do people develop adaptive strategies towards risk ? And above all, how is it possible to ensure an increase in behaviours suited for prevention and protection ? After drawing up a report on the research in this area, we will discuss the limitations of a persuasive communication, in order to better understand the interest of a bin…
Using Statistical and Computer Models to Quantify Volcanic Hazards
2009
Risk assessment of rare natural hazards, such as large volcanic block and ash or pyroclastic flows, is addressed. Assessment is approached through a combination of computer modeling, statistical modeling, and extreme-event probability computation. A computer model of the natural hazard is used to provide the needed extrapolation to unseen parts of the hazard space. Statistical modeling of the available data is needed to determine the initializing distribution for exercising the computer model. In dealing with rare events, direct simulations involving the computer model are prohibitively expensive. The solution instead requires a combination of adaptive design of computer model approximation…
Human security: an analytical tool for disaster perception research
2015
Purpose – The purpose of this paper is to examine the possible benefits arising from the application of the human security concept to analysing the disaster impacts. Design/methodology/approach – A three-piece human security analytical tool is synthesized by combining the discoveries in human security studies over the last two decades with the perspective of disaster studies focusing on the resilience and securitabilities of the affected societies. To illustrate the merit of the proposed analytical framework a specifically tailored social survey is used to measure the resilience of Ogre’s (Latvia) society after it faces major floods in 2013. It foresees that community’s resilience is inver…
Comparison of machine learning models for gully erosion susceptibility mapping
2020
© 2019 China University of Geosciences (Beijing) and Peking University Gully erosion is a disruptive phenomenon which extensively affects the Iranian territory, especially in the Northern provinces. A number of studies have been recently undertaken to study this process and to predict it over space and ultimately, in a broader national effort, to limit its negative effects on local communities. We focused on the Bastam watershed where 9.3% of its surface is currently affected by gullying. Machine learning algorithms are currently under the magnifying glass across the geomorphological community for their high predictive ability. However, unlike the bivariate statistical models, their structu…
Ground motion phenomena in Caltanissetta (Italy) investigated by InSAR and geological data integration
2008
Urban areas are frequently affected by ground instabilities of various origins. The location of urban zones affected by ground instability phenomena is crucially important for hazard mitigation policies. Satellite-based Interferometric Synthetic Aperture Radar (InSAR) has demonstrated its remarkable capability to detect and quantify ground and building motion in urban areas, especially since the development of Advanced Differential Interferometric SAR techniques (A-DInSAR). In fact, the high density of re.ectors like buildings and infrastructures in urban areas improves the quality of the InSAR signal, allowing sub-centimetric displacements to be reliably detected. The A-DInSAR techniques a…