6 resultados para submarine landslides

em Digital Commons - Michigan Tech


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With recent advances in remote sensing processing technology, it has become more feasible to begin analysis of the enormous historic archive of remotely sensed data. This historical data provides valuable information on a wide variety of topics which can influence the lives of millions of people if processed correctly and in a timely manner. One such field of benefit is that of landslide mapping and inventory. This data provides a historical reference to those who live near high risk areas so future disasters may be avoided. In order to properly map landslides remotely, an optimum method must first be determined. Historically, mapping has been attempted using pixel based methods such as unsupervised and supervised classification. These methods are limited by their ability to only characterize an image spectrally based on single pixel values. This creates a result prone to false positives and often without meaningful objects created. Recently, several reliable methods of Object Oriented Analysis (OOA) have been developed which utilize a full range of spectral, spatial, textural, and contextual parameters to delineate regions of interest. A comparison of these two methods on a historical dataset of the landslide affected city of San Juan La Laguna, Guatemala has proven the benefits of OOA methods over those of unsupervised classification. Overall accuracies of 96.5% and 94.3% and F-score of 84.3% and 77.9% were achieved for OOA and unsupervised classification methods respectively. The greater difference in F-score is a result of the low precision values of unsupervised classification caused by poor false positive removal, the greatest shortcoming of this method.

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Large parts of the world are subjected to one or more natural hazards, such as earthquakes, tsunamis, landslides, tropical storms (hurricanes, cyclones and typhoons), costal inundation and flooding. Virtually the entire world is at risk of man-made hazards. In recent decades, rapid population growth and economic development in hazard-prone areas have greatly increased the potential of multiple hazards to cause damage and destruction of buildings, bridges, power plants, and other infrastructure; thus posing a grave danger to the community and disruption of economic and societal activities. Although an individual hazard is significant in many parts of the United States (U.S.), in certain areas more than one hazard may pose a threat to the constructed environment. In such areas, structural design and construction practices should address multiple hazards in an integrated manner to achieve structural performance that is consistent with owner expectations and general societal objectives. The growing interest and importance of multiple-hazard engineering has been recognized recently. This has spurred the evolution of multiple-hazard risk-assessment frameworks and development of design approaches which have paved way for future research towards sustainable construction of new and improved structures and retrofitting of the existing structures. This report provides a review of literature and the current state of practice for assessment, design and mitigation of the impact of multiple hazards on structural infrastructure. It also presents an overview of future research needs related to multiple-hazard performance of constructed facilities.

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La Yeguada volcanic complex is one of three Quaternary volcanic centers in Panama, and is located on the southern slope of the Cordillera Central mountain range in western Panama, province of Veraguas. To assess potential geologic hazards, this study focused on the main dome complex near the village of La Laguna and also examined a cinder cone 10 km to the northwest next to the village of Media Luna. Based on newly obtained 40Ar/39Ar ages, the most recent eruption occurred approximately 32 000 years ago at the Media Luna cinder cone, while the youngest dated eruption at the main dome complex occurred 0.357 ± 0.019 Ma, producing the Castillo dome unit. Cerro Picacho is a separate dome located 1.5 km east of the main complex with a date of 4.47 ± 0.23 Ma, and the El Satro Pyroclastic Flow unit surrounds the northern portion of the volcanic complex and has an age of 11.26 ± 0.17 Ma. No Holocene (10 000 years ago to present) activity is recorded at the La Yeguada volcanic complex and therefore, it is unlikely to produce another eruption. The emergence of a new cinder cone is a possibility, but the associated hazards tend to be low and localized, and this does not pose a significant threat to the small communities scattered throughout the area. The main geologic hazard at the La Yeguada volcanic complex is from landslides coming off the many steep slopes.

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Soil erosion is a natural geological phenomenon resulting from removal and transportation of soil particles by water, wind, ice and gravity. As soil erosion may be affected from cultural factors as well. The physical and social phenomena of soil erosion are researched in six communities in the upper part of Rio Grijalva Basin in the vicinity of Motozintla de Mendoza, Chiapas, Mexico. For this study, the USDA RUSLE model was applied to estimate soil erosion rates in the six communities based on the available data. The RUSLE model is based on soil properties, topography, and land cover and management factors. These results showed that estimated soil erosion rates ranged from a high of 2,050 metric ton ha-1 yr-1 to a low of 100 metric ton ha-1 yr-1. A survey concerning knowledge, attitudes and practices (KAP) related to soil erosion was also conducted in all 236 households in the six communities. The main findings of the KAP survey were: 69% of respondents did not know what soil erosion was, while over 40% of the population perceived that hurricanes are the biggest factors that cause soil erosion, and about 20 % of the interviewees said that the landslides are the consequences of the soil erosion. People in communities did not perceive cultural factors as important in conservation efforts for reduce vulnerability to erosion; therefore, the results obtained are suggested to be useful for informing efforts to educate stakeholders.

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The municipality of San Juan La Laguna, Guatemala is home to approximately 5,200 people and located on the western side of the Lake Atitlán caldera. Steep slopes surround all but the eastern side of San Juan. The Lake Atitlán watershed is susceptible to many natural hazards, but most predictable are the landslides that can occur annually with each rainy season, especially during high-intensity events. Hurricane Stan hit Guatemala in October 2005; the resulting flooding and landslides devastated the Atitlán region. Locations of landslide and non-landslide points were obtained from field observations and orthophotos taken following Hurricane Stan. This study used data from multiple attributes, at every landslide and non-landslide point, and applied different multivariate analyses to optimize a model for landslides prediction during high-intensity precipitation events like Hurricane Stan. The attributes considered in this study are: geology, geomorphology, distance to faults and streams, land use, slope, aspect, curvature, plan curvature, profile curvature and topographic wetness index. The attributes were pre-evaluated for their ability to predict landslides using four different attribute evaluators, all available in the open source data mining software Weka: filtered subset, information gain, gain ratio and chi-squared. Three multivariate algorithms (decision tree J48, logistic regression and BayesNet) were optimized for landslide prediction using different attributes. The following statistical parameters were used to evaluate model accuracy: precision, recall, F measure and area under the receiver operating characteristic (ROC) curve. The algorithm BayesNet yielded the most accurate model and was used to build a probability map of landslide initiation points. The probability map developed in this study was also compared to the results of a bivariate landslide susceptibility analysis conducted for the watershed, encompassing Lake Atitlán and San Juan. Landslides from Tropical Storm Agatha 2010 were used to independently validate this study’s multivariate model and the bivariate model. The ultimate aim of this study is to share the methodology and results with municipal contacts from the author's time as a U.S. Peace Corps volunteer, to facilitate more effective future landslide hazard planning and mitigation.

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In 1988 a landslide occurred at a construction site in Birmingham, Alabama in which a portion of the construction site required excavating a rock slope with a group of apartments that were located at the top of the slope. During construction, two separate landslides occurred causing one and half of the apartment buildings to collapse downslope. The slope failure was investigated by two firms. One firm investigated the site conditions and the second firm investigated the design of the cut slope. The main concerns in the investigation were (1) the lack of consideration for the existing joint system, (2) using averaged the strength parameters, (3) the possibility of damaging the slope with blasting, and (4) the potential that there were underground mines at the site. The Rocscience program RocPlane was used to model the in situ conditions and the excavation. The model showed that the joint system’s pore water pressure was most likely the main factor in the failure.