1,720,963 research outputs found
A comparison between probabilistic approaches for the evaluation of rainfall-induced landslide susceptibility at regional scale
No full textThis paper contributes to the framework of probabilistic modeling of uncertainty. Two probabilistic models for the evaluation of rainfall-induced landslide susceptibility are compared: one based on the Monte Carlo method and the other on the Point Estimate Method (PEM), accounting for the correlation between soil strength properties and using the TRIGRS model (Baum et al., 2002) to assess the Factor of Safety and the distribution of pore pressure. The results are compared in terms of: total amount of time required by the analyses, mean values of the Factor of Safety, probability distribution functions, and Probability of Failure, showing that the PEM is an efficient alternative to the Monte Carlo method, allowing to save time. This is very important, especially when the susceptibility maps are provided for regional scale analysis
An approach for large-scale soil characterization for the application of non-structural landslide risk mitigation
No full textThis paper describes the methodology used to create a database of the physical and mechanical properties of the soils within the Perugia Province, for the application of probabilistic predictive models at large scale. Starting from an extensive data collection from previous geotechnical campaigns, provided by the Civil Protection and Structural Control Office of the Perugia Province, the geostatistic Kriging technique was applied to obtain: (i) a spatial distribution of the mechanical characteristics of the soil within the selected study area, taking into account the collected measurement points and their spatial correlation; (ii) an evaluation of data reliability on the basis of the computed experimental variograms for the main types of soil identified. After this large-scale characterization, an application of the probabilistic physically-based model PG-TRIGRS [SALCIARINI et al., 2017] for rainfall-induced shallow landslide assessment over a selected study area in the Perugia Province is presented, in order to demonstrate the importance of the availability of quantitative and geo-referenced information concerning the mechanical properties of soils to apply predictive tools
Reliable Soil Property Maps over Large Areas: A Case Study in Central Italy
No full textIn this article we present results of a data collection project carried out to create a reliable georeferenced database to characterize the soil types constituting the near surface cover of study areas located in central Italy. The database includes the following features: i) the coordinates of the site investigations; ii) the geotechnical parameters; iii) the shear wave velocity in the upper 30 m of soil; iv) the type of test used to evaluate the geotechnical parameters and the shear wave velocity; and v) the general description of the stratigraphy. Preliminary analyses on the data were performed to determine the average values, the distribution of the measured data over the intervals, and the probability density function that best fits the measured values. Secondly, geostatistical analyses were done to assess the spatial correlation between data. Among the soils considered, only gravels show a low correspondence between the experimental variograms and the mathematical curve fitting them, while for all of the other soils, such agreement is high. Finally, two applications of the newly developed database are proposed. The first one is the development of continuous soil property maps for a selected study area, created from the information included in the database, which is constrained by a discrete amount of information. In the second application approximately the 80 percent of the measured data are considered to provide spatial predictions, which are tested with the remaining 20 percent of the data
A probabilistic model for rainfall—induced shallow landslide prediction at the regional scale
No full textThis paper presents a new probabilistic physically-based computational model (called PG_TRIGRS) for the probabilistic analysis of rainfall-induced landslide hazard at a regional scale. The model is based on the deterministic approach implemented in the original TRIGRS code, developed by Baum et al. (USGS Open File Report 02–424, 2002) and Baum et al. (USGS Open File Report 08–1159, 2008). Its key innovative features are: (a) the application of Ordinary Kriging for the estimation of the spatial distributions of the first two statistical moments of the probability density functions of the relevant soil properties over the entire area, based on limited available information gathered from available information from limited site investigation campaigns, and (b) the use of Rosenblueth’s Point Estimate method as a more efficient alternative to the classical Monte Carlo method for the reliability analysis performed at the single-cell level to obtain the probability of failure associated to a given rainfall event. The application of the PG_TRIGRS code to a selected study area located in the Umbria Region for different idealized but realistic rainfall scenarios has demonstrated the computational efficiency and the accuracy of the proposed methodology, assessed by comparing predicted landslide densities with available field observations reported by the IFFI project. In particular, while the model might fail to identify all individual landslide events, its predictions are remarkably good in identifying the areas of higher landslide density
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Modeling the Effects Induced by the Expected Climatic Trends on Landslide Activity at Large Scale
No full textAbstractTraditionally, slope stability assessments are based on stationary expected extreme rainfalls, provided by the Intensity-Duration-Frequency curves. More recent approaches are based on projected rainfall scenarios, considering the expected climatic trends provided by General Circulation Models (GCMs). The projected rainfalls used in this study have been obtained by climate simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5). Different GCMs emission scenarios (Representative Concentration Pathways 2.6, 4.5, 8.5) and time horizons (e.g., 2010-2039; 2040-2069; 2070-2099) are analysed. In order to fill the scale gap between the spatial resolution of GCMs and the resolution required for impact studies, statistically downscaled climate projections provided by [1,2] are used as input into PG_TRIGRS [3] to predict the effect of climatic change on landslide activity. A hydrological basin located in the Umbria region of central Italy is used as case study
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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