1,720,976 research outputs found
Coherence-based prediction of Multi-Temporal InSAR measurement availability for infrastructure monitoring
No full textPredicting the availability of measurement points provided by Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) poses a challenge due to a nonuniform distribution of Persistent Scatterers (PSs). This article introduces a novel method to estimate the availability of MT-InSAR results on buildings and infrastructure networks, eliminating the need for labor-intensive and time-consuming analyses of the entire SAR data stack. The method is based on an analysis of the interferometric coherence decay characteristics and data regarding buildings and transport infrastructure location as inputs to a convolutional neural network. Specifically, a U-Net architecture model was implemented and trained to predict the PS density of Sentinel-1 data. The methodology was applied to a regional-scale analysis of the Dutch infrastructure, resulting in a low 1.06 ± 0.10 mean absolute error in the pixel-based PS count estimation on the test data split, with over 80% of predictions within ± 1 from the actual value. The model achieved high accuracy when applied to a previously unseen dataset, demonstrating strong generalization performance. The proposed workflow, with its notable ability to accurately predict areas lacking measurement points, offers stakeholders a tool to assess the feasibility of applying MT-InSAR for specific structures. Thereby, it enhances infrastructure reliability by addressing a critical need in decision-making processes and improving the applicability of MT-InSAR for structural health monitoring of infrastructure assets
Landslide susceptibility assessment for engineered slopes using statistical and deterministic approaches
No full textLandslides cause hundreds of deaths and billions euros of damage to infrastructure and the environment each year. In order to predict the locations most susceptible to landslides, the field of landslide hazard assessment has gone through a massive development in the last twenty years by introducing a wealth of statistical and geotechnical landslide susceptibility models.However, these efforts have been largely restricted to landslides occurring in natural terrain even though landslides occurring on geotechnical assets on transportation networks can result in even greater consequences. Current risk assessment approaches for earthworks on large transportation networks still largely take form of subjective risk matrices with inputs gathered by visual walkover surveys using data stored in an asset database.This paper shows the application of two distinctive objective landslide susceptibility approaches on a case study of Irish rail. The first is a ‘statistical’, or ‘data-driven’ approach uses logistic regression as a statistical tool to establish the influence of slope-describing variables that have led to landslide occurrence. This approach draws the data from the asset database containing records of slope variables, and the adjoining landslide register. The same asset database is used as a basis for the second, ‘geotechnical’ or ‘deterministic’ approach. In this approach, geometrical and geotechnical properties of each slope are used to carry out probabilistic slope stability analysis, resulting in probability of failure for each slope.Both approaches result in susceptibility zoning for earthwork assets across the network, effectively ranking them in the criticality terms. This study compares the requirements, applicability and outcomes of each approach, and discuss the methods needed for developing each of them into hazard and risk assessments.Geo-engineerin
Quantitative Landslide Susceptibility and Hazard Analysis for Earthworks on Transport Networks
No full textEarthworks such as cuttings and embankments account for a major part of the entire transport network infrastructure. Large parts of that infrastructure in Europe are susceptible to a range of geohazards, landslides being the most prevalent. These landslides frequently result in direct damage to assets, deaths and injuries, while indirectly also leading to traffic disruptions. There is a need therefore to identify critical assets where remediation efforts should be prioritised in order to prevent such events from occurring. Current state of the art practice involves using qualitative risk matrices, where the hazard and consequence components are determined through subjective visual survey observations. Landslide hazard analysis determines the spatial (susceptibility) and temporal probability of landslides of a certain intensity occurring over an observed area. A number of quantitative methods for landslide hazard and risk assessment have been developed recently; generally these methods are considered more effective due to their reduced subjectivity and their consideration of additional factors. A number of studies outline the application of these methods to natural terrain, but to date these methods have not been developed for transport network earthworks. This study presents and compares the results of two landslide susceptibility analysis approaches for cuttings and embankments on a section of Irish Rail network. The first, “geotechnical” approach uses probabilistic slope stability calculations to rank the assets by their reliability index. The second, “statistical” or “data driven” approach, uses logistical regression as a statistical tool to obtain the susceptibility ranking of the earthworks, using the database of previous failures on the network as an input. Furthermore, several methods for obtaining the temporal hazard characteristics are presented and applied, these methodologies combine to provide a full hazard assessment map of the network.Geo-engineerin
Multi-modal risk assessment of slopes
No full textA significant proportion of European rail networks are built upon earthworks that are over one hundred years old. These earthworks are under increased pressure as they have to contend with heavier and more frequent traffic, far outside the scope of their design. To compound this problem further, recent years have seen unpredictable weather patterns develop with prolonged intense rainstorms commonplace. This has led to increased incidence of slope failures along rail networks, as many aged earthworks struggle to withstand such drastic changes in loading. Marginal engineered slopes fail depending on the triggering mechanism which presents itself first. Therefore the failure surface is intrinsically linked to the applied load i.e. surcharge loading will instigate a different type of landslide than prolonged rainfall. Therefore this paper proposes to analyse marginal slopes probabilistically as a system, where multiple slip circles are considered. A multi-modal optimisation algorithm LIPS (locally informed particle swarm optimisation) is used to locate all significant slip circles. In a slope with multiple potential failure surfaces the consequence of failure is not necessarily the same across the different slip surfaces. This paper addresses this deficit by examining the consequence of the different landslides should they occur. When combined with previously calculated probabilities of failure this will entail amount to a full geotechnical risk assessment of engineered slopes.Geo-engineerin
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
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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