310 research outputs found

    Private Outsourced Kriging Interpolation

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    A Cohort Study of Traffic-Related Air Pollution and Mortality in Toronto, Ontario, Canada

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    BackgroundChronic exposure to traffic-related air pollution (TRAP) may contribute to premature mortality, but few studies to date have addressed this topic.ObjectivesIn this study we assessed the association between TRAP and mortality in Toronto, Ontario, Canada.MethodsWe collected nitrogen dioxide samples over two seasons using duplicate two-sided Ogawa passive diffusion samplers at 143 locations across Toronto. We calibrated land use regressions to predict NO2 exposure on a fine scale within Toronto. We used interpolations to predict levels of particulate matter with aerodynamic diameter < or = 2.5 microm (PM(2.5)) and ozone levels. We assigned predicted pollution exposures to 2,360 subjects from a respiratory clinic, and abstracted health data on these subjects from medical billings, lung function tests, and diagnoses by pulmonologists. We tracked mortality between 1992 and 2002. We used standard and multilevel Cox proportional hazard models to test associations between air pollution and mortality.ResultsAfter controlling for age, sex, lung function, obesity, smoking, and neighborhood deprivation, we observed a 17% increase in all-cause mortality and a 40% increase in circulatory mortality from an exposure contrast across the interquartile range of 4 ppb NO2. We observed no significant associations with other pollutants.ConclusionsExposure to TRAP was significantly associated with increased all-cause and circulatory mortality in this cohort. A high prevalence of cardiopulmonary disease in the cohort probably limits inference of the findings to populations with a substantial proportion of susceptible individuals

    Geospatial information infrastructures

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    Manual of Digital Earth / Editors: Huadong Guo, Michael F. Goodchild, Alessandro Annoni .- Springer, 2020 .- ISBN: 978-981-32-9915-3Geospatial information infrastructures (GIIs) provide the technological, semantic,organizationalandlegalstructurethatallowforthediscovery,sharing,and use of geospatial information (GI). In this chapter, we introduce the overall concept and surrounding notions such as geographic information systems (GIS) and spatial datainfrastructures(SDI).WeoutlinethehistoryofGIIsintermsoftheorganizational andtechnologicaldevelopmentsaswellasthecurrentstate-of-art,andreïŹ‚ectonsome of the central challenges and possible future trajectories. We focus on the tension betweenincreasedneedsforstandardizationandtheever-acceleratingtechnological changes. We conclude that GIIs evolved as a strong underpinning contribution to implementation of the Digital Earth vision. In the future, these infrastructures are challengedtobecomeïŹ‚exibleandrobustenoughtoabsorbandembracetechnological transformationsandtheaccompanyingsocietalandorganizationalimplications.With this contribution, we present the reader a comprehensive overview of the ïŹeld and a solid basis for reïŹ‚ections about future developments

    Local spatial regression models : a comparative analysis on soil contamination

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    Spatial data analysis focuses on both attribute and locational information. Local analyses deal with differences across space whereas global analyses deal with similarities across space. This paper addresses an experimental comparative study to analyse the spatial data by some weighted local regression models. Five local regression models have been developed and their estimation capacities have been evaluated. The experimental studies showed that integration of objective function based fuzzy clustering to geostatistics provides some accurate and general models structures. In particular, the estimation performance of the model established by combining the extended fuzzy clustering algorithm and standard regional dependence function is higher than that of the other regression models. Finally, it could be suggested that the hybrid regression models developed by combining soft computing and geostatistics could be used in spatial data analysis

    Rethinking the learning space at work and beyond: The achievement of agency across the boundaries of work-related spaces and environments

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    This paper focuses on the notion of the learning space at work and discusses the extent to which its different configurations allow employees to exercise personal agency within a range of learning spaces. Although the learning space at work is already the subject of extensive research, the continuous development of the learning society and the development of new types of working spaces calls for further research to advance our knowledge and understanding of the ways that individuals exercise agency and learn in the workplace. Research findings suggest that the current perception of workplace learning is strongly related to the notion of the learning space, in which individuals and teams work, learn and develop their skills. The perception of the workplace as a site only for work-specific training is gradually changing, as workplaces are now acknowledged as sites for learning in various configurations, and as contributing to the personal development and social engagement of employees. This paper argues that personal agency is constructed in the workplace, and this process involves active interrelations between agency and three dimensions of the workplace (individual, spatial and organisational), identified through both empirical and theoretical research. The discussion is supported by data from two research projects on workplace learning in the United Kingdom. This paper thus considers how different configurations of the learning space and the boundaries between a range of work-related spaces facilitate the achievement of personal agency

    Geographical Detector-Based Risk Assessment of the Under-Five Mortality in the 2008 Wenchuan Earthquake, China

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    On 12 May, 2008, a devastating earthquake registering 8.0 on the Richter scale occurred in Sichuan Province, China, taking tens of thousands of lives and destroying the homes of millions of people. Many of the deceased were children, particular children less than five years old who were more vulnerable to such a huge disaster than the adult. In order to obtain information specifically relevant to further researches and future preventive measures, potential risk factors associated with earthquake-related child mortality need to be identified. We used four geographical detectors (risk detector, factor detector, ecological detector, and interaction detector) based on spatial variation analysis of some potential factors to assess their effects on the under-five mortality. It was found that three factors are responsible for child mortality: earthquake intensity, collapsed house, and slope. The study, despite some limitations, has important implications for both researchers and policy makers

    Monthly precipitation mapping of the Iberian Peninsula using spatial interpolation tools implemented in a Geographic Information System

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    Premi a l'excel·lĂšncia investigadora. Àmbit de les CiĂšncies Socials. 2008In this study, spatial interpolation techniques have been applied to develop an objective climatic cartography of precipitation in the Iberian Peninsula (583,551 km2). The resulting maps have a 200m spatial resolution and a monthly temporal resolution. Multiple regression, combined with a residual correction method, has been used to interpolate the observed data collected from the meteorological stations. This method is attractive as it takes into account geographic information (independent variables) to interpolate the climatic data (dependent variable). Several models have been developed using different independent variables, applying several interpolation techniques and grouping the observed data into different subsets (drainage basin models) or into a single set (global model). Each map is provided with its associated accuracy, which is obtained through a simple regression between independent observed data and predicted values. This validation has shown that the most accurate results are obtained when using the global model with multiple regression mixed with the splines interpolation of the residuals. In this optimum case, the average R2 (mean of all the months) is 0.85. The entire process has been implemented in a GIS (Geographic Information System) which has greatly facilitated the filtering, querying, mapping and distributing of the final cartography
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