SAR Sentinel 1 imaging and detection of palaeo-landscape features in the mediterranean area

The use of satellite radar in landscape archaeology offers great potential for manifold applications, such as the detection of ancient landscape features and anthropogenic transformations. Compared to optical data, the use and interpretation of radar imaging for archaeological investigations is more complex, due to many reasons including that: (i) ancient landscape features and anthropogenic transformations provide subtle signals, which are (ii) often covered by noise; and, (iii) only detectable in specific soil characteristics, moisture content, vegetation phenomenology, and meteorological parameters. In this paper, we assessed the capability of SAR Sentinel 1 in the imaging and detection of palaeo-landscape features in the Mediterranean area of Tavoliere delle Puglie. For the purpose of our investigations, a significant test site (larger than 200 km2) was selected in the Foggia Province (South of Italy) as this area has been characterized for millennia by human frequentation starting from (at least) the Neolithic. The results from the Sentinel 1 (S-1) data were successfully compared with independent data sets, and the comparison clearly showed an excellent match between the S-1 based outputs and ancient anthropogenic transformations and landscape features

Eliciting Dirichlet and Gaussian copula prior distributions for multinomial models

In this paper, we propose novel methods of quantifying expert opinion about prior distributions for multinomial models. Two different multivariate priors are elicited using median and quartile assessments of the multinomial probabilities. First, we start by eliciting a univariate beta distribution for the probability of each category. Then we elicit the hyperparameters of the Dirichlet distribution, as a tractable conjugate prior, from those of the univariate betas through various forms of reconciliation using least-squares techniques. However, a multivariate copula function will give a more flexible correlation structure between multinomial parameters if it is used as their multivariate prior distribution. So, second, we use beta marginal distributions to construct a Gaussian copula as a multivariate normal distribution function that binds these marginals and expresses the dependence structure between them. The proposed method elicits a positive-definite correlation matrix of this Gaussian copula. The two proposed methods are designed to be used through interactive graphical software written in Java

Impact of Tumor Burden Score on Conditional Survival after Curative-Intent Resection for Hepatocellular Carcinoma: A Multi-Institutional Analysis

Background: The impact of tumor burden score (TBS) on conditional survival (CS) among patients undergoing curative-intent resection of hepatocellular carcinoma (HCC) has not been examined to date. Methods: Patients who underwent liver resection of HCC between 2000 and 2017 were identified from a multi-institutional database. The impact of TBS and other clinicopathologic factors on 3-year conditional survival (CS3) was examined. Results: Among 1,040 patients, 263 (25.3%) patients had low TBS, 668 (64.2%) had medium TBS and 109 (10.5%) had high TBS. TBS was strongly associated with OS; 5-year OS was 39.0% among patients with high TBS compared with 61.1% and 79.4% among patients with medium and low TBS, respectively (p < 0.001). While actuarial survival decreased as time elapsed from resection, CS increased over time irrespective of TBS. The largest differences between 3-year actuarial survival and CS3 were noted among patients with high TBS (5-years postoperatively; CS3: 78.7% vs. 3-year actuarial survival: 30.7%). The effect of adverse clinicopathologic factors including high TBS, poor/undifferentiated tumor grade, microvascular invasion, liver capsule involvement, and positive margins on prognosis decreased over time. Conclusions: CS rates among patients who underwent resection for HCC increased as patients survived additional years, irrespective of TBS. CS estimates can be used to provide important dynamic information relative to the changing survival probability after resection of HCC.info:eu-repo/semantics/publishedVersio

Big Earth Data for Cultural Heritage in the Copernicus Era

Digital data is stepping in its golden age characterized by an increasing growth of both classical and emerging big earth data along with trans- and multidisciplinary methodological approaches and services addressed to the study, preservation and sustainable exploitation of cultural heritage (CH). The availability of new digital technologies has opened new possibilities, unthinkable only a few years ago for cultural heritage. The currently available digital data, tools and services with particular reference to Copernicus initiatives make possible to characterize and understand the state of conservation of CH for preventive restoration and opened up a frontier of possibilities for the discovery of archaeological sites from above and also for supporting their excavation, monitoring and preservation. The different areas of intervention require the availability and integration of rigorous information from different sources for improving knowledge and interpretation, risk assessment and management in order to make more successful all the actions oriented to the preservation of cultural properties. One of the biggest challenges is to fully involve the citizen also from an emotional point of view connecting “pixels with people” and “bridging” remote sensing and social sensing

Prevalence and Population Attributable Risk for Chronic Airflow Obstruction in a Large Multinational Study

Rationale: The Global Burden of Disease programme identified smoking, and ambient and household air pollution as the main drivers of death and disability from Chronic Obstructive Pulmonary Disease (COPD).Objective: To estimate the attributable risk of chronic airflow obstruction (CAO), a quantifiable characteristic of COPD, due to several risk factors.Methods: The Burden of Obstructive Lung Disease study is a cross-sectional study of adults, aged≥40, in a globally distributed sample of 41 urban and rural sites. Based on data from 28,459 participants, we estimated the prevalence of CAO, defined as a post-bronchodilator one-second forced expiratory volume to forced vital capacity ratio Measurements and Main Results: Mean prevalence of CAO was 11.2% in men and 8.6% in women. Mean PAR for smoking was 5.1% in men and 2.2% in women. The next most influential risk factors were poor education levels, working in a dusty job for ≥10 years, low body mass index (BMI), and a history of tuberculosis. The risk of CAO attributable to the different risk factors varied across sites.Conclusions: While smoking remains the most important risk factor for CAO, in some areas poor education, low BMI and passive smoking are of greater importance. Dusty occupations and tuberculosis are important risk factors at some sites

Prior distribution elicitation for generalized linear and piecewise-linear models

An elicitation method is proposed for quantifying subjective opinion about the regression coefficients of a generalized linear model. Opinion between a continuous predictor variable and the dependent variable is modelled by a piecewise-linear function, giving a flexible model that can represent a wide variety of opinion. To quantify his or her opinions, the expert uses an interactive computer program, performing assessment tasks that involve drawing graphs and bar-charts to specify medians and other quantiles. Opinion about the regression coefficients is represented by a multivariate normal distribution whose parameters are determined from the assessments. It is practical to use the procedure with models containing a large number of parameters. This is illustrated through practical examples and the benefit from using prior knowledge is examined through cross-validation

A Comparative Analysis of Temporal Changes in Urban Land Use Resorting to Advanced Remote Sensing and GIS in Karaj, Iran and Luxor, Egypt

As many developing countries, Iranian and Egyptian cities are growing in population and physically expanding at a high rate. The uncontrolled scattered construction causes loss of orchards, agricultural lands as well as spatial chaos, traffic congestion and increasing costs of municipal services. As a consequence, this also induces a loss of identity and social characteristics of neighborhoods, poor quality of life and degradation of natural landscapes, etc. To face with these issues, it is important to quantify trend and the rate of land cover conversion in order to support plan for a rational land use policy. The main purpose of this research is to set up low cost and reliable tools useful for the monitoring of the urban growth. In this paper, multi-temporal satellite data (Landsat TM 1984, Landsat TM 1998 and L8 2016) have been analyzed for investigating and assessing the effects of the urban expansion in Karaj (Iran) and Luxor (Egypt). According to the results obtained from change detection analysis, both of the investigated sites clearly exhibit an increasing trend in urban expansion much more evident in the case of Luxor than Karaj area. The integration between remote sensing and GIS and the joint use of analytical methods for quantitative-qualitative assessment enable the identification of changes and the mapping of new planned and unplanned urban construction. The availability of timely information free available from NASA web site and the data processing herein adopted provide useful information for supporting planning and sustainable developing policies

Management of Cultural Heritage Sites Using Remote Sensing Indices and Spatial Analysis Techniques

Sustainable management and exploitation policies as well as suitable conservation and mitigation strategies are mandatory to preserve cultural heritage and to reduce threats, weathering phenomena, and human actions that may produce significant deterioration and alteration of cultural heritage and “its environment”. In this context, remote sensing technologies can offer useful data to timely update information and documentation and set up reliable tools for systematic monitoring of cultural properties. In this study, multi-temporal and multi-sensor satellite data from Corona, Landsat, Spot, Quickbird, and Sentinel-2A have been exploited along with spatial analysis to investigate the area of the Theban temples at west Luxor (Egypt), severely threatened by uncontrolled urban sprawl. The results from our analyses showed that the urban expansion continuously occurred during the whole investigated period causing an increasing in urban areas around (1) 1.316&nbsp;km2 from 1967 to 1984, (2) 1.705&nbsp;km2 from 1984 to 2000, (3) 0.978&nbsp;km2 from 2000 to 2003, (4) 2.314&nbsp;km2 from 2003 to 2011, and (5) 1.377&nbsp;km2 from 2011 to 2017. The random urban expansion caused bad sewage networks and high groundwater depth which in turn affected the archaeological areas directly (as evident on a landscape view) and indirectly by causing changes (growing) in the level of ground water depth and increasing and accelerating weathering phenomena. The quantification and mapping of urban sprawl enabled us not only to quantify and spatially characterize urban sprawl but also to create a model to mitigate the impact and provide some operational recommendations to protect the archaeological site. Outcomes from our analysis pointed out that today the tremendous availability of advanced remote sensing data has opened new prospectives unthinkable several years ago