Flood events cause substantial damage to urban and rural areas. Monitoring water extent during large-scale flooding is crucial in order to identify the area affected and to evaluate damage. During such events, spatial assessments of floodwater may be derived from satellite or airborne sensing platforms. Meanwhile, an increasing availability of smartphones is leading to documentation of flood events directly by individuals, with information shared in real-time using social media. Topographic data, which can be used to determine where floodwater can accumulate, are now often available from national mapping or governmental repositories. In this work, we present and evaluate a method for rapidly estimating flood inundation extent based on a model that fuses remote sensing, social media and topographic data sources. Using geotagged photographs sourced from social media, optical remote sensing and high-resolution terrain mapping, we develop a Bayesian statistical model to estimate the probability of flood inundation through weights-of-evidence analysis. Our experiments were conducted using data collected during the 2014 UK flood event and focus on the Oxford city and surrounding areas. Using the proposed technique, predictions of inundation were evaluated against ground-truth flood extent. The results report on the quantitative accuracy of the multisource mapping process, which obtained area under receiver operating curve values of 0.95 and 0.93 for model fitting and testing, respectively.

Objective: Higher intakes of red and processed meat are associated with poorer health outcomes and negative environmental impacts. Drawing upon a population survey the present paper investigates meat consumption behaviours, exploring perceived impacts for human health, animal welfare and the environment. Design: Structured self-completion postal survey relating to red and processed meat, capturing data on attitudes, sustainable meat purchasing behaviour, red and processed meat intake, plus sociodemographic characteristics of respondents. Setting: Urban and rural districts of Nottinghamshire, East Midlands, UK, drawn from the electoral register. Subjects: UK adults (n 842) aged 18-91 years, 497 females and 345 males, representing a 35·6 % response rate from 2500 randomly selected residents. Results: Women were significantly more likely (P < 0·01) to consume ≤ 1 portion of meat/d compared with men. Females and older respondents (>60 years) were more likely to hold positive attitudes towards animal welfare (P < 0·01). Less than a fifth (18·4 %) of the sample agreed that the impact of climate change could be reduced by consuming less meat, dairy products and eggs. Positive attitudes towards animal welfare were associated with consuming less meat and a greater frequency of 'higher welfare' meat purchases. Conclusions: Human health and animal welfare are more common motivations to avoid red and processed meat than environmental sustainability. Policy makers, nutritionists and health professionals need to increase the public's awareness of the environmental impact of eating red and processed meat. A first step could be to ensure that dietary guidelines integrate the nutritional, animal welfare and environmental components of sustainable diets.

There is no evidence to suggest that wine and tobacco consumption may protect against Alzheimer's disease.

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