Search for the Wreckage of Air France Flight AF 447

Stone, Lawrence D.; Keller, Colleen M.; Kratzke, Thomas M.; Strumpfer, Johan P.

doi:10.1214/13-sts420

Cited by 40 publications

(31 citation statements)

References 7 publications

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“…This was, for example, the case in the search for Air France flight 447, which disappeared over the Atlantic Ocean in 2009. Probabilistic maps of the location of the wreckage were successfully used to find the wreckage in 2011, while previous attempts, spanning a 2-year period, all failed (Stone et al, 2014). More specific to flood mapping, information about uncertainties can be used to direct surveys to areas in which the flood extent is highly uncertain.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic flood extent estimates from social media flood observations

Brouwer¹,

Eilander²,

Loenen³

et al. 2017

Nat. Hazards Earth Syst. Sci.

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Abstract. The increasing number and severity of floods, driven by phenomena such as urbanization, deforestation, subsidence and climate change, create a growing need for accurate and timely flood maps. In this paper we present and evaluate a method to create deterministic and probabilistic flood maps from Twitter messages that mention locations of flooding. A deterministic flood map created for the December 2015 flood in the city of York (UK) showed good performance (F (2) = 0.69; a statistic ranging from 0 to 1, with 1 expressing a perfect fit with validation data). The probabilistic flood maps we created showed that, in the York case study, the uncertainty in flood extent was mainly induced by errors in the precise locations of flood observations as derived from Twitter data. Errors in the terrain elevation data or in the parameters of the applied algorithm contributed less to flood extent uncertainty. Although these maps tended to overestimate the actual probability of flooding, they gave a reasonable representation of flood extent uncertainty in the area. This study illustrates that inherently uncertain data from social media can be used to derive information about flooding.

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Section: Introductionmentioning

confidence: 99%

Probabilistic flood extent estimates from social media flood observations

Brouwer¹,

Eilander²,

Loenen³

et al. 2017

Nat. Hazards Earth Syst. Sci.

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show abstract

“…The classical search algorithm when searching for and locating missing objects based on Bayes theorem reads [ Breivik et al ., ; Stone et al ., ]:

p_{p o s t} = p_{p r i o r} \frac{1 - q}{1 - p_{p r i o r} q} < p_{p r i o r} .

…”

Section: Bayesian Search Strategiesmentioning

confidence: 99%

Cost efficient environmental survey paths for detecting continuous tracer discharges

Alendal

2017

JGR Oceans

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Designing monitoring programs for detecting potential tracer discharges from unknown locations is challenging. The high variability of the environment may camouflage the anticipated anisotropic signal from a discharge, and there are a number of discharge scenarios. Monitoring operations may also be costly, constraining the number of measurements taken. By assuming that a discharge is active, and a prior belief on the most likely seep location, a method that uses Bayes' theorem combined with discharge footprint predictions is used to update the probability map. Measurement locations with highest reduction in the overall probability of a discharge to be active can be identified. The relative cost between reallocating and measurements can be taken into account. Three different strategies are suggested to enable cost efficient paths for autonomous vessels.

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“…In psychology, around 28% of Bayesian regression analyses over a quarter of a decade were motivated to use Bayesian to enable computation, or to improve accuracy over Frequentist alternatives . Advances in Bayesian computation have enabled solution of previously intractable problems, in a wide range of contexts such as: the sudden polarisation of magnets (Metropolis, Rosenbluth, Rosenbluth, Teller, and Teller, 1953), analysis of medical imagery (Besag, 1986), search and detection of missing aircraft (Stone, Keller, Kratzke, Strumpfer, et al, 2014), estimating the number of species relying on coral reefs (Fisher, O'Leary, Low-Choy, Mengersen, Knowlton, Brainard, and Caley, 2015), meta-analysis accounting for publication bias and low power (Kim, Belland, and Walker, 2017), accounting for measurement, misclassification and missing values in higher education participation (Goldstein, Browne, and Charlton, 2017).…”

Section: Bridging Via Computationmentioning

confidence: 99%

Using Bayesian statistical modelling as a bridge between quantitative and qualitative analyses: illustrated via analysis of an online teaching tool

Low‐Choy

Riley

Alston-Knox

2017

Educational Media International

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Bayesian methods provide a more general approach to statistical analysis that mathematically includes Null Hypothesis Significance Testing (NHST) and classical statistical modelling as special cases. This expanded, Bayesian, approach provides several benefits, which we illustrate using a case study about decision-making by teachers. We focus on a relatively unexplored topic: the way in which a Bayesian approach provides a 'bridge' between qual/quant methods. We highlight five bridges, illustrated using the case study: (1) visualization of the conceptual framework, (2) generalization via randomization and alternatives, (3) stories for interpretation, (4) computation that is flexible, and (5) continual learning, through priors. This work illustrates these bridges using a case study on a digital tool that wove together: a behavioural study to investigate decision-making, with an inbuilt perceptual component to probe rationale for specific decisions, and an interview component. A mixed method was therefore a natural choice for integrating learnings across these data sources. This online tool inhabits the digital realm of education which enables 'virtual' assessment, and sits midway between theoretical, written pieces and the fully immersed practicums in the classroom. Adopting a similar tool for training in a virtual classroom could provide greater accessibility and privacy, and enhanced feedback through the in situ qual/quant analytics. Thus the digital learning sphere provides a context for raising awareness of the potential that Bayesian statistical paradigm offers researchers who wish to connect qual/quant methods.

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Search for the Wreckage of Air France Flight AF 447

Cited by 40 publications

References 7 publications

Probabilistic flood extent estimates from social media flood observations

Probabilistic flood extent estimates from social media flood observations

Cost efficient environmental survey paths for detecting continuous tracer discharges

Using Bayesian statistical modelling as a bridge between quantitative and qualitative analyses: illustrated via analysis of an online teaching tool

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