U.S. Civil Air Show Crashes, 1993 to 2013

Ballard, Sarah-Blythe; Osorio, Victor B.

doi:10.3141/2471-01

Cited by 6 publications

(3 citation statements)

References 14 publications

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“…The evacuation decision making during a hurricane is quite complex, requiring to consider different dimensions of evacuee behavior, such as the route choice, evacuation mode, choice of safe destination or mobilization time. There are extensive existing studies along this line and particularly notable are the work by Sadri et al [ 66 – 69 ] and Hasan et al [ 70 , 71 ]. Since this paper is not about evacuation decision making, but merely documenting the overt behavior (departure time, re-entry time, and location) as evidenced by social media data (tweets), the discussions of the underlying motivations of the route choice, choice of destination, and return time are beyond the scope this paper.…”

Section: Limitationsmentioning

confidence: 99%

Leveraging Twitter to gauge evacuation compliance: Spatiotemporal analysis of Hurricane Matthew

2017

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Hurricane Matthew was the deadliest Atlantic storm since Katrina in 2005 and prompted one of the largest recent hurricane evacuations along the Southeastern coast of the United States. The storm and its projected landfall triggered a massive social media reaction. Using Twitter data, this paper examines the spatiotemporal variability in social media response and develops a novel approach to leverage geotagged tweets to assess the evacuation responses of residents. The approach involves the retrieval of tweets from the Twitter Stream, the creation and filtering of different datasets, and the statistical and spatial processing and treatment to extract, plot and map the results. As expected, peak Twitter response was reached during the pre-impact and preparedness phase, and decreased abruptly after the passage of the storm. A comparison between two time periods—pre-evacuation (October 2th-4th) and post-evacuation (October 7th-9th)—indicates that 54% of Twitter users moved away from the coast to a safer location, with observed differences by state on the timing of the evacuation. A specific sub-state analysis of South Carolina illustrated overall compliance with evacuation orders and detailed information on the timing of departure from the coast as well as the destination location. These findings advance the use of big data and citizen-as-sensor approaches for public safety issues, providing an effective and near real-time alternative for measuring compliance with evacuation orders.

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Section: Limitationsmentioning

confidence: 99%

Leveraging Twitter to gauge evacuation compliance: Spatiotemporal analysis of Hurricane Matthew

2017

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“…Ballard and Osario [34] provided new public health data about the U.S. civil air shows. Risk factors for fatalities in civil show crashes have been analysed by using the regression methods.…”

Section: Literature Reviewmentioning

confidence: 99%

Multiple Criteria Evaluation and the Inverse Hierarchy Model for Justifying the Choice of Rail Transport Mode

Sivilevičius

Maskeliūnaitė

2018

PROMET

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The choice of a particular mode of transport as an alternative to another one is subjective and usually based on an individual passenger’s approach to the evaluation of advantages and disadvantages of some particular means of transport. The paper presents the methods of analysing the reasons for passengers’ choice of travelling by train as an alternative to using air transport and the results obtained in the research. The 16 criteria (sub-criteria), describing the advantages of travelling by rail over air travel, are defined. The data of the survey questionnaire filled by 52 passengers of the Vilnius–Moscow train and the ranks assigned by them to the considered criteria are described. The average ranks of all 16 criteria and their normalized subjective weights are calculated by using a new method of average rank transformation into weight (ARTIW). The average ranks assigned by the passengers of the train to sub-criteria and the calculated global weights show what criteria are most important. Using the inverse hierarchy model based on the sub-criteria weights, the most and the least important groups of criteria are determined. The institutions and companies engaged in passenger transportation by rail, which give priority to improving the services described by the most important criteria, can make this mode of transport more attractive to people.

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“…Operation in the tightest airspaces can only be permissible when the safety record of a drone category is equal or superior to manned aerial vehicles (MAVs) (General Civil Aviation Authority 2015). Commercial MAV accidents resulting in at least one fatality are 0.73 per million departures (Boeing 2014), though accidents are far more frequent at civil air shows, with 31 crashes per 1000 shows, of which 16 involve fatalities (Ballard and Osorio 2015). Operational reliability of a specific UAS can only be established once a large number of flights have been logged (Stevenson et al 2015) and is therefore currently very limited due to continued innovation of products, and the absence of a requirement for operators to keep log books of all flights.…”

Section: Safety and Aircraft Delaysmentioning

confidence: 99%