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Coastal Fog Detection Using Visual Sensing


Dian Zhang, Timothy Sullivan, Noel O'Connor, Randy Gillespie, Fiona Regan

Publication Type: 
Refereed Conference Meeting Proceeding
Use of visual sensing techniques to detect low visibility conditions may have a number of advantages when combined with other methods, such as satellite based remote sensing, as data can be collected and processed in real or near real time. Camera-enabled visual sensing can provide direct con- firmation of modelling and forecasting results. Indeed, fog detection, modelling and prediction are a priority for maritime communities and coastal cities due to economic impacts of fog on aviation, marine, and land transportation. Canadian and Irish coasts are particularly vulnerable to dense fog under certain environmental conditions, and offshore installations related to oil and gas production on Grand Bank (off the Canadian East Coast) for example can be adversely affected by weather and sea state conditions. In particular, fog can disrupt the transfer of equipment and people to/from the production platforms by helicopter. Such disruptions create delays and the delays cost money. According to offshore oil and gas industry representatives at a recent workshop on metocean monitoring and forecasting for the NL offshore, there is a real need for improved forecasting of visibility (fog) out to 3 days. The ability to accurately forecast future fog conditions would improve the industrys ability to adjust its schedule of operations accordingly. In addition, it was recognised by workshop participants that the physics of Grand Banks fog formation is not well understood, and that more and better data are needed.
Conference Name: 
Oceans 2015
Oceans 2015
Digital Object Identifer (DOI): 
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Conference Location: 
Research Group: 
Dublin City University (DCU)
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