TY - CHAP
T1 - Coastal fog detection using visual sensing
AU - Zhang, Dian
AU - Sullivan, Timothy
AU - O'Connor, Noel E.
AU - Gillespie, Randy
AU - Regan, Fiona
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/9/17
Y1 - 2015/9/17
N2 - 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 confirmation 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 the Grand Banks (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 Newfoundland and Labrador (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 industry's ability to adjust its schedule of operations accordingly. In addition, it was recognised by workshop participants that the physics of the Grand Banks fog formation is not well understood, and that more and better data are needed. In Europe, an EU COST action fog project, with objectives of reducing economic loss and fatalities, has also been created to develop advanced methods for very short-range forecasts of fog and low clouds. Key research objectives of the project included methods for determining the optimal combination of satellite and ground-based observations and measurement techniques of fog. These data were then used to develop estimates of fog risk at high spatial and temporal resolutions, however the focus was on remote satellite observations rather than local visual sensing systems [1].
AB - 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 confirmation 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 the Grand Banks (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 Newfoundland and Labrador (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 industry's ability to adjust its schedule of operations accordingly. In addition, it was recognised by workshop participants that the physics of the Grand Banks fog formation is not well understood, and that more and better data are needed. In Europe, an EU COST action fog project, with objectives of reducing economic loss and fatalities, has also been created to develop advanced methods for very short-range forecasts of fog and low clouds. Key research objectives of the project included methods for determining the optimal combination of satellite and ground-based observations and measurement techniques of fog. These data were then used to develop estimates of fog risk at high spatial and temporal resolutions, however the focus was on remote satellite observations rather than local visual sensing systems [1].
UR - https://www.scopus.com/pages/publications/84957695890
U2 - 10.1109/OCEANS-Genova.2015.7271683
DO - 10.1109/OCEANS-Genova.2015.7271683
M3 - Chapter
AN - SCOPUS:84957695890
T3 - MTS/IEEE OCEANS 2015 - Genova: Discovering Sustainable Ocean Energy for a New World
BT - MTS/IEEE OCEANS 2015 - Genova
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - MTS/IEEE OCEANS 2015 - Genova
Y2 - 18 May 2015 through 21 May 2015
ER -