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AUTOMATIC CALCULATION OF OIL SLICK AREA FROM MULTIPLE SAR ACQUISITIONS FOR DEEPWATER HORIZON OIL SPILL

机译:深水地平线油泄漏多种SAR采集的自动计算油烟区

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The Deepwater Horizon oil spill occurred in the Gulf of Mexico in April 2010 and became the largest accidental marine oil spill in history. Oil leaked continuously between April 20th and July 15th of 2010, releasing about 780, 000m~(3) of crude oil into the Gulf of Mexico. The oil spill caused extensive economical and ecological damage to the areas it reached, affecting the marine and wildlife habitats along with fishing and tourism industries. For oil spill mitigation efforts, it is important to determine the areal extent, and most recent position of the contaminated area. Satellite-based oil pollution monitoring systems are being used for monitoring and in hazard response efforts. Due to their high accuracy, frequent acquisitions, large area coverage and day-and-night operation Synthetic Aperture Radar (SAR) satellites are a major contributer of monitoring marine environments for oil spill detection. We developed a new algorithm for determining the extent of the oil spill from multiple SAR images, that are acquired with short temporal intervals using different sensors. Combining the multi-polarization data from Radarsat-2 (C-band), Envisat ASAR (C-band) and Alos-PALSAR (L-band) sensors, we calculate the extent of the oil spill with higher accuracy than what is possible from only one image. Short temporal interval between acquisitions (hours to days) allow us to eliminate artifacts and increase accuracy. Our algorithm works automatically without any human intervention to deliver products in a timely manner in time critical operations. Acquisitions using different SAR sensors are radiometrically calibrated and processed individually to obtain oil spill area extent. Furthermore the algorithm provides probability maps of the areas that are classified as oil slick. This probability information is then combined with other acquisitions to estimate the combined probability map for the spill.
机译:2010年4月墨西哥湾发生了深水地平线漏油,成为历史上最大的意外船舶漏油。 2010年4月20日和2010年7月15日在2010年4月20日之间持续泄露,将原油释放到墨西哥湾的780 000 000米〜(3)。该漏油机泄漏对达到的地区造成了广泛的经济和生态损害,影响了海洋和野生动物栖息地以及渔业和旅游业。对于漏油减缓努力,重要的是确定污染区域的区域范围和最近的位置。基于卫星的油污监测系统用于监测和危害反应努力。由于它们的高精度,频繁的采集,大面积覆盖率和日夜操作合成孔径雷达(SAR)卫星是监测漏油检测海洋环境的主要贡献者。我们开发了一种用于确定来自多个SAR图像的漏油泄漏程度的新算法,其使用不同传感器的短时间间隔获取。将来自Radarsat-2(C波段),Envisat Asar(C波段)和Alos-Palsar(L波段)传感器的多极化数据组合,我们计算漏油的程度,比可能的精度更高只有一个图像。收购之间的短时间间隔(小时到几天)允许我们消除伪影并提高精度。我们的算法在没有任何人为干预的情况下自动工作,以及时交付产品。使用不同SAR传感器的采集是辐射校准的,并单独处理,以获得漏油面积范围。此外,该算法提供了被归类为油印的区域的概率图。然后将该概率信息与其他获取组合以估计泄漏的组合概率图。

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