利用星载雷达数据集量化油轮损失的石油——以2018年7月哈尔迪亚港溢油事件为例

S. J. Prasad, T. B. Balakrishnan Nair
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引用次数: 1

摘要

确定海洋含油污染物的溢油体积是进行溢油建模和应急响应的必要条件。一般来说,泄漏污染物的质量是由受损船舶储罐的总量和剩余量计算得出的。阐述了利用星载合成孔径雷达数据集估算溢油污染物数量的方法。合成孔径雷达数据具有穿透云层的能力,不受天气条件的影响,已被广泛用于探测泄漏石油的特征。欧洲空间局和加拿大空间局提供的SAR数据被用来探测溢油,因为它们已被证明适合于探测溢油。2018年7月14日,SSL油轮在加尔各答附近的Haldia港附近发生轻微漏油事件。遇险船舶的地理位置为东经88.775′,北纬21.441′。监测了船舶遇险区域是否有浮油。雷达卫星哨兵-1A的采购计划是从欧洲空间局获得的。据此,哨兵-1A的通行证于2018年7月15日和2018年7月17日在研究地区可用。合成孔径雷达(SAR)数据集根据其可用性从哨兵-1A获得。这些数据集使用Sentinel应用平台(SNAP)工具箱进行处理。SAR数据经过地形校正,自动重新投影雷达场景。下一阶段是进行辐射校准,将振幅转换为强度值。雷达反射率值在Sentinel工具箱中转换为Sigma0强度值。该Sigma0值以netdf格式编写,用于识别浮油。较小强度值的像素被识别并解释为浮油。雷达场景中的浮油区域被认为是不规则的多边形。计算了这些多边形的面积。然后利用溢油污染物的厚度计算溢油的体积。最后计算出污染物的质量。根据SAR数据集,估计在Haldia港附近沉没的SSL船损失了33吨燃料油。本文详细阐述了利用SAR数据集处理船舶油损的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quantification of oil lost from tanker vessel using space borne radar datasets - Case study of Haldia port oil spill, July 2018.
Determining the spilled volume of the marine oil pollutant is an essential requisite for the oil spill modellers and the responders. Generally, the mass of the spilled pollutant is computed from the total quantity and the remaining quantity of the storage tank of the distressed vessel. A method to estimate the quantity of the spilled oil pollutant using the space -borne synthetic aperture radar dataset is elaborated here. The synthetic aperture radar data, its ability to penetrate cloud cover, irrespective of weather conditions, has been widely used to detect the signature of spilt oil. SAR data available from European Space Agency and Canadian Space Agency were used to detect the oil spills as they are proved to be appropriate for oil spill detection. Minor oil spill occured off Haldia Port, off Kolkata from SSL tanker vessel on 14 July 2018. The geographical location of the distressed vessel is 88.775 ′E, 21.441 ′N. The zone of the vessel distress was monitored for oil slicks. The acquisition plan of the Radar satellite Sentinel -1A was obtained from European Space Agency. As per that, the pass of the Sentinel -1A was available on 15 July 2018 and 17 July 2018 for the region of study. The Synthetic Aperture Radar (SAR) datasets were obtained from Sentinel -1A as per their availability. Those datasets were processed using Sentinel Application Platform (SNAP) tool box. The SAR data is subjected to terrain correction, which automatically reprojects the radar scene. The next stage is performing radiometric calibration, which converts the amplitude into intensity values. The radar reflectance values are converted to Sigma0 intensity values in Sentinel tool box. This Sigma0 values were wrote in netcdf format for identifying the oil slicks. The pixels of lesser intensity values are identified and are interpreted for oil slicks. The zone of the oil slicks in the radar scene are considered as irregular polygons. The area of those polygons were computed. Later the volume of the spilled oil is computed using the thickness of the spilled oil pollutant. Finally the mass of the pollutant is computed. It was collectively estimated from the SAR datasets, that, 33 Tons of Fuel oil was lost from SSL vessel that sank off Haldia Port. This paper elaborates in detail about the method of processing SAR dataset and estimating the quantity of oil lost from the vessel using SAR datasets.
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