An Introduction to the use of Synthetic Aperture Radar (SAR) to Detect Marine oil Spills

Author(s):  
M. B. Kannan
2021 ◽  
Vol 13 (9) ◽  
pp. 1607
Author(s):  
Guannan Li ◽  
Ying Li ◽  
Yongchao Hou ◽  
Xiang Wang ◽  
Lin Wang

Marine oil spill detection is vital for strengthening the emergency commands of oil spill accidents and repairing the marine environment after a disaster. Polarimetric Synthetic Aperture Radar (Pol-SAR) can obtain abundant information of the targets by measuring their complex scattering matrices, which is conducive to analyze and interpret the scattering mechanism of oil slicks, look-alikes, and seawater and realize the extraction and detection of oil slicks. The polarimetric features of quad-pol SAR have now been extended to oil spill detection. Inspired by this advancement, we proposed a set of improved polarimetric feature combination based on polarimetric scattering entropy H and the improved anisotropy A12–H_A12. The objective of this study was to improve the distinguishability between oil slicks, look-alikes, and background seawater. First, the oil spill detection capability of the H_A12 combination was observed to be superior than that obtained using the traditional H_A combination; therefore, it can be adopted as an alternate oil spill detection strategy to the latter. Second, H(1 − A12) combination can enhance the scattering randomness of the oil spill target, which outperformed the remaining types of polarimetric feature parameters in different oil spill scenarios, including in respect to the relative thickness information of oil slicks, oil slicks and look-alikes, and different types of oil slicks. The evaluations and comparisons showed that the proposed polarimetric features can indicate the oil slick information and effectively suppress the sea clutter and look-alike information.


Author(s):  
Ferdinando Nunziata ◽  
Andrea Buono ◽  
Maurizio Migliaccio

Oil spills are adverse events that may be very harmful to ecosystems and food chain. In particular, large sea oil spills are very dramatic occurrence often affecting sea and coastal areas. Therefore the sustainability of oil rig infrastructures and oil transportation via oil tankers are linked to law enforcement based on proper monitoring techniques which are also fundamental to mitigate the impact of such pollution. Within this context, in this study a meaningful showcase is analyzed using remotely sensed measurements collected by the Synthetic Aperture Radar (SAR) operated by the COSMO-SkyMed (CSK) constellation. The showcase presented refers to the Deepwater Horizon (DWH) oil incident that occurred in the Gulf of Mexico in 2010. It is one of the world's largest incidental oil pollution event that affected a sea area larger than 10,000 km2. In this study we exploit, for the first time, dual co-polarization SAR data collected by the Italian CSK X-band SAR constellation showing the key benefits of HH-VV SAR measurements in observing such a huge oil pollution event, especially in terms of the very dense revisit time offered by the CSK constellation.


2021 ◽  
Vol 226 (06) ◽  
pp. 10-17
Author(s):  
Nguyễn Hùng An ◽  
Nguyễn Tiến Phát ◽  
Lương Thị Ngọc Tú

Ngày nay, hiện tượng dầu loang trên biển diễn ra khá phổ biến trên các sông ngòi, biển và gây ra các hậu quả nghiêm trọng cho môi trường nước. Vì vậy, việc phát hiện các vết dầu loang và đưa ra các cảnh báo sớm về hiện tượng này nhận được sự quan tâm rất lớn trong vài thập kỷ gần đây. Thực tế, người ta đã phát triển nhiều thuật toán nhận dạng vết dầu loang trên biển sử dụng ảnh ra đa mặt mở tổng hợp bởi vì chất lượng ảnh ít phụ thuộc vào điều kiện thời tiết, ngày và đêm và có khả năng bắt giữ các sự kiện trên quy mô địa lý rộng lớn. Trong đó, các thuật toán dựa trên ngưỡng khá phổ biến trong thực tế vì thực hiện đơn giản. Tuy nhiên, những thuật toán này nói chung có độ chính xác không cao. Bài báo này đề xuất một thuật toán mới dựa trên ngưỡng để phát hiện vết dầu loang trên biển. Đây là ngưỡng toàn cục được xác định dựa trên phân tích thống kê về cường độ các điểm ảnh và kích thước của ảnh. Các kết quả mô phỏng của thuật toán trên phần mềm Python được so sánh với các phương pháp khác và chứng minh rằng phương pháp đề xuất đã cải thiện đáng kể độ chính xác.


Eos ◽  
2012 ◽  
Vol 93 (16) ◽  
pp. 161-162 ◽  
Author(s):  
Maurizio Migliaccio ◽  
Ferdinando Nunziata ◽  
Carl E. Brown ◽  
Benjamin Holt ◽  
Xiaofeng Li ◽  
...  

Oceanography ◽  
2013 ◽  
Vol 26 (2) ◽  
Author(s):  
Michael Caruso ◽  
Maurizio Migliaccio ◽  
John Hargrove ◽  
Oscar Garcia-Pineda ◽  
Hans Graber

2018 ◽  
Vol 10 (10) ◽  
pp. 3599 ◽  
Author(s):  
Ferdinando Nunziata ◽  
Andrea Buono ◽  
Maurizio Migliaccio

Oil spills are adverse events that may be very harmful to ecosystems and the food chain. In particular, large sea oil spills are very dramatic occurrences that may affect sea and coastal areas. Hence, the sustainability of oil rig infrastructures and oil transportation via oil tankers is linked to law enforcement based on proper monitoring techniques, which are also fundamental to mitigate the impact of such pollution. In this study, a showcase referring to the Deepwater Horizon (DWH) oil incident, one of the world’s largest incidental oil pollution event that occurred in the Gulf of Mexico in 2010 affecting a sea area larger than 10,000 km 2 , is analyzed using remotely-sensed information collected by Synthetic Aperture Radar (SAR). Although, operationally, SAR sea oil slick observation is typically accomplished using C-band VV-polarized SAR imagery, during the DWH oil incident, because of their very dense revisit time, even single-polarization X-band COSMO-SkyMed (CSK) SAR measurements were collected. In this study, we exploit, for the first time, incoherent dual co-polarization SAR data collected by the Italian CSK X-band SAR constellation showing the key benefits of HH-VV SAR measurements in observing such a huge oil pollution event, especially in terms of the very dense revisit time offered by the CSK constellation.


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