Synthetic aperture radar (SAR) is now commonly used for operational oil spill monitoring. During major spills SAR data from different satellites give an overview of the areas affected and provide information on the direction in which surface oil is drifting. SAR is also used to monitor illegal discharges from ship traffic or offshore operations. In many areas this has helped to reduce oil pollution.
In regions that are relatively cloud free data from optical sensors such as MERIS and MODIS are increasingly used. Combining SAR and optical data makes detection of small spills more reliable and can provide additional information for use in oil spill response during larger spills.
IMPORTANT NOTE: This lesson requires Bilko 3.4 from February 2013 or later, as earlier versions of the software can not open and display all data as described in the lesson.
The most reliable information about oil spills is obtained by combining data from a range of different sensors. SAR and optical data are both used for detecting and mapping surface oil; SAR is the most established because of its ability to 'see' through clouds. By combining the two sensor types it may also be possible to obtain information about relative thickness of the oil, but unless the spill is very large, this requires better spatial resolution than the 250-300m pixels available from MODIS and MERIS. Optical data may also give information about dispersed oil, but this is difficult to distinguish from suspended sediment and coloured dissolved organic matter (CDOM), and requires detailed baseline information from the region. Hence this capability is not yet exploited in operational monitoring of oil spills, although it has been used in post-spill impact assessments.
Detecting the oil and knowing where it is (or was at the time of satellite overpass) is only half the story. Equally important is the ability to predict how a spill will evolve, and where the oil is headed. This allows responsible authorities to direct clean-up activities and protection of sensitive areas and industries. Satellite data are therefore commonly used in conjunction with numerical models capable of predicting how the spill will evolve, and where it will be transported by wind and currents. Satellite data for input into oil spill models include wind and waves from altimetry, scatterometry and SAR, as well is information about current speed and direction derived from altimetry, SST, optical sensors and SAR data.
This lesson shows how ASAR Wide Swath (resolution 75m) and MERIS Full Resolution (300m+) top of atmosphere (TOA) data may be used to detect and characterise surface oil. The images used in the lesson are taken from the Gulf of Mexico oil spill in spring 2011. However, similar images exist from other spills; we have provided some of these as alternatives to those used in the lesson.
Aim and objectives
At the end of the lesson you should be able to
- identify surface oil in SAR images, understand the physical mechanism behind oil -water contrast in SAR data;
- identify surface oil optical images outside the sun-glint zone, and understand how optical data may be used to identify areas of thicker oil;
- identify surface oil in optical sun-glint images and understand why oil appears brighter than the surrounding water;
- combine SAR and optical data for more reliable information about surface oil, its thickness and likely direction of oil spill drift;
- understand the main mechanisms behind oil spill transport and evolution, and how satellite data from other sensors may provide environmental background information that can help predict the fate of the oil;
- appreciate how satellite data may work with oil spill models to aid clean-up and environmental protection measures.
The lesson is divided into five main sections:
- Detecting surface oil using SAR data.
- Detecting surface oil in optical images and obtaining information on oil thickness.
- Combining SAR and optical data to obtain more information.
- Combining SAR and optical data to obtain more information.
- Modelling oil spill transport and evolution (optional)
Files needed to complete the lesson activities
All data and tools needed to complete the lesson activities are listed below. We also provide additional data that may be used to complement or extend the lesson (see alternative and related data sets).
Level 1B Envisat data
The images have been compressed using bzip2 compression to save space. Bilko will open these on the fly, so there is no need to uncompress the images first.
Synthetic aperture radar (SAR) data:
- ASA_WSM_1PNUPA20100429_034542*.N1.bz2: Envisat ASAR Wide Swath (WS) data from the Gulf of Mexico oil spill on 29 April 2010, a week after the Deep Water Horizon accident.
- ASA_WSM_1PNUPA20100525_154716.N1.bz2: Envisat ASAR wide swath (WS) data from the Gulf of Mexico oil spill on 25 May 2010, about 5 weeks after the Deep Water Horizon accident.
Optical L1B (top of atmosphere) data from EnviSat MERIS:
- MER_FR__1PNUPA20100429_ 160409*.N1.bz2: Envisat MERIS Level 1B (TOA) data from roughly the same area just over 12 hours later.
- MER_FR__1PNUPA20100524_161809*.N1.bz2: Envisat MERIS Level 1B (TOA) data from 24 May just over a month after the Deep Water Horizon accident. The image is affected by sun-glint.
Oil spill demos for Google Earth (optional)
RSMAS_oil_spill_modelling_demos: This folder contains a number of kmz files needed for the optional Section 5 of the lesson. They have been produced by the University of Miami's Carthe oil spill team from model output for a period in summer 2012, when conditions were similar to those experienced during the Deepwater Horizon spill. The work is part of an on-going effort to improve the ability of models to predict the movement of oil released from the sea floor in deep water.
NB! To view the model output you will need Google Earth installed on your computer. See http://www.google.com/earth/index.html for information on how to download and use Google Earth.
For more about Carthe, see http://carthe.org/, or https://www.facebook.com/CARTHE.GoMRI.
The lesson downloads contain everything you need to complete the lesson. This includes the data and tools listed above, and three PDF documents:
- Lesson Activities - step by step instructions to carry out hands-on data analysis, brief explanations and questions to test understanding.
- Background - more detailed information on topics included in the lesson.
- Model Answers Answers to the questions posed in the 'Activities' with explanations to enable students to follow the reasoning that led to the model answer.
To download the lesson and data you must be a registered user. If you have not yet done so you can register here. Once your registration is confirmed you can download the lesson after submitting your registered e-mail address below. This will take you to the download page where you can select the documents, tools and data you wish to download.