Systematic GPS Manipulation Occuring at Chinese Oil Terminals and Government Installations

Analysis reveals precise location and timing of GPS interference but purpose remains unclear.

Last month, an article in MIT Technology Review described strange GPS anomalies  in Shanghai. I began investigating, and have now found evidence of a novel form of GPS manipulation occuring at at least 20 sites on the Chinese coast during the past year. The majority of these sites are oil terminals, but government installations in Shanghai and Qingdao also show the same striking pattern of interference in GPS positioning. We don’t know the reason for this interference. It may simply be a general security or anti-surveillance system but it is also possible that it is intended to avoid scrutiny of imports of Iranian crude which have recently come under U.S. sanctions. Whatever the intention, we are able to demonstrate here, through analysis of vessel tracking data, that this GPS interference can be pinpointed very precisely in both time and location.

According to the MIT Technology Review article, this phenomenon was first documented by the U.S. flagged container ship Manukai when the vessel entered the port of Shanghai in July. The captain noticed that the vessel’s AIS (Automatic Identification System) appeared to malfunction — vessels on the navigation screen appeared and disappeared without explanation and appeared to move when they were in fact stationary. AIS, originally designed for collision avoidance, transmits vessels’ GPS locations, courses, and speed every few seconds via VHF (very high frequency) radio. These signals are not only picked up by nearby vessels and terrestrial antennas, but some private companies have also launched satellites able to receive these signals. For this analysis we were able to use data made available by two of these companies, Spire and Orbcomm, through our research partnership with Global Fishing Watch.

An investigation by non-profit C4ADS (Center for Advanced Defence Studies) showed that AIS vessel locations from hundreds of ships navigating Shanghai’s Huangpu river were coming up at false locations. Strangely, vessels on the river would have their GPS location jump to a ring of positions appearing on land. And this was not just affecting ships; looking at the cycling and running app STRAVA’s tracking map of cyclists, C4ADS also confirmed that this strange pattern of interference was affecting all GPS receivers.

To further investigate the GPS manipulation documented in Shanghai, I examined AIS position broadcasts from ships in the area. A distinct pattern emerged. Upon approaching the area of interference, a vessel’s broadcast position jumps from the vessel’s true location to a point on land where false AIS broadcasts occur in a ring approximately 200 meters in diameter. Many of the positions within the ring had speeds of precisely 31 knots or 21 knots (much faster than vessels would be moving near dock) and showed a course varying depending on the position within the ring. The GPS anomaly appears to affect vessels once they are a few kilometers out from the center of the ring. Once affected, vessels begin broadcasting seemingly random positions within the ring or from other high speed positions scattered around it.

Image 1. The Chinese cargo ship Huai Hia Ji 1 Hao (yellow) transits southeast on the Huangpu river. Upon nearing the center of GPS interference area the track jumps to the ring on land and to other random positions nearby. Positions from other affected vessels are shown in red. AIS data courtesy Global Fishing Watch / Orbcomm / Spire.

Image 2. GPS interference can be pinpointed based on this ring of false AIS positions. Approximately 200 meters in diameter, many of the positions in the ring had reported speeds near 31 knots (much faster than a normal vessel speed) and a course going counterclockwise around the circle. AIS data courtesy Global Fishing Watch / Orbcomm / Spire.

Because the ring of false AIS broadcasts follows this very specific pattern, I was able to query AIS tracking data to check if there are other locations where these rings are also occurring. The results are striking. This GPS manipulation is occuring not only in Shanghai but has occurred in at least 20 locations in six Chinese cities within the past year. The focus of these apparent GPS manipulation devices is clearly oil terminals (where 16 of the 20 detected locations were observed). But three prominent office buildings in Shanghai and Qingdao are also affected: the Industrial and Commercial Bank of China in Shanghai, the Qingdao tax administration office, and the Qingdao headquarters of the Qingjian industrial group.

Image 3. A ring of false AIS positions marks an apparent GPS interference device deployed in an office building identified as the Qingdao tax administration office. AIS data courtesy Global Fishing Watch / Orbcomm / Spire.

Image 4. Locations of detected GPS manipulation occuring in six Chinese cities in 2019. Interference following this pattern was not found beyond the Chinese coast.

It seems likely that the centers of these rings of false AIS positions actually mark the physical location of some sort of GPS disrupting device. A device having precisely this effect on GPS receivers, including shipborne AIS systems, has not been previously documented, though there have been other cases of GPS blocking and manipulation. Earlier this year C4ADS published a report with details on GPS manipulation clearly being carried out by the Russian government. These Russian systems appeared to have the effect of making all receiving devices within range show some particular location, such as a nearby airport, rather than the true location of the device. This was seen in one striking example of vessels approaching Putin’s alleged palace on the Black Sea coast.

This Chinese system is clearly being deployed both at central government offices and at the much more remote locations of oil terminals. In the case of the government office buildings it seems likely that these GPS disrupting devices were activated as a security measure. Some are only active for a few days, perhaps to coincide with the visit of an important official. However,  the AIS manipulation occuring at oil terminals particularly interests us at SkyTruth: One possible motive for deploying GPS manipulation devices at oil terminals could be recent U.S. sanctions on Chinese companies importing Iranian crude. And the intentional disruption of a navigation safety system, in close proximity to crude oil storage, is a serious concern.

Almost half of the specific locations where these presumed GPS disrupting devices have been deployed are at oil terminals near Dalian in northeast China. In an August analysis, The New York Times matched Planet satellite imagery from June and July with AIS tracking data to show Iranian tankers delivering oil to China in violation of U.S. sanctions. The Financial Times also documented Chinese flagged tankers importing Iranian crude after ship to ship transfers with Iranian tankers.

I took a closer look at exactly how this GPS disruption is affecting vessel tracking in one oil terminal east of Dalian. Here I identified four locations where GPS disrupting devices appear to have been deployed in 2019. I compared AIS vessel position data from March 1, 2019  and September 5, 2019. The differences were dramatic.

These two days showed similar numbers of AIS positions in the area. But on September 5 approximately two-thirds of the vessel positions at dock disappeared and appeared to be replaced by positions orbiting the GPS disrupting devices or scattered randomly in the region. At the same time, it does appear that some normal AIS broadcasts are coming through and that the GPS disruption does not entirely mask all vessel movements in the area.

Image 5. On March 1, 2019 AIS vessel position data around an oil terminal east of Dalian China shows accurate vessel positions and speeds. On that date, none of the four locations of GPS interference were active. Consequently no vessel positions appear on land and stationary vessels are accurately shown with near 0 speeds (green). AIS data courtesy Global Fishing Watch / Orbcomm / Spire.

Image 6. On September 5, 2019 two GPS interference locations were active and this had a dramatic effect on scrambling vessel positions in the area. Many positions now appear orbiting the presumed GPS interference devices and others appear scattered on land. On the water many positions are appearing with very high speeds (over 25 knots, red) and it’s not possible to distinguish true and false locations. However some slow speed positions (green) are appearing at dock where they would be expected, so some AIS broadcasts appear to be unaffected. AIS data courtesy Global Fishing Watch / Orbcomm / Spire.

Image 7. The distribution of AIS speeds in the area is significantly altered by the activation of the GPS interference devices. Above AIS speed distributions are compared between March 1 (left, no GPS interference) and September 5 (right, active GPS interference). On Sept 5 the total number of slow speed positions from docked vessels is greatly reduced and spikes now appear at 21 and 31 knots from positions orbiting the presumed GPS interference devices.

I also examined one individual vessel track to see how it was affected by GPS interference. This is the Chinese flagged tanker Jin Nui Zou which entered the Dalian oil terminal on September 5. Initially a normal track is seen as the vessel approaches the terminal from the southeast. With closer proximity to the presumed interference device, scrambled positions — often with very high speeds — start to appear. Eventually almost all of the vessel’s AIS positions appear in the ring orbiting the interference device.

Image 8. The tanker Jin Niu Zuo approaches an oil terminal east of Dalian on September 5. Initially, positions with normal transit speeds appear (yellow). With closer proximity, scattered high speed positions begin to emerge (red) and eventually most positions appear in the ring surrounding the presumed AIS interference device. AIS data courtesy Global Fishing Watch / Orbcomm / Spire.

The timing of GPS interference at different sites on the Chinese coast can be inferred based on the appearance of AIS positions on land with 21 and 31 knot speeds. Of the 20 locations identified, interference appears earliest at office buildings in Qingdao but only over a couple days (April 17 – 18, 2019). The first GPS interference at oil terminals appears in June and has continued until recently but timing varies by location. Activation of interference at different terminals is intermittent and may be in response to specific events. For instance at an oil terminal near Quanzhou GPS interference appears to have been activated only between September 25th and 27th, 2019.

At the Dalian oil terminals GPS interference appears to have begun in late June 2019. It is possible that this was a reaction to increased scrutiny of crude imports after the U.S. ended exemptions for purchase of Iranian oil on May 2nd. In fact, Dalian is the headquarters of two subsidiaries of Cosco shipping which were sanctioned on September 25 for importing Iranian crude. Based on what can be seen with vessel activity in Dalian, it is clear that GPS interference is not able to entirely mask vessels approaching the terminal. However, it likely would make it impossible to reliably link a vessel’s AIS track with satellite imagery of a vessel discharging crude at dock. While it is not at all clear that GPS interference was intended to obscure shipping activity, we do see that it had a significant impact on AIS tracking and that the interference was specifically concentrated at oil terminals.

In the November article first documenting the strange GPS anomaly in Shanghai, the question was posed whether this was the work of the Chinese state or some other actor like a mafia engaged in smuggling river sand. Based on the very specific characteristics of the GPS manipulation observed and its deployment at high level installations, it seems very likely that the Chinese state is responsible. It remains to be seen whether this is simply a security measure or if GPS manipulation is also being deployed specifically to prevent monitoring of oil imports.

Unusual Behavior by Tankers Near Brazil Oil Spill

The source of the massive oil spill affecting Brazil remains unclear, but unusual tanker activity raises questions.

For months now, oil has been washing up on the beaches of northeast Brazil. The quantity of oil, the large area affected, and the length of time oil has appeared, have generated international news coverage and concern. Government officials, scientists and non-governmental organizations around the world — including SkyTruth — have been trying to identify the source of the pollution; so far, unsuccessfully. Brazilian researchers have identified a likely location for the origin of the spill based on ocean currents. The oil is a heavy consistency that floats below the surface of the water and Brazilian researchers and government officials have claimed that it is likely from Venezuela, although they haven’t published the chemical analysis data to support this.

Photo 1. Heavy oil has been sullying the beaches of northeastern Brazil since early September. The cause remains elusive. [Photo courtesy tvBrasil via Creative Commons license]

At SkyTruth we have been examining available satellite imagery and evaluating some of the theories put forward on the origin of the spill. We haven’t seen any convincing evidence of oil slicks or sources on the images, and we don’t agree with analyses published by others (here and here) that claim to have solved the mystery. I recently decided to take a look at AIS (Automatic Identification System) ship-tracking data in the region that Brazilian researchers identified to be the likely origin of the spill. When I examined the AIS data, I found some unusual behavior by oil tankers passing through the area. 

AIS is a system in which vessels at sea transmit their location at regular intervals via VHF radio. Initially designed for collision avoidance, this location data is also picked up by satellites and provides a global record of vessel movements. I was aided by Global Fishing Watch’s automated modeling of AIS tracks, developed by data scientist Nate Miller, which identifies loitering events, that is, locations where vessels have essentially come to a stop, and are drifting out at sea. Tankers and cargo ships normally maintain a relatively constant transit speed as they are moving from their point of origin to their destination port. Ships may stop out at sea for a number of reasons, including engine problems, waiting for entry authorization at a port, or even at-sea transfers of cargo or refueling. But spending more than 24 hours adrift at sea represents a financial loss for a tanker and would suggest unusual circumstances.

Of hundreds of tankers that moved through the area in the months before the oil was reported, a handful stood out for having lengthy loitering events near the likely area of origin for the spill. One particular tanker, rather than proceeding directly on a course from Spain to Argentina, stopped for two extended periods (each for approximately 14 hours) just within Brazil’s Exclusive Economic Zone (the EEZ area extends up to 200 nautical miles from shore). The tanker I identified with these unusual loitering events is The Amigo, a 133-meter vessel listed as an Asphalt/Bitumen tanker and flagged to the Marshall Islands. 

Figure 1. Tanker loitering events (yellow circles) detected by Global Fishing Watch analytical tools on the coast of northeast Brazil in July and August 2019 (filtered to events longer than 8 hours). Five loitering events near the area thought to be the likely origin of the spill are shown as larger circles and listed in the table below. The AIS track of tanker The Amigo is shown in red. The EEZ boundary marking Brazil’s waters is in green.

We checked for satellite imagery in the area where the vessel was drifting (July 24 – 26) and unfortunately didn’t turn anything up. So any possible association between this tanker and the oil spill is purely speculative. However, some of the circumstances of the vessel’s operation fit with theories on the source of the spill, so we think its activities should be scrutinized further.

The Amigo is an unusual tanker in that it is outfitted to maintain its cargo at high temperature to keep it from solidifying. When the tanker passed through Brazilian waters off Brazil’s northeast coast, it was en route from Cadiz, Spain to a port near Buenos Aires, Argentina. The loitering events occurred between July 24 and July 26 before the vessel proceeded to Argentina. Port records show that on August 10 the vessel delivered 14,000 tons of bitumen (or at least it was scheduled to offload that quantity of product). AIS confirms that the tanker reached dock in Campana, Argentina on August 10. 

The tanker was coming from Cadiz, Spain though we don’t know if the asphalt was actually from Spain or what quantity was loaded at the port facility in Cadiz. Earlier this year the vessel visited Venezuelan ports and imported Venezuelan asphalt to the US. This article from March mentions The Amigo in the context of US sanctions against Venezuela that were coming into force. Could The Amigo have been carrying a cargo of asphalt that originated in Venezuela?

Figure 2. Movements of The Amigo since January 2019. The tanker’s current location in Turkey is shown.

The terms asphalt and bitumen appear to be used interchangeably to describe a semi-solid form of petroleum. High heat tankers like The Amigo must maintain their cargo at an elevated temperature so that it does not solidify, and can be pumped out of the vessel. Problems with heating might result in product remaining in one of the ship’s tanks and needing to be flushed out. Even under normal operations, heavy oil residue can build up in the cargo tanks and needs to be washed out or removed to free up usable space. International law requires that this be done in port where the oily sludge can be treated, but many ports lack the necessary treatment facilities. If somehow asphalt did end up being discharged directly into the ocean it would be expected to drift below the surface in warm equatorial waters. This might not generate a large surface oil slick that could be seen on satellite images, possibly explaining our frustration here at SkyTruth. 

As mentioned, there are some legitimate reasons for a tanker to be drifting out at sea. But we think it is fair to pose some further questions about this vessel given the severity of the spill in Brazil. What prompted the vessel to halt its normal transit off Brazil? What was the origin of the asphalt carried by the vessel and what quantities were loaded and offloaded? Could the chemical properties of the oil found on Brazilian beaches match this cargo, or any oily residue remaining in The Amigo’s cargo tanks?

But it’s not just The Amigo that’s raising questions for us. We’ve detected loitering events by other tankers in recent months (as shown on the map above and in the table below). We’ve found evidence of likely bilge-dumping by a few vessels in the area. And we’ve noticed that more than a dozen tankers operating in this area turn their AIS off while at sea, apparently in violation of international maritime safety law.

Table 1. Table showing the five tanker loitering events detected near the likely source of origin of the Brazil oil spill, shown as large yellow circles on the map at top.

We hope to find out answers to some of these questions soon, and we will continue to investigate all available data that might help to identify the origin of this devastating oil spill. One problem is very clear: we don’t know everything we need to know about the tanker activity near Brazil, and in many other parts of the ocean. 

Update 19 Nov 2019 – Since posting this last week I’ve had a chance to get some input regarding the Bitumen tanker I identified as of particular interest, The Amigo. The 14,000 tons they were scheduled to offload in Argentina would represent close to the full carrying capacity of the vessel. With estimates of at least 2,000 tons of material recovered from the beaches it seems that the vessel could not be responsible if they delivered a full cargo. 

We remain puzzled by the properties of oil coming up on the beach. It has been clearly reported as floating below the surface which fits with the fact that no large slick has so far shown up on satellite imagery. It has been questioned whether any of the asphalt carried by a vessel like The Amigo would really remain in the water column and be able to float ashore, rather than sinking to the seafloor. So some sort of heavy crude seems to be the most likely source. 

We are continuing to investigate any possible leads on the source of the spill and will share any more information that comes up. 

Bilge Dumping off the Coast of Brazil

The cause of the massive oil spill plaguing Brazil’s beaches is still unknown, but monitoring reveals a potential new bilge dumping incident

We still haven’t found the cause of the massive oil spill that’s been plaguing Brazil’s beaches since early September.  

But SkyTruth’s continued surveillance of the coast of northeastern Brazil, in response to one of the country’s worst oil-related environmental disasters ever, has uncovered what appears to be another previously unreported bilge dumping incident off the coast of Joao Pessoa in the state of Paraiba. Located about 20 km offshore, a 25 km-long slick appears to originate from the Grajau, a Brazil-flagged liquefied petroleum gas (LPG) tanker. Slicks such as this are a hallmark of the intentional dumping of untreated, oily bilge wastes from vessels underway at sea, although there may be other explanations for this slick (for example, the ship was experiencing a serious mechanical problem). The slick (a long, dark streak) and vessel (a bright spot at the south end of the slick) are shown on this Sentinel-1 radar satellite image taken on the 19th of July. We identified the vessel using their public AIS tracking broadcasts, extracted from the ShipView vessel-tracking platform. The image was captured at 07:53 UTC; a careful look at the AIS broadcasts from Grajau just before and after the image was taken show that the vessel we can see on the radar image is very likely Grajau.

Recent discoveries of bilge dumping in the Atlantic Ocean along Brazil’s coast reveal that this is a persistent problem that — as in many places — lacks effective enforcement. None of the slicks we’ve seen appear big enough to be the source of the oil plaguing Brazil’s beaches. This potential bilge slick from Grajau is no exception: it’s a modest-sized slick compared with the dozens of bilge slicks we’ve seen from other places around the world that are occasionally more than 100 km long. And this slick, just 20 km offshore, probably would have dissipated or washed ashore several weeks before the thick globs of heavy oil began to appear on the beaches in early September.

Nevertheless, bilge dumping is a chronic source of oil pollution in the ocean that has been hidden for too long. Now that we can see it, and can identify the likely polluters, it’s time for governments to take action to bring this illegal practice to an end.

AIS ship-tracking broadcasts (red dots) from the Brazil-flagged LPG tanker Grajau, overlain on a Sentinel-1 radar satellite image showing an apparent bilge-dumping slick (dark streak) and the vessel that appears to be responsible (bright spot, indicated within the red circle). Based on the AIS data, we think this vessel is likely the Grajau. See inset map at upper right for detail. Image was collected at 07:53 on July 19.

The location of the boat, relative to Brazil’s coastline.

Bilge Dumping Caught in Indonesia – Again!

SkyTruth identified the bulk carrier Lumoso Aman as the likely polluter via AIS and satellite imagery.

On October 10, 2019, SkyTruth discovered yet another likely bilge dumping incident in Southeast Asian waters. At 10:25:26 UTC (Coordinated Universal Time), Sentinel-1 Imagery captured this oily pollution during routine monitoring of the Makassar Strait. Lingering off the southwest coast of Sulawesi, Indonesia, this oil slick measures approximately 33 kilometers long. The slick and the suspected responsible vessel (circled in red in Figure 1 below) appear roughly 100 kilometers west of the coast of Makassar, the capital of Sulawesi. Makassar is a port city with active commerce and tourism.

Figure 1: A vessel suspected of bilge dumping.

We identified the potential culprit through AIS (Automatic Identification System) broadcasts from the Lumoso Aman (Figure 2), a bulk cargo carrier operating under the flag of Indonesia. 

Figure 2: A picture of the Lumoso Aman, courtesy of Vessel Finder.

Bilge dumping is the disposal of waste water from a ship’s lower hull. Bilge water is supposed to be treated before it’s discharged, but sometimes vessel operators will bypass the pollution control equipment and flush oily, untreated bilge into the ocean – in direct violation of international marine pollution law. You can learn more about this ongoing source of ocean pollution, and how SkyTruth identifies perpetrators, in our recent post about bilge dumping in Southeast Asia.

Our motto at SkyTruth is “If you can see it, you can change it.” We tirelessly monitor the ocean with this vision in mind, to be watchdogs and defenders of our Earth’s waters. No matter how remote these areas of pollution appear to be, we can see them with satellite images. These seemingly remote bodies of water are connected to waters throughout the world. Just as air pollution migrates between contiguous countries or states, oil pollution can find its way to any coastline and harm coastal environments and communities. With continued monitoring, we hope that nations, communities, and enforcement agencies can hold ship operators accountable, making it clear that bilge pollution is an unacceptable threat to the world’s ocean ecosystems. 

Figure 3: SkyTruth intern Tatianna Evanisko tracks polluting vessels around the world from the SkyTruth offices in Shepherdstown WV. Photo credit: Johnna Armstrong.

What About the Oceans? Mapping Offshore Infrastructure

Mapping stationary structures in the ocean helps us track fishing vessels and monitor pollution more effectively.

We’re all accustomed to seeing maps of the terrestrial spaces we occupy. We expect to see cities, roads and more well labeled, whether in an atlas on our coffee table or Google Maps on our smartphone. SkyTruthers even expect to access information about where coal mines are located or where forests are experiencing regrowth. We can now see incredibly detailed satellite imagery of our planet. Try looking for your house in Google Earth. Can you see your car in the driveway?

In comparison, our oceans are much more mysterious places. Over seventy percent of our planet is ocean, yet vast areas are described with only a handful of labels: the Pacific Ocean, Coral Sea, Strait of Hormuz, or Chukchi Sea for example. And while we do have imagery of our oceans, its resolution decreases drastically the farther out from shore you look. It can be easy to forget that humans have a permanent and substantial footprint across the waters of our planet. At SkyTruth, we’re working to change that.

Former SkyTruth senior intern Brian Wong and I are working to create a dataset of offshore infrastructure to help SkyTruth and others more effectively monitor our oceans. If we know where oil platforms, aquaculture facilities, wind farms and more are located, we can keep an eye on them more easily. As technological improvements fuel the growth of the ocean economy, allowing industry to extract resources far out at sea, this dataset will become increasingly valuable. It can help researchers examine the effects of humanity’s expanding presence in marine spaces, and allow activists, the media, and other watchdogs to hold industry accountable for activities taking place beyond the horizon.

What We’re Doing

Brian is now an employee at the Marine Geospatial Ecology Lab (MGEL) at Duke University. But nearly two years ago, at a Global Fishing Watch research workshop in Oakland, he and I discussed the feasibility of creating an algorithm that could identify vessel locations using Synthetic Aperture Radar (SAR) imagery. It was something I’d been working on on-and-off for a few weeks, and the approach seemed fairly simple.

Image 1. SkyTruth and Global Fishing Watch team members meet for a brainstorming session at the Global Fishing Watch Research Workshop, September 2017. Photo credit: David Kroodsma, Global Fishing Watch.

Readers who have been following SkyTruth’s work are probably used to seeing SAR images from the European Space Agency’s Sentinel-1 satellites in our posts. They are our go-to tools for monitoring marine pollution events, thanks to SAR’s ability to pierce clouds and provide high contrast between slicks and sea water. SAR imagery provides data about the relative roughness of surfaces. With radar imagery, the satellite sends pulses to the earth’s surface. Flat surfaces, like calm water (or oil slicks), reflect less of this data back to the satellite sensor than vessels or structures do, and appear dark. Vessels and infrastructure appear bright in SAR imagery because they experience a double-bounce effect. This means that — because such structures are three-dimensional — they typically reflect back to the satellite more than once as the radar pulse bounces off multiple surfaces. If you’re interested in reading more about how to interpret SAR imagery this tutorial is an excellent starting point.

Image 2. The long, dark line bisecting this image is a likely bilge dump from a vessel captured by Sentinel-1 on July 2, 2019. The bright point at its end is the suspected source. Read more here.

Image 3. The bright area located in the center of this Sentinel-1 image is Neft Daşları, a massive collection of offshore oil platforms and related infrastructure in the Caspian Sea.

Given the high contrast between water and the bright areas that correspond to land, vessels, and structures (see the vessel at the end of the slick in Image 2 and Neft Daşları in Image 3), we thought that if we could mask out the land, picking out the bright spots should be relatively straightforward. But in order to determine which points were vessels, we first needed to identify the location of all the world’s stationary offshore infrastructure, since it is virtually impossible to differentiate structures from vessels when looking at a single SAR image. Our simple task was turning out to be not so simple.

While the United States has publicly available data detailing the locations of offshore oil platforms (see Image 4), this is not the case for other countries around the world. Even when data is available, it is often hosted across multiple webpages, hidden behind paywalls, or provided in formats which are not broadly accessible or useable. To our knowledge, no one has ever published a comprehensive, global dataset of offshore infrastructure that is publicly available (or affordable).

Image 4. Two versions of a single Sentinel-1 image collected over the Gulf of Mexico, in which both oil platforms and vessels are visible. On the left, an unlabelled version which illustrates how similar infrastructure and vessels appear. On the right, oil platforms have been identified using the BOEM Platform dataset.

As we began to explore the potential of SAR imagery for automated vessel and infrastructure detection, we quickly realized that methods existed to create the data we desired. The Constant False Alarm Rate algorithm has been used to detect vessels in SAR imagery since at least 1988, but thanks to Google Earth Engine we are able to scale up the analysis and run it across every Sentinel-1 scene collected to date (something which simply would not have been possible even 10 years ago). To apply the algorithm to our dataset, we, among other things, had to mask out the land, and then set the threshold level of brightness that indicated the presence of a structure or vessel. Both structures and vessels will have high levels of reflectance. So we then had to separate the stationary structures from vessels. We did this by compiling a composite of all images for the year 2017. Infrastructure remains stationary throughout the year, while vessels move. This allowed us to clearly identify the infrastructure.

Image 5. An early version of our workflow for processing radar imagery to identify vessel locations. While the project shifted to focus on infrastructure detection first, many of the processing steps remained.

Where We Are Now

Our next step in creating the infrastructure dataset was testing the approach in areas where infrastructure locations were known. We tested the algorithm’s ability to detect oil platforms in the Gulf of Mexico, where the US Bureau of Ocean Energy Management (BOEM) maintains a dataset. We also tested the algorithm’s ability to identify wind turbines. We used a wind farm boundary dataset provided by the United Kingdom Hydrographic Office to validate our dataset, as well as information about offshore wind farms in Chinese waters verified in media reports, with their latitude and longitude available on Wikipedia.

Image 6. Wind farms in the Irish Sea, west of Liverpool.

Our results in these test areas have been very promising, with an overall accuracy of 96.1%. The methodology and data have been published by the journal Remote Sensing of Environment. Moving beyond these areas, we are continuing to work with our colleagues at MGEL to develop a full global dataset. What started as a project to identify vessels for GFW has turned into an entirely different, yet complementary, project identifying offshore infrastructure around the world.

Image 7. This animated map shows the output of our offshore infrastructure detection algorithm results (red) compared to the publicly available BOEM Platform dataset (yellow).

In addition to helping our partners at Global Fishing Watch identify fishing vessels, mapping the world’s offshore infrastructure will help SkyTruth more effectively target our daily oil pollution monitoring work on areas throughout the ocean that are at high risk for pollution events from oil and gas drilling and shipping (such as bilge dumping). This is also the first step towards one of SkyTruth’s major multi-year goals: automating the detection of marine oil pollution, so we can create and publish a global map of offshore pollution events, updated on a routine basis.

Be sure to keep an eye out for more updates, as we will be publishing the full datasets once we complete the publication cycles.