Ship Traffic Distributions and Statistics in the Gulf of Guinea and Off West Africa

Ship traffic distributions and statistics in the Gulf of Guinea and off West Africa

Harm Greidanus, Marlene Alvarez, Torkild Eriksen, Thomas Barbas

2013

Ship traffic density map from Satellite AIS data Nov 2012 – Mar 2013

European Commission Joint Research Centre Institute for the Protection and Security of the Citizen

Contact information Harm Greidanus Address: Joint Research Centre, Via Enrico Fermi 2749, TP 670, 21027 Ispra (VA), Italy E-mail: [email protected] Tel.: +39 0332 78 9739 Fax: +39 0332 78 9156 http://ipsc.jrc.ec.europa.eu/

This publication is a Reference Report by the Joint Research Centre of the European Commission.

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Executive summary

The PMAR (Piracy, Maritime Awareness and Risks) – Gulf of Guinea project was run to increase the maritime awareness of the authorities around the Gulf of Guinea. As part of the project, 6 months of maritime surveillance data have been collected from ship reporting systems (AIS, LRIT). The area of collection was over the Gulf of Guinea and West Africa, in the box 10° South to 30° North by 30° West to 15° East. The period was 1 Oct 2012 to 31 Mar 2013. This report shows statistics derived from these 6 months of data, in the form of ship traffic density maps per ship category at a grid size of 0.1°x0.1°, daily ship counts, and composition of the fleets by Flag and type of ship.

It is found that the grand total number of different ships seen during the entire 6 months period is about 12,000; while the daily average number of ships is over 2,500. For fishing ships, passenger ships, cargo ships and tankers, the daily average numbers are approximately 125, 190, 850, and 505 respectively. The activity of passenger ships, cargo ships and tankers is relatively constant over the period, whereas the activity of fishing ships and yachts changes much from month to month. The Flags that occur most frequently are – probably not surprisingly – Panama, Liberia and Marshall Islands. Concerning fishing ships, the country with the highest number in the entire area (which includes the Canary Islands) is Spain; within a narrower area only including the Gulf of Guinea itself, however, it is Japan.

The results in this report represent a description of the ship traffic in the Gulf of Guinea to a level of detail that was not available before. This information can be put to use by the relevant government authorities for maritime policy development and implementation.

Contents

1 Introduction ...... 5 2 Data...... 5 3 Processing ...... 6 4 Results ...... 7 4.1 Total ship numbers and impact of error corrections ...... 7 4.2 The ship/cargo type attribute ...... 8 4.2.1 Count of MMSIs grouped by ship/cargo type ...... 8 4.2.2 Number of different ship/cargo types used ...... 9 4.3 Different types of ship traffic distributions, exemplified for one month ...... 9 4.4 Ship density maps integrated for 6 months ...... 15 4.5 Daily numbers of ships ...... 19 4.5.1 Daily numbers of ships per category in the whole area ...... 19 4.5.2 Daily numbers of ships per category, Gulf of Guinea only ...... 24 4.6 Number of ships per country, 6 month combined ...... 29 4.6.1 Number of ships per country, whole area ...... 29 4.6.2 Number of fishing ships per country, whole area ...... 31 4.6.3 Number of ships per country, GoG area ...... 35 4.6.4 Number of fishing ships per country, GoG area ...... 37 4.6.5 Passenger ships, cargo ships and tankers, GoG area ...... 38 4.7 Density maps per month ...... 39 4.7.1 All ship traffic, per month ...... 39 4.7.2 Class B ship traffic, per month ...... 42 4.7.3 Engaged in fishing (navstat = 7), per month ...... 45 4.7.4 Fishing ships (navstat = 7 or ship/cargo type = 30), per month ...... 48 4.7.5 Passenger ships (ship/cargo type = 60-69), per month ...... 51 5 Conclusions ...... 55 Acknowledgements ...... 56 References ...... 56

1 Introduction The “Piracy, Maritime Awareness and Risks – Gulf of Guinea” project (PMAR – GoG) was carried out during 2011-2013 by the European Commission’s Joint Research Centre (JRC) to test methods for improved maritime awareness for authorities in the Gulf of Guinea (GoG) region [1][2]. The main driver was counter piracy, but improved maritime security and maritime governance in general were closely related goals. One of the factors that prevent an adequate response to piracy and other security, safety and sustainability threats at or from the sea, is a lack of knowledge of ongoing activities at sea. One of the activities in the PMAR project was therefore the collection of 6 months of ship reporting data in a wide area around the Gulf of Guinea and West Africa. This data collection served (a) to supply test data for the experimental PMAR-MSA system to provide Maritime Situational Awareness (MSA) to the authorities, and (b) to build up knowledge on ship traffic distributions and statistics in the region. This report discusses the latter issue.

2 Data The ship reporting data were acquired within the geographical box 10° South to 30° North, and 30° West to 15° East (see Figure 1), during the period 1 Oct 2012 – 31 Mar 2013.

Two types of ship reporting data were collected: AIS (Automatic Identification System) and LRIT (Long Range Identification and Tracking).

The AIS data were collected from the following sources:  Coastal AIS: o MSSIS international AIS network  Satellite AIS: o Norwegian constellation . Two satellites, AISSat-1 and NORAIS o exactEarth constellation . Up to four satellites o Orbcomm/LuxSpace constellation . Two satellites

The LRIT data were limited to EU-Flagged vessels.

All data from these sources were ingested via internet connections, and stored in a structured data base.

The MSSIS network links a number of coastal AIS receiving stations. However, the Gulf of Guinea / West Africa coast is not uniformly covered. In fact, good coastal coverage is only obtained in a few areas, like the Canary and Cape Verde Islands and a few major ports on the African coast. In the areas that are covered, AIS reception is continuous. The range of the coastal stations depends strongly on their height above sea level and on the atmospheric propagation conditions for the AIS signal (on VHF). A typical range is 20 nautical miles, but that can be extended tenfold under particular good conditions.

The satellites provide a geographical coverage that is more homogeneous, as their orbits take them in due time over the entire region. At the same time, this orbiting nature prevents them from giving continuous coverage. The much larger distance of the satellites (in the order of a thousand kilometres), together with the fact that AIS equipment was originally not designed to emit upward, result in not all AIS transmissions being successfully received. Especially Class B transponders (see below) that emit a weaker signal are more difficult to detect.

AIS uses a number of different message types [3][4]. Class A AIS transponders, mandatory under IMO regulations on the bigger ships (typically 300 GT and up), use AIS messages 1, 2 and 3 to report their position, and message 5 to report their static and voyage information such as ship name, ship/cargo type and destination. Class B transponders, carried voluntarily on smaller ships,

5 use messages 18 and 19 to report their position, and the same message 19 and message 24 for static data. In the present analysis, messages 1, 2, 3, 18 and 19 (“position” or “dynamic” reports) have been used to plot ship positions on a map, and messages 5, 19 and 24 (“static reports”) have been used to select ships with specific ship/cargo types [8]. The position messages also contain an attribute navigational status (navstat) [8] that specifies the activity a ship is engaged in. In this report, “Class A ships” means ships carrying Class A AIS equipment, and likewise for Class B ships.

The performance of AIS, in terms of number of messages and ships detected per AIS provider, was analysed in a separate report [5].

A ship is identified in AIS messages by its MMSI (Maritime Mobile Service Identity) number. For normal ships, the first three digits of the 9-digit MMSI constitute the MID code [7], which specifies the ship’s country (Flag). (Other users of MMSI numbers e.g. include coastal stations, for which the MMSI number starts with 00.)

The LRIT messages used in this study are of a type containing the MMSI number in addition to the IMO number and position. Most ships that carry LRIT also use AIS, and the AIS and LRIT messages of the same ship can be linked through the MMSI number. As the frequency of LRIT messages, at four per day, is much lower than that of AIS, which can be several per minute but may be thinned out to once every few minutes by the collection systems, the addition of LRIT has in fact little impact on the present construction of ship position density maps. For other maritime surveillance uses, however, LRIT does have an added value [6].

3 Processing During the campaign period, collecting data from all the sources mentioned in the previous section, the amount of incoming messages was very high, in the order of almost 400,000 per day. As some errors occur in the transmission, reception and decoding, a small amount of these messages contain erroneous data. They must be filtered out to prevent spurious results. Furthermore, some ships use a wrong MMSI number in their AIS, which results in a number of cases of the same MMSI number being used on multiple ships. This leads to errors in associating the static and the dynamic messages. As a consequence, the resulting statistics have some error margin. Different methods have been tried to deal with these issues.

Some AIS positions are – erroneously – found on land. They are filtered out using a land mask. As the land masks that were used have a certain accuracy, and certainly do not contain inland waters except for the bigger estuaries and ports, some valid messages are removed. But the objective is anyway maritime surveillance, not surveillance of inland waters.

Also the position longitude, latitude = 0, 0 occurs too often; these messages are also removed.

An erroneous AIS message can typically have contents that are random in one or more of its fields, including the MMSI number. This leads to the occurrence of MMSI numbers that are only seen once during the entire campaign period. Removing such messages has been tried as one way of error mitigation. However, when doing that, certainly some valid messages are removed as well in the process. In any case, the removal of such individual messages has no impact on the ship traffic density maps; but it has impact on the ship counts per Flag, which are also presented here.

For the density maps, all position messages received during a chosen time interval were binned on a geographic grid with a cell size of 0.1° x 0.1°. This corresponds to 11.1 km x 11.1 km. This process results in a 2-dimensional matrix of 450 x 400 pixels, in which each pixel counts the number of position messages inside that bin. This matrix represents a map of ship density; the density of ship messages being used as an approximation for ship density.

This procedure was done using the messages from all ships, and also after selecting various subsets of the ships. A particular subset of interest is fishing ships, in order to obtain information about fishing activity. Three ways of selecting fishing ships have been used:

 Selecting only messages that have navstat = 7 (“engaged in fishing”) in the AIS position message;  Selecting the position messages from those ships that have ship/cargo type = 30 (“fishing ship”) in their static AIS messages;  The combination (union) of those two. The setting of the AIS message fields is done by the ship’s master, initially when the AIS equipment is installed, and later when the ship changes its cargo or activity; they may therefore not always be up to date.

Another selection was done to view only ships that carry a Class B transponder. These are mostly smaller ships (including yachts and pleasure craft).

Also passenger ships, cargo ships and tankers were selected separately, based on the ship/cargo type in the static AIS message.

In order to better display the ship density maps, first a smoothing was applied with a kernel of [0.25 0.5 0.25] in both directions. This leads to a smoother and thereby more easily interpretable picture. Secondly, a logarithmic colour scaling was applied. This is needed because some pixels, particularly in ports, contain a very high number of ship positions, and a linear scaling would make most of the other pixels fall below the threshold of visibility.

Periods over which ship density maps were constructed are monthly (separately per month), and over the entire 6 month period (1 Oct 2012 – 31 Mar 2013) combined.

4 Results 4.1 Total ship numbers and impact of error corrections As mentioned above, various ways have been used to filter out erroneous AIS messages, which has an impact on the total number of ships, and on the ships-per-Flag counts (but not on the traffic density maps).

Filtering out all AIS messages that fall on land (using a particular choice of coast line), the total number of different MMSIs that are seen with position messages in the entire area during the entire 6-month period is 12,737. However, from 2,099 of those, only one single position message is received during the entire period. Assuming that these messages are due to errors, hence do not contain data from real ships, the total number of different MMSIs would be 10,638. However, one can be less strict in this filtering, and only filter out those singly-occurring MMSI that have an invalid MID code; in that case, 11,941 different MMSIs are seen. In this context, an invalid MID is one that is not in the range 200 to 799 [3]. Table 1 below gives an overview of the results of these different methods of filtering.

# MMSI No MMSI removed Removed MMSIs that Removed MMSIs that occur only once and have occur only once an invalid MID code Whole area 12,737 11,941 10,638 Gulf of Guinea 7,734 6,975 6,224 Table 1: Number of different MMSIs seen on position reports during 6 months, using three different methods of filtering out errors. “Whole area” is using all data (ref. Figure 1); “Gulf of Guinea” refers to a sub-area as shown in Figure 8.

In the remainder, no MMSIs have been removed. Therefore the absolute numbers are on the high side, but the relative numbers (for the various ship categories or Flags) are not so different between the different methods of filtering. Only the amount of ships that have an invalid MMSI (and therefore cannot be assigned to a Flag) are obviously high.

4.2 The ship/cargo type attribute This element of the static AIS report describes the type of ship, in some cases in combination with the type of cargo. For some ships, the cargo can change from voyage to voyage for the same ship. This section gives an overview of the occurrence of the various ship/cargo types in the region during the campaign.

4.2.1 Count of MMSIs grouped by ship/cargo type As explained, the classification according to ship type is done by joining the MMSIs from the position reports with a ship/cargo type for that MMSI from the static/voyage report. Table 2 shows the results from the whole campaign (6 months) as well as for the last month (Mar 2013).

ship/cargo Description 6 months Mar 2013 0 Not available (default) 432 261 1-19 Reserved for future use 53 31 20-29 Wing in ground (WIG) 13 8 30 Fishing 369 190 31 Towing 52 33 32 Towing: length exceeds 200m … 36 16 33 Dredging or underwater ops 67 36 34 Diving ops 18 15 35 Military ops 52 24 36 Sailing 576 96 37-38 Pleasure Craft 318 83 39 Reserved 38 28 40-49 High speed craft (HSC) 47 31 50 Pilot Vessel 24 16 51 Search and Rescue vessel 25 22 52 Tug 419 304 53 Port Tender 10 7 54 Anti-pollution equipment 8 6 55 Law Enforcement 19 14 57 Spare - Local Vessel 8 7 58 Medical Transport 1 0 59 Non-combatant ship … 6 5 60-69 Passenger 331 200 70-79 Cargo 5,446 2,224 80-89 Tanker 2,154 966 90-99 Other Type 614 386 Missing or reserved ship/cargo type 2,422 621 Total 13,558 5,630

Table 2: Number of MMSIs grouped by ship/cargo type. Colour coding is by amount, from green (low) to red (high).

The relative distribution of ships does not differ much between March 2013 and the whole period, as visualised by the similar colours, except that the “Missing or reserved ship/cargo type” is larger in the whole campaign than in March (may be related to the contribution of the month of Dec 2012 for which this number was relatively high).Also the number of sailing and pleasure craft is low in March, which is related to their increased presence during Nov and Dec 2012, discussed further below.

Static reports are emitted much less frequently than position reports. Therefore, it happens that for a certain ship some position reports are received within a certain time interval, but no static reports. For Mar 2013 it was investigated how the number of combinations of MMSIs from

8 position reports that could be matched with a static report depended on the time interval in which the static data was taken from. When static is considered for the month of Mar 2013, the table shows that there are 621 MMSIs without valid ship/cargo type. If static reports from all the 6- months are considered, the number is reduced to 509, and if no limit (in time) is used the number reduces to 434. 187 vessels were added to the defined groups in the latter case, but it did not make much difference to the overall distribution.

4.2.2 Number of different ship/cargo types used The count of the different ship/cargo types used, combined over all ships, for Mar 2013 is shown in Table 3. Of the 5,630 ships observed this month, an AIS message 5 was received from 5,142 ships, leaving 488 from which no message 5 was received. The use of more than one ship/cargo type by the same MMSI is probably within the intended use of the system for low numbers, but not for the high numbers. The problem is related to the use of erroneous MMSIs; values such as 0, 1, 1193046, 100000000, 111111111, 123456789, 222222222, 273000000, 999999999.

# Ship/cargo types used # MMSIs 0 6 1 4,598 2 447 3 68 4 10 5 3 7 1 9 1 11 1 12 2 14 1 15 1 16 1 19 1 21 1 No message 5 488 Total 5,630 Table 3. Histogram for March 2013 data: number of MMSIs per number of different types of ship/cargo used.

The ratio of the number of distinct MMSIs in static messages to the number in position reports is 5,142 / 5,630 = 0.91.

4.3 Different types of ship traffic distributions, exemplified for one month This section shows ship density maps for the month of November 2012, processed and displayed in various ways, so as to assess the differences between the types of results. The next sections will select only a few of these types of results, and, for those selected types, it will show the results for all 6 months that data have been collected.

Figure 1 and Figure 2 show the total ship density for November 2012 before and after the smoothing is applied, respectively.

Figure 1. Ship density map, using all AIS and LRIT position messages during the month Nov 2012. The total number of messages is 11,446,927 (annotated on the left). The total number of ships seen during the entire month is 5,562 (annotated on the bottom). The colour coding for the ship density is logarithmic, with the scale on the right, so that red indicates almost 106 ship positions per 0.1 x 0.1 degree cell per month. The main shipping routes can be recognised, as well as ship concentrations at ports. White areas are devoid of any reporting ships.

Figures 3 and 4 show the distribution of Class B AIS ships (the smaller ships), and the impact of using coastal AIS data. The coastal stations receive much more data inside their area of coverage, so that a map tends to show a combination of the effects of station area coverage and actual ship density. A map made from satellite AIS data only does not have this effect, even if it represents only a fraction of all data collected.

Figure 2. Ship density map, the same as Figure 1, but after smoothing with a kernel of [0.25 0.5 0.25] in both directions. The smoothing makes in particular very small areas of high ship concentration better visible.

Figure 3. Class B AIS only, using all data sources (satellite and coastal). The total number of position messages is 689,473, and the total number of ships is 766. Class B ships are seen near the coast and in the North-West corner of the area, the latter

related to Atlantic crossing sailing ships and yachts. Large concentrations are seen around the islands of the Canaries and Cape Verde.

Figure 4. Class B AIS only, using satellite data only (no coastal). The high concentrations around the Canary and Cape Verde islands from the previous figure are gone, giving a more unbiased picture of the actual Class B ship traffic. The total number of position messages is now only 28,210 (compared to 689,473 in the previous figure), and the total number of ships is 552 (compared to 766).

Figures 5, 6 and 7 show three ways to map fishing vessels. The first figure shows the distribution of AIS messages with navstat = 7 (“engaged in fishing”); the second one with ship/cargo type = 30 (“fishing vessel”); and the last one the combination of the two (the messages with navstat = 7 or those with an MMSI that has ship/cargo type = 30). It can be seen that while on the one hand the selection navstat = 7 clearly misses a number of ships that are fishing (but have not set their navstat to 7), the addition of the ships that have ship/cargo type = 30 introduces many ships that are not actually fishing but merely transiting.

Figure 8 shows a map of only the Gulf of Guinea, leaving out the West Africa part. Such a map does not contain essentially new information, because it is included in the larger maps (in this case, Figure 1). However, when it comes to counting the number of ships, a geographical restriction can be required.

Figure 5. All ships with navstat = 7 (“engaged in fishing”) in the position message.

Figure 6. All ships with ship/cargo type = 30 (“fishing ship”).

Figure 7. All ships with navstat = 7 or ship/cargo type = 30.

Figure 8. All ship traffic, only within the Gulf of Guinea. This map is already contained in Figure 1. The number of ships seen in this smaller area during the month Nov 2012 is 3,204, compared to 5,562 inside the entire area including West Africa.

4.4 Ship density maps integrated for 6 months The following density maps are shown integrated for the entire period of 6 months, Oct 2012 – Mar 2013:  All ship traffic;  Class B ship traffic;  Engaged in fishing (navstat = 7);  Fishing ships (navstat = 7 or ship/cargo type = 30);  Passenger ships (ship/cargo type = 60-69);  Cargo ships (ship/cargo type = 70-79);  Tankers (ship/cargo type = 80-89). Each are made using only satellite AIS data, in order to prevent the bias from the coastal AIS coverage. Except for the one that visualises the Class B traffic only (Figure 10), they all contain both Class A and Class B.

Section 4.5 plots the number of ships seen per day for these different categories.

Figure 9. All ship traffic, combined over 6 months.

Figure 10. Class B ship traffic, combined over 6 months.

Figure 11. Ships engaged in fishing (navstat = 7), combined over 6 months.

Figure 12. Fishing ships (navstat = 7 or ship/cargo type = 30), combined over 6 months.

Figure 13. Passenger ships (ship/cargo type = 60-69), combined over 6 months.

Figure 14. Cargo ships (ship/cargo type = 70-79), combined over 6 months.

Figure 15. Tankers (ship/cargo type = 80-89), combined over 6 months.

4.5 Daily numbers of ships

4.5.1 Daily numbers of ships per category in the whole area In the previous section, the text on the horizontal axis of the plots mentioned the total number of different ships over the entire 6 month period. This section shows the daily number of different ships that are seen in the density maps of the previous section, covering the entire area.

Each graph shows two lines, the black/upper one based on all AIS data sources (terrestrial and satellite), the blue/lower one based on satellite AIS only. The latter one therefore exactly corresponds to the contents of the density maps of the previous section.

No filtering of MMSI numbers that occur only once or with invalid MID codes, as discussed in section 4.1, has been done. The numbers therefore total to those in the leftmost column of Table 1. One can apply a ratio to estimate numbers that would have been obtained with such filtering; for example a factor of 0.94 to estimate results if singly occurring MMSI numbers with invalid MID codes would have been taken out (corresponding to column 2 in that table). This is what has given the figures quoted in the executive summary.

The section after this one shows daily number of ships only for the narrower Gulf of Guinea region itself.

Figure 16. Daily number of Class A ships between 1 Oct 2012 and 31 Mar 2013, whole region.

Figure 17. Daily number of Class B ships between 1 Oct 2012 and 31 Mar 2013, whole region.

Figure 18. Daily number of ships engaged in fishing (navstat = 7) between 1 Oct 2012 and 31 Mar 2013, whole region. All such ships are Class A, none are Class B.

Figure 19. Daily number of fishing ships (navstat = 7 or ship/cargo type = 30) between 1 Oct 2012 and 31 Mar 2013, whole region; Class A.

Figure 20. Daily number of fishing ships (navstat = 7 or ship/cargo type = 30) between 1 Oct 2012 and 31 Mar 2013, whole region; Class B.

Figure 21. Daily number of passenger ships (ship/cargo type = 60-69) between 1 Oct 2012 and 31 Mar 2013, whole region; Class A.

Figure 22. Daily number of passenger ships (ship/cargo type = 60-69) between 1 Oct 2012 and 31 Mar 2013, whole region; Class B.

Figure 23. Daily number of cargo ships (ship/cargo type = 70-79) between 1 Oct 2012 and 31 Mar 2013, whole region; Class A. The daily number of Class B cargo ships is not plotted, but varies between 1 and 6.

Figure 24. Daily number of tankers (ship/cargo type = 70-79) between 1 Oct 2012 and 31 Mar 2013, whole region; Class A. The daily number of Class B tankers is not plotted, but varies between 0 and 4.

4.5.2 Daily numbers of ships per category, Gulf of Guinea only This section shows the same graphs as the previous section, except that the geographical area is now limited to the narrower Gulf of Guinea, leaving out the Atlantic / West Africa part, as in Figure 8 (longitude –15° to 15°; latitude –10° to 11°).

Figure 25. Daily number of Class A ships between 1 Oct 2012 and 31 Mar 2013, Gulf of Guinea area only.

A peak in the daily number of ships from the coastal AIS around day 72 is unexplained (it goes much higher than the limit of the graph), but is most likely caused by data errors.

Figure 26. Daily number of Class B ships between 1 Oct 2012 and 31 Mar 2013, Gulf of Guinea area only.

Figure 27. Daily number of ships engaged in fishing (navstat = 7) between 1 Oct 2012 and 31 Mar 2013, Gulf of Guinea area only. All such ships are Class A, none are Class B.

Figure 28. Daily number of fishing ships (navstat = 7 or ship/cargo type = 30) between 1 Oct 2012 and 31 Mar 2013, Gulf of Guinea area only; Class A.

Figure 29. Daily number of fishing ships (navstat = 7 or ship/cargo type = 30) between 1 Oct 2012 and 31 Mar 2013, Gulf of Guinea area only; Class B.

Figure 30. Daily number of passenger ships (ship/cargo type = 60-69) between 1 Oct 2012 and 31 Mar 2013, Gulf of Guinea area only; Class A.

Figure 31. Daily number of passenger ships (ship/cargo type = 60-69) between 1 Oct 2012 and 31 Mar 2013, Gulf of Guinea area only; Class B.

Figure 32. Daily number of cargo ships (ship/cargo type = 70-79) between 1 Oct 2012 and 31 Mar 2013, Gulf of Guinea area only; Class A. The daily number of Class B cargo ships is not plotted, but varies between 1 and 5.

Figure 33. Daily number of tankers (ship/cargo type = 80-89) between 1 Oct 2012 and 31 Mar 2013, Gulf of Guinea area only; Class A. The daily number of Class B tankers is not plotted, but varies between 0 and 4.

4.6 Number of ships per country, 6 month combined This section lists the number of different ships per country over the full 6-month period 1 Oct 2012 – 31 Mar 2013. The country is derived from the MID code, which are the first three digits of the 9-digit MMSI number.

Six different numbers of ships are given for each country:  Class A from all sources;  Class A from satellite AIS only;  Class B from all sources;  Class B from satellite AIS only;  Class A+B from all sources;  Class A+B from satellite AIS only.

The list is sorted by the 5th column, A+B all sources, which represents all available data.

There are four subsections in this section:  Whole area, all ships;  Whole area, fishing ships;  Gulf of Guinea area, all ships;  Gulf of Guinea area, fishing ships.

4.6.1 Number of ships per country, whole area This first sub-section combines counts of ships of all categories and from the entire area.

The first two columns correspond to the daily counts of Figure 16 (column A - black line; column Asat - blue line), except that the table here gives the 6-monthly count. The second two columns correspond to the daily counts of Figure 17 (column B - black line; column Bsat - blue line). Column Bsat corresponds to the density map of Figure 10. Column A+Bs corresponds to the density map of Figure 9.

In this and in similar tables that follow, “Invalid MID” means that the MID did not correspond to any MID in the official ITU list of MIDs for each Flag [7]. It is thereby more strict than what was called “invalid MID” in section 4.1. Furthermore, it is reminded that no filtering of singly occurring or invalid-MID MMSIs has been done (ref. section 4.1). Therefore, the counts under “Invalid MID” are (too) high.

A Asat B Bsat A+B A+Bs Country | 1440 1415 8 5 1448 1420 PA - Panama (Republic of) 1119 1091 0 0 1119 1091 LR - Liberia (Republic of) 970 264 56 46 1026 310 ?? - Invalid MID 935 901 3 3 938 904 MH - Marshall Islands (Republic of the) 575 546 16 15 591 561 MT - Malta 510 504 2 2 512 506 HK - Hong Kong (Special Administrative Region of… 304 292 182 148 486 440 GB - United Kingdom of Great Britain and… 481 479 2 1 483 480 BS - Bahamas (Commonwealth of the) 463 458 4 4 467 462 SG - Singapore (Republic of) 278 253 122 84 400 337 ES - Spain 326 320 3 3 329 323 CY - Cyprus (Republic of) 308 297 3 1 311 298 GR - Greece 226 224 53 51 279 275 NG - Nigeria (Federal Republic of) 141 121 136 108 277 229 FR - France 214 189 62 53 276 242 NL - Netherlands (Kingdom of the) 270 254 1 1 271 255 AG - Antigua and Barbuda 208 189 38 31 246 220 NO - Norway 219 219 6 6 225 225 VU - Vanuatu (Republic of) 182 173 19 18 201 191 VC - Saint Vincent and the Grenadines 174 151 8 7 182 158 IT - Italy 145 138 22 21 167 159 KY - Cayman Islands - United Kingdom of Great… 113 101 49 43 162 144 US - United States of America 81 79 66 48 147 127 DE - Germany (Federal Republic of) 140 134 7 6 147 140 DK - Denmark 102 99 13 12 115 111 CN - China (People's Republic of) 97 80 4 4 101 84 TR - Turkey 96 95 2 2 98 97 BM - Bermuda - United Kingdom of Great Britain…

84 80 5 4 89 84 GI - Gibraltar - United Kingdom of Great Britain… 79 70 1 1 80 71 KR - Korea (Republic of) 64 63 7 7 71 70 JP - Japan 65 63 5 2 70 65 BZ - Belize 46 42 22 17 68 59 BE - Belgium 61 58 0 0 61 58 LU - Luxembourg 54 42 0 0 54 42 RU - Russian Federation 15 15 38 31 53 46 SE - Sweden 46 45 2 2 48 47 AN - Bonaire, Sint Eustatius and Saba - Curaçao -… 44 44 4 4 48 48 TF - Kerguelen Islands - France 44 25 0 0 44 25 IS - Iceland 38 34 5 5 43 39 KN - Saint Kitts and Nevis (Federation of) 38 37 2 2 40 39 KM - Comoros (Union of the) 25 24 14 10 39 34 CH - Switzerland (Confederation of) 35 35 0 0 35 35 PH - Philippines (Republic of the) 33 32 0 0 33 32 PT - Madeira - Portugal 25 24 4 4 29 28 MA - Morocco (Kingdom of) 8 6 21 18 29 24 PL - Poland (Republic of) 28 28 0 0 28 28 BB - Barbados 21 18 7 7 28 25 CK - Cook Islands - New Zealand 24 22 3 3 27 25 CV - Cape Verde (Republic of) 27 26 0 0 27 26 MY - Malaysia 24 19 3 2 27 21 SL - Sierra Leone 27 24 0 0 27 24 TG - Togolese Republic 25 23 1 0 26 23 TH - Thailand 6 6 17 16 23 22 AU - Australia 16 14 4 4 20 18 PT - Portugal 19 19 1 1 20 20 VN - Viet Nam (Socialist Republic of) 19 19 0 0 19 19 AO - Angola (Republic of) 17 15 2 2 19 17 BR - Brazil (Federative Republic of) 17 15 2 1 19 16 HR - Croatia (Republic of) 5 5 13 8 18 13 CM - Cameroon (Republic of) 18 17 0 0 18 17 IN - India (Republic of) 3 3 15 10 18 13 VG - British Virgin Islands - United Kingdom of… 17 17 0 0 17 17 FK - Falkland Islands (Malvinas) - United Kingdom… 13 13 4 4 17 17 GH - Ghana 15 10 0 0 15 10 KH - Cambodia (Kingdom of) 15 15 0 0 15 15 LT - Lithuania (Republic of) 12 11 2 1 14 12 PT - Azores - Portugal 14 9 0 0 14 9 TZ - Tanzania (United Republic of) 10 10 2 2 12 12 HN - Honduras (Republic of) 5 4 6 6 11 10 CA - Canada 5 5 6 5 11 10 FI - Finland 11 11 0 0 11 11 FO - Faroe Islands - Denmark 11 11 0 0 11 11 LB - Lebanon 1 1 9 7 10 8 AT - Austria 10 10 0 0 10 10 BD - Bangladesh (People's Republic of) 10 10 0 0 10 10 DM - Dominica (Commonwealth of) 9 9 0 0 9 9 EG - Egypt (Arab Republic of) 9 9 0 0 9 9 TV - Tuvalu 8 8 0 0 8 8 GQ - Equatorial Guinea (Republic of) 8 8 0 0 8 8 LK - Sri Lanka (Democratic Socialist Republic of) 3 3 5 5 8 8 ZA - South Africa (Republic of) 7 7 0 0 7 7 BF - Burkina Faso 7 7 0 0 7 7 SN - Senegal (Republic of) 7 5 0 0 7 5 UA - Ukraine 3 3 3 2 6 5 EE - Estonia (Republic of) 6 6 0 0 6 6 GA - Gabonese Republic 6 6 0 0 6 6 KI - Kiribati (Republic of) 6 4 0 0 6 4 MD - Moldova (Republic of) 6 6 0 0 6 6 MP - Northern Mariana Islands (Commonwealth of… 6 5 0 0 6 5 MX - Mexico 6 6 0 0 6 6 ST - Sao Tome and Principe (Democratic Republic… 4 3 1 1 5 4 CL - Chile 5 5 0 0 5 5 LV - Latvia (Republic of) 5 5 0 0 5 5 SO - Somali Democratic Republic 4 3 0 0 4 3 AE - United Arab Emirates 4 4 0 0 4 4 AX - Alaska (State of) - United States of America 4 4 0 0 4 4 CD - Democratic Republic of the Congo 4 4 0 0 4 4 ID - Indonesia (Republic of) 1 1 3 3 4 4 MQ - Martinique (French Department of) - France 0 0 4 0 4 0 NZ - New Zealand 4 3 0 0 4 3 UY - Uruguay (Eastern Republic of) 3 2 0 0 3 2 AD - Andorra (Principality of) 3 3 0 0 3 3 AR - Argentine Republic 2 0 1 0 3 0 BH - Bahrain (Kingdom of) 1 1 2 2 3 3 BJ - Benin (Republic of) 3 2 0 0 3 2 CO - Colombia (Republic of) 2 2 1 1 3 3 IE - Ireland 3 3 0 0 3 3 JM - Jamaica 3 3 0 0 3 3 KW - Kuwait (State of) 3 3 0 0 3 3 LY - Libya

3 3 0 0 3 3 MC - Monaco (Principality of) 3 3 0 0 3 3 NC - New Caledonia - France 3 3 0 0 3 3 NI - Nicaragua 3 3 0 0 3 3 PK - Pakistan (Islamic Republic of) 3 3 0 0 3 3 QA - Qatar (State of) 3 3 0 0 3 3 SA - Saudi Arabia (Kingdom of) 2 2 0 0 2 2 AW - Aruba (Netherlands) 2 1 0 0 2 1 BO - Bolivia (Plurinational State of) 2 2 0 0 2 2 CD - Congo (Republic of the) 2 2 0 0 2 2 EC - Ecuador 2 2 0 0 2 2 GM - Gambia (Republic of the) 1 1 1 1 2 2 HU - Hungary 2 2 0 0 2 2 IL - Israel (State of) 2 1 0 0 2 1 IR - Iran (Islamic Republic of) 2 2 0 0 2 2 KE - Kenya (Republic of) 2 2 0 0 2 2 ME - Montenegro 2 2 0 0 2 2 ML - Mali (Republic of) 2 2 0 0 2 2 MU - Mauritius (Republic of) 2 2 0 0 2 2 MW - Malawi 2 2 0 0 2 2 NE - Niger (Republic of the) 2 1 0 0 2 1 PE - Peru 2 2 0 0 2 2 RE - Reunion (French Department of) - France 2 2 0 0 2 2 RW - Rwanda (Republic of) 2 2 0 0 2 2 SC - Seychelles (Republic of) 1 1 0 0 1 1 AL - Albania (Republic of) 0 0 1 0 1 0 BG - Bulgaria (Republic of) 1 1 0 0 1 1 BN - Brunei Darussalam 1 1 0 0 1 1 BT - Bhutan (Kingdom of) 0 0 1 1 1 1 BY - Belarus (Republic of) 1 1 0 0 1 1 CI - Côte d'Ivoire (Republic of) 0 0 1 1 1 1 CZ - Czech Republic 1 1 0 0 1 1 DJ - Djibouti (Republic of) 1 1 0 0 1 1 ER - Eritrea 1 1 0 0 1 1 ET - Ethiopia (Federal Democratic Republic of) 1 1 0 0 1 1 GD - Grenada 0 0 1 1 1 1 GE - Georgia 1 1 0 0 1 1 GN - Guinea (Republic of) 1 1 0 0 1 1 IQ - Iraq (Republic of) 1 1 0 0 1 1 JO - Jordan (Hashemite Kingdom of) 1 1 0 0 1 1 KP - Democratic People's Republic of Korea 1 1 0 0 1 1 MM - Myanmar (Union of) 1 1 0 0 1 1 MR - Mauritania (Islamic Republic of) 1 1 0 0 1 1 NA - Namibia (Republic of) 1 1 0 0 1 1 PF - French Polynesia - France 0 0 1 1 1 1 PG - Papua New Guinea 1 1 0 0 1 1 PR - Puerto Rico - United States of America 1 1 0 0 1 1 SI - Slovenia (Republic of) 1 1 0 0 1 1 TC - Turks and Caicos Islands - United Kingdom of… 1 1 0 0 1 1 TM - Turkmenistan 1 1 0 0 1 1 TW - Taiwan (Province of China) - China (People's… 1 1 0 0 1 1 UG - Uganda (Republic of) 1 1 0 0 1 1 WF - Wallis and Futuna Islands - France Table 4. Number of ships per country, all ship types, whole area. See text above for explanations.

4.6.2 Number of fishing ships per country, whole area 4.6.2.1 “Engaged in fishing” (navstat = 7) The total number of MMSIs in the area that at any time in the 6-month campaign period reported navstat 7 is 184. The counts grouped by month are as follows.

Year Month Number of distinct MMSIs 2012 10 77 2012 11 73 2012 12 71 2013 1 71 2013 2 71 2013 3 93

The count per country is listed below, for the entire 6-month period, and for the month of Mar 2013. Colours indicate relative amount, green-yellow-orange-red going from low to high.

6 months Mar 2013 Flag Region name 2 2 BE Belgium 2 0 BS Bahamas (Commonwealth of the) 8 2 BZ Belize 1 1 CN China (People's Republic of) 1 0 CO Colombia (Republic of) 1 1 CV Cape Verde (Republic of) 1 1 CY Cyprus (Republic of) 54 33 ES Spain 1 0 FI Finland 16 7 FR France 2 0 GB United Kingdom of Great Britain and Northern Ireland 1 1 GD Grenada 2 1 GH Ghana 1 0 GR Greece 1 1 HK Hong Kong (Special Administrative Region of China…) 1 0 IE Ireland 1 0 IN India (Republic of) 4 0 IS Iceland 3 2 IT Italy 16 9 JP Japan 1 0 KH Cambodia (Kingdom of) 3 2 KM Comoros (Union of the) 1 0 KR Korea (Republic of) 3 1 LR Liberia (Republic of) 1 0 LT Lithuania (Republic of) 1 0 LU Luxembourg 1 1 LV Latvia (Republic of) 7 6 MA Morocco (Kingdom of) 4 2 MH Marshall Islands (Republic of the) 1 0 MT Malta 2 1 NG Nigeria (Federal Republic of) 2 0 NL Netherlands (Kingdom of the) 7 1 NO Norway 1 1 PA Panama (Republic of) 1 1 PL Poland (Republic of) 4 2 PT Azores - Portugal 5 3 PT Portugal 4 3 RU Russian Federation 1 0 SE Sweden 1 1 TW Taiwan (Province of China) - China (People's Republic 1 0 VC Saintof) Vincent and the Grenadines 1 1 VU Vanuatu (Republic of) 12 6 Not valid MID 184 93 Total

Table 5. Ship count by Flag for ships with navstat = 7 (“engaged in fishing”).

4.6.2.2 “Fishing ship” (ship/cargo type = 30) The total number of MMSIs in the area that at any time in the 6-month campaign period reported ship/cargo type 30 is 406. The counts grouped by month are as follows.

Year Month Number of distinct MMSIs 2012 10 213 2012 11 220 2012 12 208 2013 1 219 2013 2 211 2013 3 223

The classification of the MMSIs reporting ship/cargo type = 30 according to flag is shown in the table below.

6 months Mar 2013 Flag Region name 1 1 AE United Arab Emirates 2 0 AR Argentine Republic 1 0 AU Australia 1 0 AZ Azerbaijani Republic 1 1 BN Brunei Darussalam 22 10 BZ Belize 1 1 CI Côte d'Ivoire (Republic of) 1 1 CM Cameroon (Republic of) 12 6 CN China (People's Republic of) 3 3 CV Cape Verde (Republic of) 1 1 CY Cyprus (Republic of) 1 0 EE Estonia (Republic of) 96 57 ES Spain 1 0 FI Finland 12 0 FK Falkland Islands (Malvinas) - United Kingdom of … 2 0 FO Faroe Islands - Denmark 11 9 FR France 2 0 GB United Kingdom of Great Britain and Northern Ireland 3 2 GH Ghana 3 2 GR Greece 1 0 HK Hong Kong (Special Administrative Region of China) - … 1 1 HU Hungary 1 0 IE Ireland 34 8 IS Iceland 10 3 IT Italy 34 25 JP Japan 1 0 KI Kiribati (Republic of) 5 4 KM Comoros (Union of the) 6 2 KN Saint Kitts and Nevis (Federation of) 15 5 KR Korea (Republic of) 4 2 LT Lithuania (Republic of) 2 2 LV Latvia (Republic of) 11 8 MA Morocco (Kingdom of) 1 0 ML Mali (Republic of) 5 2 NG Nigeria (Federal Republic of) 5 1 NL Netherlands (Kingdom of the) 12 5 NO Norway 1 1 PE Peru 3 3 PL Poland (Republic of)

10 5 PT Azores - Portugal 12 8 PT Portugal 17 10 RU Russian Federation 1 1 SE Sweden 1 0 SG Singapore (Republic of) 1 0 SL Sierra Leone 1 0 SO Somali Democratic Republic 1 1 TH Thailand 1 1 TW Taiwan (Province of China) - China (People's Republic of) 4 1 UA Ukraine 1 0 US United States of America 1 0 UY Uruguay (Eastern Republic of) 1 1 VC Saint Vincent and the Grenadines 2 1 ZA South Africa (Republic of) 23 8 Not valid MID 406 203 Total Table 6. Ship count by Flag for ships with ship/cargo type = 30.

4.6.2.3 “Engaged in fishing” (navstat = 7) or “Fishing ship” (ship/cargo type = 30) Table 7 lists the number of ships per country that have navstat = 7 or ship/cargo type= 30. Columns A and Asat correspond to the daily counts of Figure 19 (column A - black line; column Asat - blue line). Columns B and Bsat correspond to the daily counts of Figure 20 (column B - black line; column Bsat - blue line). Column A+Bs corresponds to the density map of Figure 12.

A Asat B Bsat A+B A+Bs Country | 102 94 1 1 103 95 ES - Spain 32 32 6 6 38 38 JP - Japan 34 17 0 0 34 17 IS - Iceland 20 17 12 6 32 23 ?? - Invalid MID 23 22 3 1 26 23 BZ - Belize 19 13 0 0 19 13 FR - France 18 18 0 0 18 18 RU - Russian Federation 15 15 0 0 15 15 KR - Korea (Republic of) 8 7 6 6 14 13 CN - China (People's Republic of) 12 12 0 0 12 12 FK - Falkland Islands (Malvinas) - United Kingdom… 11 11 1 1 12 12 PT - Portugal 9 9 2 2 11 11 MA - Morocco (Kingdom of) 9 9 0 0 9 9 PT - Azores - Portugal 8 6 0 0 8 6 NO - Norway 7 5 0 0 7 5 NG - Nigeria (Federal Republic of) 6 6 0 0 6 6 KM - Comoros (Union of the) 6 6 0 0 6 6 KN - Saint Kitts and Nevis (Federation of) 6 3 0 0 6 3 NL - Netherlands (Kingdom of the) 5 3 0 0 5 3 MH - Marshall Islands (Republic of the) 4 1 0 0 4 1 IT - Italy 4 3 0 0 4 3 LR - Liberia (Republic of) 4 4 0 0 4 4 LT - Lithuania (Republic of) 3 3 0 0 3 3 CV - Cape Verde (Republic of) 3 3 0 0 3 3 GH - Ghana 3 2 0 0 3 2 GR - Greece 2 2 1 1 3 3 PL - Poland (Republic of) 3 3 0 0 3 3 UA - Ukraine 2 0 0 0 2 0 BE - Belgium 2 2 0 0 2 2 BS - Bahamas (Commonwealth of the) 2 2 0 0 2 2 CY - Cyprus (Republic of) 2 2 0 0 2 2 FO - Faroe Islands - Denmark 2 2 0 0 2 2 GB - United Kingdom of Great Britain and Northern… 2 2 0 0 2 2 HK - Hong Kong (Special Administrative Region… 2 2 0 0 2 2 IE - Ireland 2 2 0 0 2 2 LV - Latvia (Republic of) 2 2 0 0 2 2 PA - Panama (Republic of) 2 2 0 0 2 2 US - United States of America 2 1 0 0 2 1 UY - Uruguay (Eastern Republic of) 1 1 1 1 2 2 VC - Saint Vincent and the Grenadines 1 1 1 1 2 2 ZA - South Africa (Republic of) 1 1 0 0 1 1 AE - United Arab Emirates 1 1 0 0 1 1 AN - Bonaire, Sint Eustatius and Saba - Curaçao -…

1 1 0 0 1 1 AR - Argentine Republic 1 1 0 0 1 1 AU - Australia 1 1 0 0 1 1 BN - Brunei Darussalam 1 1 0 0 1 1 CI - Côte d'Ivoire (Republic of) 0 0 1 1 1 1 CM - Cameroon (Republic of) 1 0 0 0 1 0 CO - Colombia (Republic of) 1 1 0 0 1 1 EE - Estonia (Republic of) 1 1 0 0 1 1 FI - Finland 1 1 0 0 1 1 GD - Grenada 1 1 0 0 1 1 HU - Hungary 1 1 0 0 1 1 KH - Cambodia (Kingdom of) 1 1 0 0 1 1 KI - Kiribati (Republic of) 1 1 0 0 1 1 LU - Luxembourg 1 1 0 0 1 1 ML - Mali (Republic of) 1 1 0 0 1 1 MT - Malta 1 1 0 0 1 1 PE - Peru 1 1 0 0 1 1 SE - Sweden 0 0 1 0 1 0 SL - Sierra Leone 1 1 0 0 1 1 TH - Thailand 1 1 0 0 1 1 VU - Vanuatu (Republic of) Table 7. Ship count by Flag for ships with navstat = 7 or ship/cargo type = 30.

4.6.3 Number of ships per country, GoG area This section lists the number of ships (all categories) per country that occur within the narrower area of the Gulf of Guinea of Figure 8 (longitude –15° to 15°; latitude –10° to 11°) during 1 Oct 2012 – 31 Mar 2013.

Columns A and Asat correspond to the daily counts of Figure 25 (column A - black line; column Asat - blue line). Columns B and Bsat correspond to the daily counts of Figure 26 (column B - black line; column Bsat - blue line). Column A+B corresponds to the density map of Figure 8.

A Asat B Bsat A+B A+Bs Country | 897 206 27 21 924 227 ?? - Invalid MID 854 832 4 3 858 835 PA - Panama (Republic of) 724 705 0 0 724 705 LR - Liberia (Republic of) 608 585 1 1 609 586 MH - Marshall Islands (Republic of the) 346 321 1 1 347 322 MT - Malta 294 290 4 4 298 294 SG - Singapore (Republic of) 290 286 0 0 290 286 HK - Hong Kong (Special Administrative Region of… 278 273 1 0 279 273 BS - Bahamas (Commonwealth of the) 226 224 53 51 279 275 NG - Nigeria (Federal Republic of) 205 195 1 0 206 195 GR - Greece 198 198 6 6 204 204 VU - Vanuatu (Republic of) 200 194 3 3 203 197 CY - Cyprus (Republic of) 174 156 0 0 174 156 AG - Antigua and Barbuda 152 144 16 16 168 160 VC - Saint Vincent and the Grenadines 155 143 6 5 161 148 GB - United Kingdom of Great Britain and Northern… 129 115 0 0 129 115 NO - Norway 111 91 2 1 113 92 NL - Netherlands (Kingdom of the) 104 86 4 4 108 90 FR - France 108 90 0 0 108 90 IT - Italy 87 84 1 1 88 85 DK - Denmark 78 72 3 3 81 75 US - United States of America 66 65 6 5 72 70 CN - China (People's Republic of) 67 52 2 2 69 54 TR - Turkey 62 61 0 0 62 61 BM - Bermuda - United Kingdom of Great Britain… 61 43 0 0 61 43 ES - Spain 54 44 1 1 55 45 KR - Korea (Republic of) 54 52 0 0 54 52 LU - Luxembourg 50 47 0 0 50 47 GI - Gibraltar - United Kingdom of Great Britain… 47 45 1 0 48 45 BZ - Belize 44 44 4 4 48 48 TF - Kerguelen Islands - France 46 44 1 1 47 45 DE - Germany (Federal Republic of) 35 34 2 2 37 36 AN - Bonaire, Sint Eustatius and Saba - Curaçao -… 33 32 4 4 37 36 JP - Japan 30 27 5 5 35 32 KN - Saint Kitts and Nevis (Federation of) 32 31 2 2 34 33 KM - Comoros (Union of the) 32 30 1 1 33 31 BE - Belgium 31 23 1 1 32 24 KY - Cayman Islands - United Kingdom of Great… 29 17 0 0 29 17 RU - Russian Federation 23 21 0 0 23 21 TG - Togolese Republic 23 21 0 0 23 21 TH - Thailand 22 21 0 0 22 21 MY - Malaysia 22 22 0 0 22 22 PH - Philippines (Republic of the) 20 15 2 1 22 16 SL - Sierra Leone 20 17 1 1 21 18 CK - Cook Islands - New Zealand

19 19 0 0 19 19 AO - Angola (Republic of) 19 19 0 0 19 19 BB - Barbados 18 18 1 1 19 19 VN - Viet Nam (Socialist Republic of) 18 17 0 0 18 17 CH - Switzerland (Confederation of) 5 5 13 8 18 13 CM - Cameroon (Republic of) 12 12 4 4 16 16 GH - Ghana 16 15 0 0 16 15 PT - Madeira - Portugal 14 13 0 0 14 13 IN - India (Republic of) 14 9 0 0 14 9 KH - Cambodia (Kingdom of) 13 8 0 0 13 8 TZ - Tanzania (United Republic of) 10 10 2 2 12 12 HN - Honduras (Republic of) 11 9 0 0 11 9 HR - Croatia (Republic of) 8 6 2 2 10 8 PT - Portugal 9 9 0 0 9 9 BD - Bangladesh (People's Republic of) 9 7 0 0 9 7 BR - Brazil (Federative Republic of) 9 9 0 0 9 9 LT - Lithuania (Republic of) 8 8 1 0 9 8 SE - Sweden 8 8 0 0 8 8 DM - Dominica (Commonwealth of) 8 8 0 0 8 8 FO - Faroe Islands - Denmark 8 8 0 0 8 8 GQ - Equatorial Guinea (Republic of) 7 7 0 0 7 7 TV - Tuvalu 6 6 0 0 6 6 CV - Cape Verde (Republic of) 6 6 0 0 6 6 LK - Sri Lanka (Democratic Socialist Republic of) 6 6 0 0 6 6 ST - Sao Tome and Principe (Democratic Republic… 5 5 0 0 5 5 AU - Australia 5 5 0 0 5 5 EG - Egypt (Arab Republic of) 5 5 0 0 5 5 GA - Gabonese Republic 5 3 0 0 5 3 MD - Moldova (Republic of) 5 5 0 0 5 5 MP - Northern Mariana Islands (Commonwealth of… 5 5 0 0 5 5 SO - Somali Democratic Republic 4 3 0 0 4 3 AE - United Arab Emirates 4 4 0 0 4 4 BF - Burkina Faso 4 4 0 0 4 4 CD - Democratic Republic of the Congo 4 4 0 0 4 4 ID - Indonesia (Republic of) 4 4 0 0 4 4 KI - Kiribati (Republic of) 4 3 0 0 4 3 MA - Morocco (Kingdom of) 4 2 0 0 4 2 PL - Poland (Republic of) 4 2 0 0 4 2 UA - Ukraine 4 3 0 0 4 3 UY - Uruguay (Eastern Republic of) 2 2 2 2 4 4 ZA - South Africa (Republic of) 3 3 0 0 3 3 AR - Argentine Republic 3 3 0 0 3 3 AX - Alaska (State of) - United States of America 1 1 2 2 3 3 BJ - Benin (Republic of) 3 2 0 0 3 2 CL - Chile 1 1 2 2 3 3 FI - Finland 3 3 0 0 3 3 IS - Iceland 3 3 0 0 3 3 KW - Kuwait (State of) 3 2 0 0 3 2 MX - Mexico 3 3 0 0 3 3 PK - Pakistan (Islamic Republic of) 3 3 0 0 3 3 QA - Qatar (State of) 2 1 0 0 2 1 AD - Andorra (Principality of) 2 2 0 0 2 2 AW - Aruba (Netherlands) 2 0 0 0 2 0 BH - Bahrain (Kingdom of) 1 1 1 1 2 2 CA - Canada 2 2 0 0 2 2 EE - Estonia (Republic of) 2 1 0 0 2 1 FK - Falkland Islands (Malvinas) - United Kingdom… 2 1 0 0 2 1 IR - Iran (Islamic Republic of) 2 2 0 0 2 2 KE - Kenya (Republic of) 2 2 0 0 2 2 LY - Libya 2 2 0 0 2 2 ML - Mali (Republic of) 2 2 0 0 2 2 MW - Malawi 2 2 0 0 2 2 NE - Niger (Republic of the) 1 1 1 1 2 2 PT - Azores - Portugal 2 2 0 0 2 2 RE - Reunion (French Department of) - France 1 1 0 0 1 1 AL - Albania (Republic of) 1 1 0 0 1 1 BN - Brunei Darussalam 1 0 0 0 1 0 BO - Bolivia (Plurinational State of) 1 1 0 0 1 1 BT - Bhutan (Kingdom of) 0 0 1 1 1 1 BY - Belarus (Republic of) 1 1 0 0 1 1 CD - Congo (Republic of the) 1 1 0 0 1 1 CI - Côte d'Ivoire (Republic of) 1 1 0 0 1 1 DJ - Djibouti (Republic of) 1 1 0 0 1 1 ER - Eritrea 1 1 0 0 1 1 ET - Ethiopia (Federal Democratic Republic of) 1 1 0 0 1 1 GD - Grenada 0 0 1 1 1 1 GE - Georgia 1 1 0 0 1 1 GN - Guinea (Republic of) 1 1 0 0 1 1 IQ - Iraq (Republic of) 1 1 0 0 1 1 JM - Jamaica 1 1 0 0 1 1 JO - Jordan (Hashemite Kingdom of) 1 1 0 0 1 1 KP - Democratic People's Republic of Korea 1 1 0 0 1 1 LB - Lebanon

1 1 0 0 1 1 LV - Latvia (Republic of) 1 1 0 0 1 1 MC - Monaco (Principality of) 1 1 0 0 1 1 ME - Montenegro 1 1 0 0 1 1 MM - Myanmar (Union of) 1 1 0 0 1 1 MU - Mauritius (Republic of) 1 1 0 0 1 1 NA - Namibia (Republic of) 1 1 0 0 1 1 NC - New Caledonia - France 1 1 0 0 1 1 NI - Nicaragua 0 0 1 0 1 0 NZ - New Zealand 1 0 0 0 1 0 PE - Peru 1 1 0 0 1 1 PR - Puerto Rico - United States of America 1 1 0 0 1 1 SC - Seychelles (Republic of) 1 1 0 0 1 1 SN - Senegal (Republic of) 1 1 0 0 1 1 TM - Turkmenistan 1 1 0 0 1 1 UG - Uganda (Republic of) 1 1 0 0 1 1 VG - British Virgin Islands - United Kingdom of… 1 1 0 0 1 1 WF - Wallis and Futuna Islands - France Table 8. Ship count by Flag, all types, 6 months, area limited to GoG

4.6.4 Number of fishing ships per country, GoG area This section lists the number of fishing ships (navstat = 7 or ship/cargo type= 30) per country that occur within the narrower area of the Gulf of Guinea of Figure 8 (longitude –15° to 15°; latitude –10° to 11°) during 1 Oct 2012 – 31 Mar 2013.

Columns A and Asat correspond to the daily counts of Figure 28 (column A - black line; column Asat - blue line). Columns B and Bsat correspond to the daily counts of Figure 29 (column B - black line; column Bsat - blue line).

A Asat B Bsat A+B A+Bs Country | 17 15 9 3 26 18 ?? - Invalid MID 17 17 4 4 21 21 JP - Japan 17 11 0 0 17 11 FR - France 16 10 0 0 16 10 ES - Spain 12 11 0 0 12 11 BZ - Belize 10 9 0 0 10 9 KR - Korea (Republic of) 7 5 0 0 7 5 NG - Nigeria (Federal Republic of) 5 2 0 0 5 2 NL - Netherlands (Kingdom of the) 4 1 0 0 4 1 IT - Italy 4 3 0 0 4 3 MH - Marshall Islands (Republic of the) 4 4 0 0 4 4 PT - Portugal 4 4 0 0 4 4 RU - Russian Federation 3 3 0 0 3 3 GH - Ghana 3 3 0 0 3 3 LR - Liberia (Republic of) 2 2 0 0 2 2 BS - Bahamas (Commonwealth of the) 2 2 0 0 2 2 HK - Hong Kong (Special Administrative Region of… 2 2 0 0 2 2 IS - Iceland 2 2 0 0 2 2 KM - Comoros (Union of the) 2 2 0 0 2 2 KN - Saint Kitts and Nevis (Federation of) 2 1 0 0 2 1 NO - Norway 2 1 0 0 2 1 UY - Uruguay (Eastern Republic of) 1 1 0 0 1 1 AE - United Arab Emirates 1 1 0 0 1 1 AN - Bonaire, Sint Eustatius and Saba - Curaçao -… 1 1 0 0 1 1 AR - Argentine Republic 1 1 0 0 1 1 AU - Australia 1 1 0 0 1 1 BN - Brunei Darussalam 1 1 0 0 1 1 CI - Côte d'Ivoire (Republic of) 0 0 1 1 1 1 CM - Cameroon (Republic of) 1 1 0 0 1 1 CV - Cape Verde (Republic of) 1 1 0 0 1 1 CY - Cyprus (Republic of) 1 0 0 0 1 0 FK - Falkland Islands (Malvinas) - United Kingdom… 1 1 0 0 1 1 FO - Faroe Islands - Denmark 1 1 0 0 1 1 GB - United Kingdom of Great Britain and Northern… 1 1 0 0 1 1 GD - Grenada 1 0 0 0 1 0 GR - Greece 1 1 0 0 1 1 KH - Cambodia (Kingdom of) 1 1 0 0 1 1 LT - Lithuania (Republic of) 1 1 0 0 1 1 LU - Luxembourg 1 1 0 0 1 1 ML - Mali (Republic of) 1 1 0 0 1 1 MT - Malta 1 1 0 0 1 1 PA - Panama (Republic of) 1 1 0 0 1 1 PL - Poland (Republic of) 0 0 1 0 1 0 SL - Sierra Leone 1 1 0 0 1 1 TH - Thailand 1 1 0 0 1 1 UA - Ukraine 1 1 0 0 1 1 US - United States of America 1 1 0 0 1 1 VU - Vanuatu (Republic of)

0 0 1 1 1 1 ZA - South Africa (Republic of) Table 9. Ship count by Flag, fishing ships only, 6 months, area limited to GoG.

4.6.5 Passenger ships, cargo ships and tankers, GoG area This section combines a reduced version of the previous tables for the number of ships per country, for these three categories of ships. It retains only column A+B (i.e. all ships seen) and the two-letter country code. Still within the narrower area of the Gulf of Guinea of Figure 8 (longitude –15° to 15°; latitude –10° to 11°) during 1 Oct 2012 – 31 Mar 2013.

Passenger Cargo Tanker Num. Flag Num. Flag Num. Flag 33 NG 556 PA 246 MH 31 PA 417 LR 236 LR 20 MT 276 MH 149 PA 20 VC 231 HK 119 GR 19 VU 196 MT 109 MT 16 TF 147 AG 89 BS 14 US 136 SG 77 SG 13 MH 128 BS 53 HK 11 BS 111 CY 53 NO 11 LR 77 GB 48 BM 10 ?? 69 GR 37 NG 8 FR 69 NL 35 DK 7 CY 54 TR 33 GB 6 GB 48 IT 28 IT 4 HK 47 CN 23 CY 4 NO 35 NO 15 FR 3 BM 33 VC 13 ?? 3 ES 32 VU 12 CN 3 GR 31 DE 12 ES 3 PH 27 DK 11 TG 2 CM 27 GI 9 BE 2 CV 25 KR 9 GI 2 DE 22 NG 7 KN 2 IT 19 AN 7 NL 2 KM 19 PH 7 TR 2 LT 19 TH 7 VC 2 NL 17 BZ 6 KR 2 SG 17 US 6 MY 2 SL 17 VN 5 KM 1 AG 16 KY 5 LU 1 BE 15 BB 5 VU 1 CH 14 ?? 4 AG 1 CK 14 CH 4 AN 1 DK 14 CK 4 BZ 1 GI 13 KM 4 DE 1 GQ 11 BE 4 RU 1 HR 11 BM 4 SL 1 IS 10 JP 3 IN 1 KN 9 BD 3 JP 1 KR 9 KN 3 KH 1 LU 8 LT 3 KY 1 MA 8 LU 3 PT 1 MD 8 RU 3 US 1 MX 7 SL 2 AE 1 NE 6 FR 2 AO 1 NZ 6 IN 2 BR 1 PT 6 KH 2 HR 1 RU 6 TZ 2 KI 1 SO 5 HR 2 LY 1 TG 5 LK 2 QA 1 TH 5 SE 2 SO 1 TR 5 TG 2 TH 1 TZ 4 DM 2 TZ 1 UG 4 MY 1 AR 1 VG 3 AO 1 BB

1 WF 3 BR 1 CH 1 ZA 3 ES 1 CK 3 GH 1 CL 3 KI 1 CM 3 PK 1 CV 3 PT 1 DM 2 CL 1 GE 2 EG 1 GQ 2 MD 1 KP 2 TV 1 KW 1 CV 1 MD 1 EE 1 PH 1 FI 1 PL 1 FO 1 SC 1 GA 1 TV 1 ID 1 UA 1 JM 1 UY 1 LB 1 MA 1 ME 1 MX 1 NA 1 PT 1 SO 1 ST 1 TF 1 UA 1 UY 285 3,168 1,552

Table 10. Passenger ship, cargo ship and tanker count by Flag, 6 months, area limited to GoG.

4.7 Density maps per month The same selections as before, where they were combined over 6 months, are now shown per separate month, in consecutive order from Oct 2012 – Mar 2013:  All ship traffic;  Class B ship traffic;  Engaged in fishing (navstat = 7);  Fishing ships (navstat = 7 or ship/cargo type = 30);  Passenger ships (ship/cargo type = 60-69).

However, tankers and cargo ships are not shown per month because their distribution is rather constant over time.

4.7.1 All ship traffic, per month The distributions are dominated by the main shipping routes, coastal traffic in the Gulf of Guinea, and – especially visible in the south-west quadrant – small concentrations that are likely due to fishing activity. Except from the fisheries activity, the patterns change little from month to month. The total number of ships varies around 5,000 per month.

4.7.2 Class B ship traffic, per month In Oct, Jan, Feb and Mar, the number of Class B ships is around 300 per month; in Nov and Dec , the number increases to around 500, and concentrations appear in the north-west corner, likely related to pleasure boats crossing the Atlantic. Compare with the peak in daily number of Class B ships at the end of Nov in Figure 17.

4.7.3 Engaged in fishing (navstat = 7), per month These maps show the distribution of fishing activity. One can recognise fishing activities close to the coast, and also in the open sea. Most activity is out in the Atlantic. The distributions show considerable change from month to month. The total number of ships per month is relatively stable around 65.

4.7.4 Fishing ships (navstat = 7 or ship/cargo type = 30), per month These distributions are more complete in showing fishing vessels, but also more contaminated with fishing vessels that are transiting rather than actually fishing. The monthly number of ships hovers around 215, much larger than seen before with only navstat = 7 which was around 65.

Also see section 4.7.5 for what might be additional fishing activity.

4.7.5 Passenger ships (ship/cargo type = 60-69), per month Most of this traffic is along the coast, plus some sea crossing routes. Some activity in the south- west part varies from month to month and is more reminiscent of fishing, because it is not clear why passengers should be carried around there; possibly use of a wrong ship/cargo type.

5 Conclusions The report has looked into geographical distributions, aggregated numbers and statistics of ships as extracted from the cooperative data, mainly AIS, gathered during the PMAR Gulf of Guinea campaign. About 12,000 ships have been detected in the entire campaign area, which covered the Gulf of Guinea and its approaches along West Africa. In the narrower Gulf of Guinea, about 7,000 ships have been seen during the 6 months. Whereas density maps show that cargo ships and oil tankers normally follow the major maritime traffic routes across the Atlantic Ocean and along the coast of Africa, the position reports from the fishing fleet shows high concentrations on the fishing grounds as well as how the fishing areas change seasonally. Also, vessels with AIS Class B equipment (voluntary use) show a very different distribution than those with Class A equipment (mandatory use). Looking at the difference between the number of ships detected by satellite AIS only and the number when including also coastal AIS, it is seen that the contribution of the terrestrial (MSSIS) stations is approximately an additional 500 ships in Class A and 200 ships in Class B.

The Flags with the largest number of ships are Panama, Liberia and Marshall Islands, followed at some distance by Malta. This is true both for the entire area, and for the smaller Gulf of Guinea area (excluding West Africa). About 2 % of the ships have an invalid MID (country code) in their MMSI; however, these may contain special cases like SAR aircraft, daughter ships or regionally assigned MMSIs.

This report contains only a fraction of the statistics and maps that can be extracted from the data that were collected. On the full digital data set, one can run queries as desired, e.g. to plot the positions of all Singapore-flagged tankers in front of Ghana, or to count the number of Nigerian passenger ships during the first two weeks of January 2013, to name but two examples.

The accuracy and completeness of the numbers are, at any rate, only as good as what the ships divulge on their AIS. While the less careful operators may not always keep their AIS up to date, Coast Guards and Port Authorities have a role to enforce correct use of AIS. In any case, the amount of information that is provided in the data analysed here represents an order of magnitude improvement over the existing maritime awareness in the region, which can and should be used by the relevant maritime authorities and decision makers for policy development and implementation.

Acknowledgements The data used in this study were partly commercially bought and partly provided free of charge by government authorities. The LRIT data have been kindly provided by the governments of the countries that participate to the EU LRIT Data Centre, with the Italian Coast Guard providing Italian LRIT data from an early stage. EMSA has kindly handled the technical provision and together with DG MOVE coordinated in the request. Data from two AIS satellites, AISSat-1 and NORAIS, have been kindly provided by the Norwegian Coastal Administration and, in an early phase, by FFI. Access to the MSSIS data was kindly provided by the Volpe Centre of the U.S. Department of Transportation and by the U.S. Navy. Also the technical support of the commercial providers exactEarth and LuxSpace is acknowledged.

References [1] Brochure “PMAR – Piracy, Maritime Awareness and Risks, Maritime awareness tailored for authorities in piracy affected regions, Gulf of Guinea”, September 2013, JRC84131 [2] Klaas Deves et al., “PMAR II – Pilot Project on Piracy Maritime Awareness and Risks – Maritime awareness tailored for authorities in the Gulf of Guinea”, JRC Scientific and Policy Report JRC87134, Luxembourg: Publications Office of the European Union, December 2013 (Limited distribution) [3] ITU, “Recommendation ITU-R M.1371-4 – Technical characteristics for an automatic identification system using time-division multiple access in the VHF maritime mobile band”, M Series: Mobile, radiodetermination, amateur and related satellite services (04/2010) [4] James K.E. Tunaley, “Utility of Various AIS Messages for Maritime Awareness”, 9th Advanced SAR Workshop, 15-18 Oct 2013, Longueuil, Quebec [5] Torkild Eriksen, “Quality of AIS services in the PMAR-2 campaign”, JRC Scientific and Policy Report JRC 86165, Luxembourg: Publications Office of the European Union, November 2013 (Limited distribution) [6] Torkild Eriksen, Harm Greidanus, Michele Vespe, “LRIT contributions in the PMAR campaigns”, JRC Scientific and Policy Report JRC84888, Luxembourg: Publications Office of the European Union, October 2013 (Limited distribution) [7] ITU website http://www.itu.int/online/mms/glad/cga_mids.sh?lng=E [8] GPSD site http://catb.org/gpsd/AIVDM.html#_type_5_static_and_voyage_related_data

European Commission JRC87225 – Joint Research Centre – Institute for the Protection and Security of the Citizen

Title: Ship traffic distributions in the Gulf of Guinea and off West Africa

Author(s): Harm Greidanus, Marlene Alvarez, Torkild Eriksen, Thomas Barbas

Luxembourg: Publications Office of the European Union

2013 – 58 pp. – 21.0 x 29.7 cm

Abstract

The PMAR (Piracy, Maritime Awareness and Risks) - Gulf of Guinea project was run to increase the maritime awareness of the authorities around the Gulf of Guinea. As part of the project, 6 months of maritime surveillance data have been collected from ship reporting systems (AIS, LRIT). The area of collection was over the Gulf of Guinea and West Africa, in the box 10° South to 30° North, by 30° West to 15° East. The period was 1 Oct 2012 – 31 Mar 2013. This report shows statistics derived from these 6 months of data, in the form of ship traffic density maps per ship category at a grid size of 0.1°x0.1°, daily ship counts, and composition of the fleets by Flag. It is found that the grand total number of different ships seen during the entire 6 months period is about 12,000; while the daily average number of ships is about 2,500. For fishing ships, passenger ships, cargo ships and tankers, the average daily numbers are 125, 190, 850, and 505 respectively. The activity of passenger ships, cargo ships and tankers is relatively constant over the period, whereas the activity of fishing ships and yachts changes much from month to month.

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