Ship traffic distributions and statistics in the Gulf of Guinea and … · 2016-06-03 · 1 2013 Harm Greidanus, Marlene Alvarez, Torkild Eriksen, Thomas Barbas Ship traffic distributions

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Harm Greidanus, Marlene Alvarez, Torkild Eriksen, Thomas Barbas

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

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

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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/

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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.

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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

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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,

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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:

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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 occur only once and have

an invalid MID code

Removed MMSIs that occur only once

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.

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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

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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.

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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.

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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

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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.

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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”).

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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.

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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.

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

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

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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.

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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.

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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.

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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.

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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.


between 1 Oct 2012 and 31 Mar 2013, whole region; Class B.

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Figure 21. Daily number of passenger ships (ship/cargo type = 60-69) between 1 Oct

2012 and 31 Mar 2013, whole region; Class A.


2012 and 31 Mar 2013, whole region; Class B.

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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.

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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.

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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.

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between 1 Oct 2012 and 31 Mar 2013, Gulf of Guinea area only; Class A.


between 1 Oct 2012 and 31 Mar 2013, Gulf of Guinea area only; Class B.

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2012 and 31 Mar 2013, Gulf of Guinea area only; Class A.


2012 and 31 Mar 2013, Gulf of Guinea area only; Class B.

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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.

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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…

30

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

31

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.

32

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 of) 1 0 VC Saint 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.

33

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)

34

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.


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





11 11 1 1 12 12 PT - Portugal



8 6 0 0 8 6 NO - Norway






4 1 0 0 4 1 IT - Italy




3 3 0 0 3 3 GH - Ghana

3 2 0 0 3 2 GR - Greece


3 3 0 0 3 3 UA - Ukraine

2 0 0 0 2 0 BE - Belgium




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









35


1 1 0 0 1 1 AU - Australia




1 0 0 0 1 0 CO - Colombia (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 LU - Luxembourg


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


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.



black line; column Bsat - blue line). Column A+B corresponds to the density map of Figure 8.


897 206 27 21 924 227 ?? - Invalid MID




346 321 1 1 347 322 MT - Malta

294 290 4 4 298 294 SG - Singapore (Republic of)




205 195 1 0 206 195 GR - Greece



174 156 0 0 174 156 AG - Antigua and Barbuda



129 115 0 0 129 115 NO - Norway


104 86 4 4 108 90 FR - France

108 90 0 0 108 90 IT - Italy

87 84 1 1 88 85 DK - Denmark



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 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)


33 32 4 4 37 36 JP - Japan



32 30 1 1 33 31 BE - Belgium

31 23 1 1 32 24 KY - Cayman Islands - United Kingdom of Great…


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

36

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)


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)


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)


8 8 1 0 9 8 SE - Sweden

8 8 0 0 8 8 DM - Dominica (Commonwealth of)


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 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 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 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 2 0 0 4 2 UA - Ukraine




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 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 MW - Malawi

2 2 0 0 2 2 NE - Niger (Republic of the)


2 2 0 0 2 2 RE - Reunion (French Department of) - France

1 1 0 0 1 1 AL - Albania (Republic of)


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 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

37


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.



black line; column Bsat - blue line).


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




4 1 0 0 4 1 IT - Italy


4 4 0 0 4 4 PT - Portugal


3 3 0 0 3 3 GH - Ghana




2 2 0 0 2 2 IS - Iceland



2 1 0 0 2 1 NO - Norway














1 1 0 0 1 1 GD - Grenada

1 0 0 0 1 0 GR - Greece



1 1 0 0 1 1 LU - Luxembourg


1 1 0 0 1 1 MT - Malta



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



38


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

39

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.

40

41

42

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.

43

44

45

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.

46

47

48

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.

49

50

51

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.

52

53

54

55

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.

56

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

http://www.itu.int/online/mms/glad/cga_mids.sh?lng=E

http://catb.org/gpsd/AIVDM.html#_type_5_static_and_voyage_related_data

57

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.

58

As the Commission’s in-house science service, the Joint Research Centre’s mission is to provide

EU policies with independent, evidence-based scientific and technical support throughout the

whole policy cycle.

Working in close cooperation with policy Directorates-General, the JRC addresses key societal

challenges while stimulating innovation through developing new standards, methods and tools,

and sharing and transferring its know-how to the Member States and international community.

Key policy areas include: environment and climate change; energy and transport; agriculture

and food security; health and consumer protection; information society and digital agenda;

safety and security including nuclear; all supported through a cross-cutting and multi-

disciplinary approach.

Documents

Ship traffic distributions and statistics in the Gulf of Guinea and … · 2016-06-03 · 1 2013 Harm Greidanus, Marlene Alvarez, Torkild Eriksen, Thomas Barbas Ship traffic distributions