1 Data information

1.1 Metadata

2 Geographical extent

2.1 Coordinates
2.2 Defined area

3 Shipping density

3.1 Fishing
3.2 Service
3.3 Dredging
3.4 Sailing
3.5 Pleasure Craft
3.6 High Speed craft
3.7 Tug and towing
3.8 Passenger
3.9 Cargo
3.10 Tanker
3.11 Military
3.12 Other
3.13 Unknown

4 Statistics

4.1 Distribution
4.2 Global traffic

5 Hierarchical clustering

5.1 Yearly densities
5.2 Classification by activities
5.3 Maritime activities clusters
5.4 Boxplot

6 All data

7 Open-notebook

1 Data information

EMODnet Vessel Density maps were created by Cogea in 2019 in the framework of EMODnet Human Activities, an initiative funded by the EU Commission. The maps are based on AIS data purchased by Collecte Localisation Satellites (CLS) and ORBCOMM. The maps show shipping density in 1km*1km cells of a grid covering all EU waters (and some neighbouring areas). Density is expressed as hours per square kilometre per month. The following ship types are available:0 Other, 1 Fishing, 2 Service, 3 Dredging or underwater ops, 4 Sailing, 5 Pleasure Craft, 6 High speed craft, 7 Tug and towing, 8 Passenger, 9 Cargo, 10 Tanker, 11 Military and Law Enforcement, 12 Unknown and All ship types. Data are available by month of year.

1.1 Metadata

Access metadata from dataset’s landing page

2 Geographical extent

2.1 Coordinates

## [1] "West-Longitude: -7"

## [1] "South-Latitude: 35.2"

## [1] "East-Longitude: -4.3"

## [1] "North-Latitude: 36.9"

Add another dataset for defined area to dashboard

2.2 Defined area

Map tiles by Stamen Design, under CC BY 3.0. Data by OpenStreetMap, under ODbL.

3 Shipping density

3.1 Fishing

3.2 Service

3.3 Dredging

3.4 Sailing

3.5 Pleasure Craft

3.6 High Speed craft

3.7 Tug and towing

3.8 Passenger

3.9 Cargo

3.10 Tanker

3.11 Military

3.12 Other

3.13 Unknown

4 Statistics

4.1 Distribution

4.1.1 Annual means

ABCDEFGHIJ0123456789

allgroup <fctr>	mean2017 <dbl>	mean2018 <dbl>	mean2019 <dbl>	mean2020 <dbl>
fishing	8.0506608	7.42580779	8.51931508	8.21028206
service	4.4062502	4.89831281	5.43435427	5.99649320
dredging	0.8226631	0.56132299	0.83147905	1.27061919
sailing	12.6984487	16.10681309	18.97677791	18.02878440
pleasure	9.9042804	10.77489282	13.03092529	15.74709328
speedcraft	2.0554098	2.12755064	2.14193982	1.56899639
tug	6.2837234	6.48421186	7.28118518	7.41362641
passenger	4.5143983	4.17658509	4.24561704	3.84886647
cargo	25.9121281	24.99368699	25.81384261	25.53499679
tanker	18.3345391	17.31556325	18.92142880	20.48990941

4.1.2 Annual percentages

ABCDEFGHIJ0123456789

allgroup <fctr>	mean2017 <dbl>	mean2018 <dbl>	mean2019 <dbl>	mean2020 <dbl>
fishing	7.8056817	7.04853047	7.36729242	6.99978680
service	4.2721694	4.64944799	4.69949482	5.11239122
dredging	0.7976297	0.53280428	0.71904246	1.08328354
sailing	12.3120388	15.28848660	16.41064696	15.37068351
pleasure	9.6028962	10.22746111	11.26882106	13.42539694
speedcraft	1.9928643	2.01945781	1.85229644	1.33766906
tug	6.0925117	6.15477348	6.29658839	6.32058727
passenger	4.3770265	3.96438854	3.67150434	3.28140307
cargo	25.1236301	23.72385193	22.32317098	21.77020620
tanker	17.7766247	16.43582473	16.36278243	17.46894886

4.2 Global traffic

ABCDEFGHIJ0123456789

year <fctr>	value <dbl>
2017	103.1385
2018	105.3526
2019	115.6370
2020	117.2933

5 Hierarchical clustering

5.1 Yearly densities

Yearly Vessel densities (2017-2020) by activity type:

Dredging
Fishing
Sailing
Services
Transport

5.2 Classification by activities

Classification of vessel densities by activity type

5.3 Maritime activities clusters

Overall classification of maritime activities seen by AIS

5.4 Boxplot

Boxplot of the maritime activities by clusters

6 All data

Monthly means (hours/km²)

## [1] "01/ Fishing"

ABCDEFGHIJ0123456789

Month <dbl>	Year_2017 <dbl>	Year_2018 <dbl>	Year_2019 <dbl>	Year_2020 <dbl>
1	0.6108688	0.5880735	0.6605662	0.7715435
2	0.6178748	0.5191840	0.5376957	0.6123209
3	0.7100898	0.4689330	0.5766815	0.6144904
4	0.5503912	0.6287652	0.6743150	0.5857650
5	0.7768397	0.7326926	0.8160629	0.6332067
6	0.7662899	0.7537893	0.8620067	0.7581769
7	0.9336770	0.7803660	0.9686872	0.9992857
8	0.8777836	0.8380817	0.9379882	0.8450099
9	0.5297062	0.4819090	0.6361941	0.6044940
10	0.3469233	0.3196354	0.4463916	0.3987188

## [1] "02/ Service"

ABCDEFGHIJ0123456789

Month <dbl>	Year_2017 <dbl>	Year_2018 <dbl>	Year_2019 <dbl>	Year_2020 <dbl>
1	0.3850566	0.4293865	0.4272640	0.5384807
2	0.3088939	0.4173038	0.3981361	0.4821898
3	0.3258017	0.4224510	0.4233367	0.5265035
4	0.3284670	0.4307533	0.4231600	0.4780895
5	0.3634140	0.3830303	0.4403868	0.4947541
6	0.3762890	0.3699944	0.4586674	0.4495698
7	0.3998438	0.4049169	0.4628639	0.4856928
8	0.3843678	0.4198001	0.4928534	0.5184386
9	0.3948494	0.3861715	0.4702772	0.4942727
10	0.3855162	0.4319676	0.5141351	0.5426347

## [1] "03/ Dredging"

ABCDEFGHIJ0123456789

Month <dbl>	Year_2017 <dbl>	Year_2018 <dbl>	Year_2019 <dbl>	Year_2020 <dbl>
1	0.04122265	0.03669450	0.05724133	0.08973581
2	0.08494949	0.03419805	0.03050764	0.08606102
3	0.12587400	0.04060976	0.04625780	0.12881500
4	0.08145469	0.01783526	0.05164916	0.13332514
5	0.08282264	0.03866281	0.07359079	0.16563689
6	0.05416182	0.07741820	0.08291096	0.11813000
7	0.04631037	0.04811893	0.09169240	0.13134053
8	0.08080402	0.04663836	0.09849552	0.11533447
9	0.05438066	0.05080146	0.09665734	0.10299450
10	0.06594276	0.04958092	0.09769491	0.07977459

## [1] "04/ Sailing"

ABCDEFGHIJ0123456789

Month <dbl>	Year_2017 <dbl>	Year_2018 <dbl>	Year_2019 <dbl>	Year_2020 <dbl>
1	0.6651006	0.9744020	1.1221886	1.3576909
2	0.7057397	0.8053906	0.9773372	1.0862214
3	0.8989341	1.0128979	1.1760169	1.3965001
4	1.0003586	1.1843424	1.2746566	0.9534378
5	1.0519602	1.5047277	1.5331983	1.2011134
6	1.0883325	1.3927843	1.7422094	1.5483629
7	1.3370188	1.5266319	1.9694782	1.8508349
8	1.3481975	1.6154659	2.0931324	1.9628657
9	1.2629974	1.3792366	1.8836394	1.7869565
10	1.3486335	1.8826768	2.0817820	1.7261022

## [1] "05/ Pleasure Craft"

ABCDEFGHIJ0123456789

Month <dbl>	Year_2017 <dbl>	Year_2018 <dbl>	Year_2019 <dbl>	Year_2020 <dbl>
1	0.6300160	0.7105277	0.7018020	1.054294
2	0.6536374	0.6284405	0.6360769	1.022854
3	0.7443885	0.7343096	0.7032414	1.305418
4	0.8741349	0.8131860	0.9109632	1.065758
5	0.9299396	0.9535570	1.1146965	1.182145
6	0.9933539	1.1179897	1.3111954	1.415551
7	0.9525552	1.0577538	1.2500434	1.718356
8	0.9035648	1.1718683	1.5009404	1.709386
9	0.8585271	0.8884483	1.2773622	1.416804
10	0.8526686	0.9307630	1.3296180	1.424541

## [1] "06/ High Speed Craft"

ABCDEFGHIJ0123456789

Month <dbl>	Year_2017 <dbl>	Year_2018 <dbl>	Year_2019 <dbl>	Year_2020 <dbl>
1	0.1722716	0.1679045	0.2069328	0.15778535
2	0.1308754	0.1600911	0.1910552	0.13274394
3	0.1321843	0.1831117	0.1868936	0.15134852
4	0.1674557	0.1542807	0.1669978	0.13162988
5	0.2075015	0.1620622	0.1786238	0.15432868
6	0.1768661	0.1615532	0.1750174	0.12522522
7	0.1744034	0.1657077	0.1786355	0.12885292
8	0.1987965	0.1849624	0.1858922	0.12125779
9	0.2102007	0.2021128	0.1683701	0.09611635
10	0.1698570	0.2024188	0.1980329	0.10203057

## [1] "07/ Tug and Towing"

ABCDEFGHIJ0123456789

Month <dbl>	Year_2017 <dbl>	Year_2018 <dbl>	Year_2019 <dbl>	Year_2020 <dbl>
1	0.5409044	0.5363761	0.6335465	0.6508779
2	0.5369415	0.4770483	0.5709086	0.5312667
3	0.6045230	0.4864353	0.5620256	0.6217696
4	0.5173706	0.4940452	0.5848010	0.5626507
5	0.5381895	0.4954636	0.5868520	0.6341901
6	0.5201103	0.5137658	0.6077858	0.6015082
7	0.5074039	0.5528383	0.6229055	0.6240460
8	0.4901525	0.5465848	0.6257047	0.6286633
9	0.4761945	0.5130166	0.5640761	0.6206123
10	0.5109273	0.5781669	0.6958768	0.6689202

## [1] "08/ Passenger"

ABCDEFGHIJ0123456789

Month <dbl>	Year_2017 <dbl>	Year_2018 <dbl>	Year_2019 <dbl>	Year_2020 <dbl>
1	0.3271864	0.2474840	0.3109501	0.2625761
2	0.2903538	0.2459118	0.2710695	0.2462884
3	0.3937222	0.2286112	0.3320819	0.2959848
4	0.4068619	0.3507525	0.3570002	0.2943011
5	0.4636257	0.4065319	0.3899678	0.3279791
6	0.3604207	0.3952259	0.3682289	0.2723452
7	0.4102415	0.4123741	0.4061142	0.3203454
8	0.4221067	0.4242736	0.4581967	0.3818146
9	0.4229964	0.3768247	0.4032515	0.3562783
10	0.3667655	0.4162570	0.3772820	0.3769517

## [1] "09/ Cargo"

ABCDEFGHIJ0123456789

Month <dbl>	Year_2017 <dbl>	Year_2018 <dbl>	Year_2019 <dbl>	Year_2020 <dbl>
1	1.976117	2.152407	2.078601	2.067082
2	2.076067	2.031439	1.863201	1.840221
3	2.155467	2.279675	1.997806	2.209933
4	2.084073	2.230307	2.051817	2.116089
5	2.192072	2.035031	2.143761	2.223131
6	2.213091	2.030620	2.089466	2.202622
7	2.475244	2.270812	2.135667	2.284040
8	2.463301	2.093033	2.405613	2.314165
9	2.082791	1.914555	2.292237	2.162606
10	2.146988	1.944422	2.434751	2.050508

## [1] "10/ Tanker"

ABCDEFGHIJ0123456789

Month <dbl>	Year_2017 <dbl>	Year_2018 <dbl>	Year_2019 <dbl>	Year_2020 <dbl>
1	1.273552	1.413444	1.611961	1.780969
2	1.538876	1.325603	1.462650	1.387019
3	1.654613	1.461438	1.554582	1.788953
4	1.485432	1.387868	1.443392	1.726108
5	1.551642	1.442051	1.573353	1.787346
6	1.536499	1.419262	1.517669	1.804241
7	1.693260	1.578531	1.541384	1.849450
8	1.529381	1.588570	1.769707	1.751162
9	1.565854	1.388026	1.630373	1.715854
10	1.574019	1.491360	1.623915	1.757632

## [1] "11/ Military and Law Enforcement"

ABCDEFGHIJ0123456789

Month <dbl>	Year_2017 <dbl>	Year_2018 <dbl>	Year_2019 <dbl>	Year_2020 <dbl>
1	0.1376485	0.1279869	0.10397285	0.09395124
2	0.1194496	0.1288574	0.09631454	0.07251844
3	0.1335506	0.1157082	0.11458860	0.13069413
4	0.1213610	0.1284157	0.13271801	0.08234133
5	0.1523485	0.1208267	0.11098833	0.11459705
6	0.1097399	0.1230898	0.10782647	0.09586469
7	0.1384065	0.1490304	0.13034707	0.11681016
8	0.1136013	0.1548790	0.13778597	0.15214339
9	0.1078459	0.1292016	0.10796126	0.12649895
10	0.1229442	0.1167085	0.14353752	0.10796642

## [1] "12/ Other"

ABCDEFGHIJ0123456789

Month <dbl>	Year_2017 <dbl>	Year_2018 <dbl>	Year_2019 <dbl>	Year_2020 <dbl>
1	0.5946866	0.7259486	0.7935603	0.6711185
2	0.6276783	0.6766756	0.6734820	0.5564249
3	0.6258788	0.7317804	0.7113009	0.6651807
4	0.5828292	0.7345496	0.7235061	0.5147255
5	0.7573311	0.7378711	0.7546566	0.5963994
6	0.7069110	0.7741899	0.7519883	0.7881804
7	0.7510910	0.7675495	0.8259069	0.8592080
8	0.7864586	0.7872798	0.7248400	0.7295205
9	0.8175504	0.6394661	0.6973884	0.5465148
10	0.8199370	0.7707637	0.7463174	0.6878314

## [1] "13/ Unknown"

ABCDEFGHIJ0123456789

Month <dbl>	Year_2017 <dbl>	Year_2018 <dbl>	Year_2019 <dbl>	Year_2020 <dbl>
1	0.0065568340	0.002394662	0.017198256	0.0052709551
2	0.0130701001	0.010869050	0.001688491	0.0024508123
3	0.0123127812	0.007028773	0.001910596	0.0000000000
4	0.0103625925	0.009456815	0.009037977	0.0025898554
5	0.0111111316	0.007475952	0.003924066	0.0000000000
6	0.0140995057	0.003126098	0.004581001	0.0007440319
7	0.0145831493	0.004460508	0.004693507	0.0006472661
8	0.0107018881	0.003923765	0.004243503	0.0023016463
9	0.0158545216	0.005903222	0.008260110	0.0013406053
10	0.0082317872	0.003780121	0.001535545	0.0015509746

## [1] "14/ Global traffic"

ABCDEFGHIJ0123456789

Month <dbl>	Year_2017 <dbl>	Year_2018 <dbl>	Year_2019 <dbl>	Year_2020 <dbl>
1	7.361188	8.113030	8.725786	9.501376
2	7.704407	7.461013	7.710123	8.058581
3	8.517339	8.172990	8.386724	9.835591
4	8.210552	8.564558	8.804014	8.646811
5	9.078797	9.019984	9.720061	9.514827
6	8.916165	9.132808	10.079553	10.180521
7	9.834039	9.719091	10.588418	11.368910
8	9.609218	9.875361	11.435393	11.232064
9	8.799748	8.355672	10.236047	10.031343
10	8.719354	9.138501	10.690870	9.925162

7 Open-notebook

Access MyBinder.org/Marine-Analyst virtual environment.
More info at Marine-Analyst.eu

This document produced by Marine-analyst.eu is licensed under CC BY-NC 4.0

MSP: Maritime activities seen by AIS

Document produced by http://www.marine-analyst.eu (Dubroca L., Cariou T., Derycke P.)

07 October, 2022

1 Data information

1.1 Metadata

2 Geographical extent

2.1 Coordinates

2.2 Defined area

3 Shipping density

3.1 Fishing

3.2 Service

3.3 Dredging

3.4 Sailing

3.5 Pleasure Craft

3.6 High Speed craft

3.7 Tug and towing

3.8 Passenger

3.9 Cargo

3.10 Tanker

3.11 Military

3.12 Other

3.13 Unknown

4 Statistics

4.1 Distribution

4.1.1 Annual means

4.1.2 Annual percentages

4.2 Global traffic

5 Hierarchical clustering

5.1 Yearly densities

5.2 Classification by activities

5.3 Maritime activities clusters

5.4 Boxplot

6 All data

7 Open-notebook