1 MPA information

2 Data information

2.1 Metadata

3 Geographical extent

3.1 Coordinates
3.2 MPA area

4 Shipping density

4.1 Fishing
4.2 Service
4.3 Dredging
4.4 Sailing
4.5 Pleasure Craft
4.6 High Speed craft
4.7 Tug and towing
4.8 Passenger
4.9 Cargo
4.10 Tanker
4.11 Military
4.12 Other
4.13 Unknown

5 Statistics

5.1 Distribution
5.2 Global traffic

6 Hierarchical clustering

6.1 Yearly densities
6.2 Classification by activities
6.3 Maritime activities clusters
6.4 Boxplot

7 All data

8 Open-notebook

1 MPA information

Wdpaid:	555539441
Pa_def:	1
Name:	Tte de Canyon du Cap Ferret
Orig_name:	Tte de Canyon du Cap Ferret
Desig:	Special Protection Area (Birds Directive)
Desig_eng:	Special Protection Area (Birds Directive)
Desig_type:	Regional
Iucn_cat:	Not Reported
Int_crit:	Not Applicable
Marine:	2
Rep_m_area:	0
Gis_m_area:	3654.12517516074
Rep_area:	3656.39
Gis_area:	3654.12517515975
Not_take:	Not Reported
Not_tk_take:	0
Status:	Designated
Status_yr:	2009
Gov_type:	Federal or national ministry or agency
Own_type:	Not Reported
Mang_auth:	Not Reported
Mang_plan:	Not Reported
Verif:	State Verified
Metadata_i:	1832
Sub_loc:	Not Reported
Parent_iso:	FRA
Iso3:	FRA

2 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.

2.1 Metadata

Access metadata from dataset’s landing page

3 Geographical extent

3.1 Coordinates

## [1] "West-Longitude: -2.61"

## [1] "South-Latitude: 44.47"

## [1] "East-Longitude: -1.92"

## [1] "North-Latitude: 45.07"

3.2 MPA area

3.2.1 Topography

3.2.2 Geographical location

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

4 Shipping density

4.1 Fishing

4.2 Service

4.3 Dredging

## ERROR: No data available

4.4 Sailing

4.5 Pleasure Craft

4.6 High Speed craft

4.7 Tug and towing

4.8 Passenger

4.9 Cargo

4.10 Tanker

4.11 Military

4.12 Other

4.13 Unknown

5 Statistics

5.1 Distribution

5.1.1 Annual means

ABCDEFGHIJ0123456789

allgroup <fctr>	mean2017 <dbl>	mean2018 <dbl>	mean2019 <dbl>	mean2020 <dbl>
fishing	7.410181553	6.211176217	6.06966829	7.3741245027
service	0.060904024	0.055298428	0.04367831	0.0818068085
dredging	0.000000000	0.000000000	0.00000000	0.0000000000
sailing	0.039085122	0.099823686	0.10402070	0.0841682826
pleasure	0.024826731	0.071450179	0.10005928	0.1316326235
speedcraft	0.000000000	0.000000000	0.00000000	0.0040969781
tug	0.004316377	0.002667646	0.00355502	0.0010551651
passenger	0.037878802	0.039142489	0.04037552	0.0029916410
cargo	0.269269740	0.336277277	0.33518559	0.3367188214
tanker	0.101132881	0.102872070	0.10277527	0.0710442370

5.1.2 Annual percentages

ABCDEFGHIJ0123456789

allgroup <fctr>	mean2017 <dbl>	mean2018 <dbl>	mean2019 <dbl>	mean2020 <dbl>
fishing	79.32456675	71.47412258	74.60804120	87.956653518
service	0.65196585	0.63633786	0.53689144	0.975770495
dredging	0.00000000	0.00000000	0.00000000	0.000000000
sailing	0.41839870	1.14870520	1.27861694	1.003937548
pleasure	0.26576538	0.82220157	1.22992342	1.570079953
speedcraft	0.00000000	0.00000000	0.00000000	0.048867697
tug	0.04620598	0.03069751	0.04369812	0.012585737
passenger	0.40548528	0.45042597	0.49629380	0.035683521
cargo	2.88248072	3.86965729	4.12008350	4.016295181
tanker	1.08260801	1.18378399	1.26330816	0.847397320

5.2 Global traffic

ABCDEFGHIJ0123456789

year <fctr>	value <dbl>
2017	9.341597
2018	8.690105
2019	8.135408
2020	8.383817

6 Hierarchical clustering

6.1 Yearly densities

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

Dredging
Fishing
Sailing
Services
Transport

6.2 Classification by activities

Classification of vessel densities by activity type

6.3 Maritime activities clusters

Overall classification of maritime activities seen by AIS

6.4 Boxplot

Boxplot of the maritime activities by clusters

7 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	0.2474129	0.4006571	0.5875426	0.57486189
2	0.4217629	0.2405335	0.3269291	0.32941692
3	0.3185358	0.2817864	0.3741550	0.27743475
4	0.8771265	0.4172466	0.4616740	0.74088449
5	0.7595750	0.9828852	0.4957697	1.12237490
6	0.4605999	0.7928464	0.8624694	0.92866906
7	0.8250082	0.8060435	0.5706375	1.23936986
8	0.7001432	0.3798941	0.6996074	1.18416721
9	1.2215069	0.5624479	0.5688206	0.32441552
10	0.7385903	0.3888184	0.6060764	0.20074223

## [1] "02/ Service"

ABCDEFGHIJ0123456789

Month <dbl>	Year_2017 <dbl>	Year_2018 <dbl>	Year_2019 <dbl>	Year_2020 <dbl>
1	0.000000000	0.000000000	0.0000000000	0.0004712240
2	0.000000000	0.000000000	0.0000000000	0.0000000000
3	0.000000000	0.000000000	0.0000000000	0.0000000000
4	0.000000000	0.000000000	0.0013619386	0.0115220455
5	0.011353057	0.000000000	0.0035337720	0.0090256513
6	0.000000000	0.000404951	0.0044517640	0.0087657342
7	0.000000000	0.000000000	0.0000000000	0.0000000000
8	0.008046968	0.007699284	0.0034231443	0.0399116279
9	0.024131506	0.026709972	0.0127468501	0.0074939855
10	0.000000000	0.010195631	0.0164906173	0.0003294301

## [1] "03/ Dredging"

ABCDEFGHIJ0123456789

Month <dbl>	Year_2017 <dbl>	Year_2018 <dbl>	Year_2019 <dbl>	Year_2020 <dbl>
1	0	0	0	0
2	0	0	0	0
3	0	0	0	0
4	0	0	0	0
5	0	0	0	0
6	0	0	0	0
7	0	0	0	0
8	0	0	0	0
9	0	0	0	0
10	0	0	0	0

## [1] "04/ Sailing"

ABCDEFGHIJ0123456789

Month <dbl>	Year_2017 <dbl>	Year_2018 <dbl>	Year_2019 <dbl>	Year_2020 <dbl>
1	0.0000000000	0.000000000	0.0000000000	0.0000000000
2	0.0000000000	0.000000000	0.0000000000	0.0000000000
3	0.0004446101	0.000000000	0.0009277706	0.0000000000
4	0.0030562652	0.000000000	0.0003244335	0.0000000000
5	0.0000000000	0.010888370	0.0042064583	0.0002823473
6	0.0118438945	0.009765654	0.0056325388	0.0070029486
7	0.0075060271	0.023729605	0.0605832298	0.0472332704
8	0.0140821308	0.040076457	0.0285171956	0.0207925633
9	0.0019264774	0.013611824	0.0028523033	0.0060049282
10	0.0002257163	0.001577263	0.0009767707	0.0028522248

## [1] "05/ Pleasure Craft"

ABCDEFGHIJ0123456789

Month <dbl>	Year_2017 <dbl>	Year_2018 <dbl>	Year_2019 <dbl>	Year_2020 <dbl>
1	0.0000000000	0.0000000000	0.0000000000	0.0000000000
2	0.0000000000	0.0000000000	0.0000000000	0.0000000000
3	0.0000000000	0.0000000000	0.0000000000	0.0000000000
4	0.0000000000	0.0000000000	0.0034588683	0.0000000000
5	0.0005539292	0.0000000000	0.0007852223	0.0002933925
6	0.0009095416	0.0006241493	0.0052630945	0.0026901213
7	0.0013004617	0.0017006482	0.0265895923	0.0771216584
8	0.0124268450	0.0342052300	0.0422201703	0.0452316344
9	0.0049233544	0.0335299089	0.0182630340	0.0062958168
10	0.0047125992	0.0007476281	0.0004506203	0.0000000000

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

ABCDEFGHIJ0123456789

Month <dbl>	Year_2017 <dbl>	Year_2018 <dbl>	Year_2019 <dbl>	Year_2020 <dbl>
1	0	0	0	0.0000000000
2	0	0	0	0.0000000000
3	0	0	0	0.0004111551
4	0	0	0	0.0000000000
5	0	0	0	0.0000000000
6	0	0	0	0.0006092228
7	0	0	0	0.0011962330
8	0	0	0	0.0018803672
9	0	0	0	0.0000000000
10	0	0	0	0.0000000000

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

ABCDEFGHIJ0123456789

Month <dbl>	Year_2017 <dbl>	Year_2018 <dbl>	Year_2019 <dbl>	Year_2020 <dbl>
1	0.0000000000	0.0000000000	0.000000000	0.001055165
2	0.0000000000	0.0000000000	0.001861397	0.000000000
3	0.0006092175	0.0000000000	0.000000000	0.000000000
4	0.0000000000	0.0002536208	0.001693623	0.000000000
5	0.0000000000	0.0000000000	0.000000000	0.000000000
6	0.0037071590	0.0000000000	0.000000000	0.000000000
7	0.0000000000	0.0000000000	0.000000000	0.000000000
8	0.0000000000	0.0000000000	0.000000000	0.000000000
9	0.0000000000	0.0024140252	0.000000000	0.000000000
10	0.0000000000	0.0000000000	0.000000000	0.000000000

## [1] "08/ Passenger"

ABCDEFGHIJ0123456789

Month <dbl>	Year_2017 <dbl>	Year_2018 <dbl>	Year_2019 <dbl>	Year_2020 <dbl>
1	0.000000000	0.002010119	0.0000000000	0.0000000000
2	0.000000000	0.000000000	0.0027903961	0.0000000000
3	0.000000000	0.000000000	0.0049486046	0.0000000000
4	0.005709242	0.002410818	0.0040760273	0.0000000000
5	0.008095394	0.007053404	0.0083085001	0.0000000000
6	0.005747040	0.004193731	0.0029090277	0.0000000000
7	0.003383807	0.003723726	0.0067525535	0.0005980279
8	0.000000000	0.003895138	0.0006405953	0.0000000000
9	0.008122260	0.007999894	0.0060424490	0.0000000000
10	0.004496185	0.004830204	0.0028143324	0.0000000000

## [1] "09/ Cargo"

ABCDEFGHIJ0123456789

Month <dbl>	Year_2017 <dbl>	Year_2018 <dbl>	Year_2019 <dbl>	Year_2020 <dbl>
1	0.007542165	0.016746849	0.01629941	0.020387573
2	0.012772558	0.008447515	0.02430361	0.029679239
3	0.020566700	0.006429928	0.03979192	0.026112631
4	0.030427813	0.018780385	0.03200672	0.021909076
5	0.013862449	0.032392020	0.02380183	0.051416373
6	0.023621235	0.032283715	0.03111937	0.019680507
7	0.032148556	0.035156279	0.02651420	0.049336248
8	0.031591832	0.026084529	0.04001739	0.053156786
9	0.024077899	0.046268512	0.03017823	0.029846795
10	0.033634853	0.048682728	0.02656295	0.007559821

## [1] "10/ Tanker"

ABCDEFGHIJ0123456789

Month <dbl>	Year_2017 <dbl>	Year_2018 <dbl>	Year_2019 <dbl>	Year_2020 <dbl>
1	0.0002556743	0.0055041747	0.005524366	0.0072685780
2	0.0042445207	0.0022426529	0.012136512	0.0069872190
3	0.0071473837	0.0007655839	0.007920144	0.0092640848
4	0.0066863473	0.0092340844	0.009237268	0.0079571829
5	0.0121836154	0.0146116306	0.009457806	0.0112974285
6	0.0164478921	0.0096477619	0.006178414	0.0018946380
7	0.0082090384	0.0080968716	0.015929344	0.0077790045
8	0.0080107966	0.0074495555	0.009746046	0.0073631879
9	0.0130249908	0.0159949766	0.006923805	0.0055807100
10	0.0119757374	0.0102789804	0.006016955	0.0006963732

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

ABCDEFGHIJ0123456789

Month <dbl>	Year_2018 <dbl>	Year_2019 <dbl>	Year_2020 <dbl>
1	0.000000e+00	0.0000000000	0.000000000
2	0.000000e+00	0.0006894894	0.000000000
3	2.519427e-03	0.0000000000	0.000000000
4	0.000000e+00	0.0047328501	0.000000000
5	6.687413e-05	0.0016728132	0.000000000
6	0.000000e+00	0.0032840168	0.000000000
7	1.025072e-03	0.0121746697	0.012156479
8	6.482325e-04	0.0000000000	0.014605069
9	0.000000e+00	0.0001533792	0.001231884
10	3.357351e-03	0.0000000000	0.000000000

## [1] "12/ Unknown"

ABCDEFGHIJ0123456789

Month <dbl>	Year_2017 <dbl>	Year_2018 <dbl>	Year_2019 <dbl>	Year_2020 <dbl>
1	0.000000000	0.000000000	0.000000000	0.0003784484
2	0.000000000	0.000000000	0.002273489	0.0000000000
3	0.000000000	0.000000000	0.004232557	0.0000000000
4	0.000000000	0.004088054	0.014054911	0.0000000000
5	0.000000000	0.048378747	0.014106950	0.0000000000
6	0.002133322	0.003818329	0.009277762	0.0000000000
7	0.000000000	0.019447416	0.018962910	0.0000000000
8	0.006322219	0.003483913	0.000000000	0.0000000000
9	0.002312600	0.003124229	0.002819976	0.0000000000
10	0.002124905	0.006743600	0.016590862	0.0000000000

## [1] "13/ Other"

ABCDEFGHIJ0123456789

Month <dbl>	Year_2017 <dbl>	Year_2018 <dbl>	Year_2019 <dbl>	Year_2020 <dbl>
1	0.000000000	0.000000000	0.000000000	0.0003784484
2	0.000000000	0.000000000	0.002273489	0.0000000000
3	0.000000000	0.000000000	0.004232557	0.0000000000
4	0.000000000	0.004088054	0.014054911	0.0000000000
5	0.000000000	0.048378747	0.014106950	0.0000000000
6	0.002133322	0.003818329	0.009277762	0.0000000000
7	0.000000000	0.019447416	0.018962910	0.0000000000
8	0.006322219	0.003483913	0.000000000	0.0000000000
9	0.002312600	0.003124229	0.002819976	0.0000000000
10	0.002124905	0.006743600	0.016590862	0.0000000000

## [1] "14/ Global traffic"

ABCDEFGHIJ0123456789

Month <dbl>	Year_2017 <dbl>	Year_2018 <dbl>	Year_2019 <dbl>	Year_2020 <dbl>
1	0.2687166	0.4339613	0.6832212	0.60631547
2	0.4728571	0.2515519	0.3762087	0.37180798
3	0.3605270	0.3038175	0.4539812	0.31683343
4	0.9941437	0.4556027	0.5534215	0.81798859
5	0.8400145	1.2536836	0.7162941	1.23425306
6	0.6849686	0.9723381	1.2858306	1.00409443
7	1.1802825	1.2210553	1.0151778	1.50700258
8	1.1902175	0.7077220	1.0271964	1.40266178
9	1.4048092	1.0889510	0.6705606	0.40357611
10	0.8482677	0.6661652	0.7018474	0.21690121

8 Open-notebook

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EU Marine Protected Area: vessel traffic analysis 2017-2020

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

08 May, 2021

1 MPA information

2 Data information

2.1 Metadata

3 Geographical extent

3.1 Coordinates

3.2 MPA area

3.2.1 Topography

3.2.2 Geographical location

4 Shipping density

4.1 Fishing

4.2 Service

4.3 Dredging

4.4 Sailing

4.5 Pleasure Craft

4.6 High Speed craft

4.7 Tug and towing

4.8 Passenger

4.9 Cargo

4.10 Tanker

4.11 Military

4.12 Other

4.13 Unknown

5 Statistics

5.1 Distribution

5.1.1 Annual means

5.1.2 Annual percentages

5.2 Global traffic

6 Hierarchical clustering

6.1 Yearly densities

6.2 Classification by activities

6.3 Maritime activities clusters

6.4 Boxplot

7 All data

8 Open-notebook