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mregions2 offers a streamlined interface to access data from Marine Regions in R for researchers, marine scientists, and geospatial analysts seeking marine geographical information. Marine Regions is part of the LifeWatch project. Its activities focus on two main outputs:

mregions2 allows to retrieve marine geospatial information from the Marine Regions Gazetteer and the Marine Regions Data Products in R.

The Marine Regions Gazetteer is a standard list of marine georeferenced place names.

Gazetteer: a dictionary of geographical names.

https://www.thefreedictionary.com/gazetteer

The entries in the Marine Regions Gazetteer are identified with an unique and persistent identifier, named the ?MRGID (Marine Regions Gazetteer Unique Identifier)

Syntax http://marineregions.org/mrgid/<number>

E.g. https://marineregions.org/mrgid/3293

In addition to the Marine Regions Gazetteer, the Marine Regions Team creates and hosts geographical Data Products, being the most popular one the Marine Regions Maritime Boundaries.

The mregions2 package aims to difference these two domains as clearly as possible, starting with the naming of its functions:

This naming is not trivial, as mregions2 uses different methods to access the Marine Regions Gazetteer than the Marine Regions Data Products: A RESTful API for the Marine Regions Gazetteer, and OGC Web Services to get the Marine Regions Data Products. These are hosted at the Flanders Marine Institute (VLIZ) geoserver:

http://geo.vliz.be/

The data products can be visualized via Web Map Services (WMS) with mrp_view() or downloaded by Web Feature Services (WFS) with mrp_get().

This package is developed for scientific, educational and research purposes. It is not meant to be used for legal, economical (in the sense of exploration of natural resources) or navigational purposes. See the Marine Regions disclaimer.

Wasn’t there a package to read Marine Regions already? mregions?

mregions2 supersedes mregions. The need of mregions2 is further explained in the article: Why mregions and mregions2?

NOTE

The naming mrp_*() instead of mr_() was decided to avoid overlapping with the functions from mregions

Marine Regions Gazetteer

library(mregions2)

# To use the pipe operator `%>%`
library(magrittr) 

# For illustrative purposes
library(sf) 
library(dplyr) 

Search by free text

You can look up for marine places the Marine Regions Gazetteer with a free text search. Some examples:

Find any term with the words ‘North Sea’

gaz_search("North Sea")
#> # A tibble: 25 × 14
#>    MRGID gazetteerSource     placeType latitude longitude preferredGazetteerName
#>    <int> <chr>               <chr>        <dbl>     <dbl> <chr>                 
#>  1  2350 "(1953). Limits of… IHO Sea …     56.4      2.74 North Sea             
#>  2  2399 "ASFA thesaurus"    Bight         51.6      3.02 Southern Bight of the…
#>  3  8542 "Large Marine Ecos… Large Ma…     57.4      2.73 North Sea             
#>  4 17441 "Aphia"             General …     53.1      2.81 Central North Sea     
#>  5 17977 "Aphia"             General …     59        1.8  Northern North Sea    
#>  6 17977 "Aphia"             General …     59        1.8  Northern Part of the …
#>  7 21912 "Spalding, M. D. F… Marine E…     55.5      4.59 North Sea             
#>  8 22165  <NA>               ICES Eco…     NA       NA    North Sea             
#>  9 22253 "Aphia"             General …     51.4      1.99 Southern North Sea    
#> 10 22762 "VLIZ (2020). Inte… Marine R…     54.6      6.78 German part of the No…
#> # ℹ 15 more rows
#> # ℹ 8 more variables: preferredGazetteerNameLang <chr>, status <chr>,
#> #   accepted <int>, minLatitude <dbl>, minLongitude <dbl>, maxLatitude <dbl>,
#> #   maxLongitude <dbl>, precision <dbl>

Search names in different languages (provide ISO 2c code)

gaz_search("Noordzee", language = "nl")
#> # A tibble: 4 × 14
#>   MRGID gazetteerSource    placeType latitude longitude minLatitude minLongitude
#>   <int> <chr>              <chr>        <dbl>     <dbl>       <dbl>        <dbl>
#> 1  2350 (1953). Limits of… IHO Sea …     56.4      2.74        51.0        -4.45
#> 2  2399 ASFA thesaurus     Bight         51.6      3.02        NA          NA   
#> 3 27417 Natura 2000 Sites… Natura 2…     53.3      5.25        NA          NA   
#> 4 50168 Wikipedia          Channel       52.5      4.56        NA          NA   
#> # ℹ 7 more variables: maxLatitude <dbl>, maxLongitude <dbl>, precision <dbl>,
#> #   preferredGazetteerName <chr>, preferredGazetteerNameLang <chr>,
#> #   status <chr>, accepted <int>

Restrict your search to only exact matches

gaz_search("Noordzee", language = "nl", like = FALSE, fuzzy = FALSE)
#> # A tibble: 1 × 14
#>   MRGID gazetteerSource    placeType latitude longitude minLatitude minLongitude
#>   <int> <chr>              <chr>        <dbl>     <dbl>       <dbl>        <dbl>
#> 1  2350 (1953). Limits of… IHO Sea …     56.4      2.74        51.0        -4.45
#> # ℹ 7 more variables: maxLatitude <dbl>, maxLongitude <dbl>, precision <dbl>,
#> #   preferredGazetteerName <chr>, preferredGazetteerNameLang <chr>,
#> #   status <chr>, accepted <int>

Search by MRGID

Pass a ?MRGID to gaz_search() to get only that record. E.g. in the previous example, the Belgian Exclusive Economic Zone has the ?MRGID 3293:

gaz_search(3293)
#> # A tibble: 1 × 14
#>   MRGID gazetteerSource    placeType latitude longitude minLatitude minLongitude
#>   <int> <chr>              <chr>        <dbl>     <dbl>       <dbl>        <dbl>
#> 1  3293 Flanders Marine I… EEZ           51.5      2.72        51.0         2.24
#> # ℹ 7 more variables: maxLatitude <dbl>, maxLongitude <dbl>, precision <dbl>,
#> #   preferredGazetteerName <chr>, preferredGazetteerNameLang <chr>,
#> #   status <chr>, accepted <int>

Search by longitude and latitude

Reverse geocoding is possible with mregions2: pass geographical coordinates in the WGS84 projection will return all records that intersect with the point.

e.g. the coordinates longitude 2.927 - latitude 51.21551 lay on the city of Ostend at the Belgian coast

gaz_search(x = 2.927, y = 51.21551)
#> # A tibble: 55 × 14
#>    MRGID gazetteerSource   placeType latitude longitude minLatitude minLongitude
#>    <int> <chr>             <chr>        <dbl>     <dbl>       <dbl>        <dbl>
#>  1    14 (2001). The Time… Nation        50.5      4.48        49.5         2.55
#>  2    14 (2001). The Time… Nation        50.5      4.48        49.5         2.55
#>  3    14 (2001). The Time… Nation        50.5      4.48        49.5         2.55
#>  4    14 (2001). The Time… Nation        50.5      4.48        49.5         2.55
#>  5    14 (2001). The Time… Nation        50.5      4.48        49.5         2.55
#>  6    14 (2001). The Time… Nation        50.5      4.48        49.5         2.55
#>  7    20 SAIL              Province…     51.0      3.03        50.7         2.55
#>  8    20 SAIL              Province…     51.0      3.03        50.7         2.55
#>  9    20 SAIL              Province…     51.0      3.03        50.7         2.55
#> 10    20 SAIL              Province…     51.0      3.03        50.7         2.55
#> # ℹ 45 more rows
#> # ℹ 7 more variables: maxLatitude <dbl>, maxLongitude <dbl>,
#> #   preferredGazetteerName <chr>, preferredGazetteerNameLang <chr>,
#> #   status <chr>, accepted <int>, precision <dbl>

Passing an sfg geometry object from sf::st_point() is also allowed:

pt <- st_point(c(x = 2.927, y = 51.21551))
pt
#> POINT (2.927 51.21551)

gaz_search(pt)
#> # A tibble: 55 × 14
#>    MRGID gazetteerSource   placeType latitude longitude minLatitude minLongitude
#>    <int> <chr>             <chr>        <dbl>     <dbl>       <dbl>        <dbl>
#>  1    14 (2001). The Time… Nation        50.5      4.48        49.5         2.55
#>  2    14 (2001). The Time… Nation        50.5      4.48        49.5         2.55
#>  3    14 (2001). The Time… Nation        50.5      4.48        49.5         2.55
#>  4    14 (2001). The Time… Nation        50.5      4.48        49.5         2.55
#>  5    14 (2001). The Time… Nation        50.5      4.48        49.5         2.55
#>  6    14 (2001). The Time… Nation        50.5      4.48        49.5         2.55
#>  7    20 SAIL              Province…     51.0      3.03        50.7         2.55
#>  8    20 SAIL              Province…     51.0      3.03        50.7         2.55
#>  9    20 SAIL              Province…     51.0      3.03        50.7         2.55
#> 10    20 SAIL              Province…     51.0      3.03        50.7         2.55
#> # ℹ 45 more rows
#> # ℹ 7 more variables: maxLatitude <dbl>, maxLongitude <dbl>,
#> #   preferredGazetteerName <chr>, preferredGazetteerNameLang <chr>,
#> #   status <chr>, accepted <int>, precision <dbl>

Search by place type

The records of the Marine Regions Gazetteer have place types assigned, either physical such as sea mounts or banks, or administrative like Territorial Sea or Exclusive Economic Zone.

You can find the full list, descriptions and its identifier in the database with gaz_types():

gaz_types()
#> # A tibble: 332 × 3
#>    typeID type                      description                                 
#>     <int> <chr>                     <chr>                                       
#>  1      1 Town                      The lowest administrative unit in Belgium a…
#>  2      2 Arrondissement            The administrative unit in Belgium that lie…
#>  3      3 Department                A high-level administrative unit that is us…
#>  4      4 Province (administrative) A medium-level administrative unit that is …
#>  5      5 Country                   A high-level administrative unit that only …
#>  6      6 Continent                 The highest subdivision of the world. There…
#>  7      7 Region                    A high-level administrative unit that is us…
#>  8      8 Ward                      The lowest administrative unit in the Unite…
#>  9      9 Commune                   The lowest administrative unit in a lot of …
#> 10     10 District                  A medium-level administrative unit that is …
#> # ℹ 322 more rows

You can restrict your search to a certain type ID in the argument typeid

gaz_search("Oostende", typeid = 1)
#> # A tibble: 2 × 14
#>   MRGID gazetteerSource placeType latitude longitude minLatitude minLongitude
#>   <int> <chr>           <chr>        <dbl>     <dbl>       <dbl>        <dbl>
#> 1    65 SAIL            Town          51.2      2.92        51.2         2.84
#> 2    65 SAIL            Town          51.2      2.92        51.2         2.84
#> # ℹ 7 more variables: maxLatitude <dbl>, maxLongitude <dbl>, precision <dbl>,
#> #   preferredGazetteerName <chr>, preferredGazetteerNameLang <chr>,
#> #   status <chr>, accepted <int>

Or you can look up all the records with a certain place type with gaz_search_by_type()

# With text
gaz_search_by_type("Town")
#> # A tibble: 934 × 14
#>    MRGID gazetteerSource placeType latitude longitude preferredGazetteerName
#>    <int> <chr>           <chr>        <dbl>     <dbl> <chr>                 
#>  1    29 SAIL            Town          51.1      3.23 Oostkamp              
#>  2    30 SAIL            Town          51.1      3.34 Beernem               
#>  3    31 SAIL            Town          51.3      3.14 Blankenberge          
#>  4    32 SAIL            Town          51.3      3.32 Damme                 
#>  5    33 SAIL            Town          51.1      3.10 Torhout               
#>  6    34 SAIL            Town          51.2      3.10 Jabbeke               
#>  7    35 SAIL            Town          51.1      3.14 Zedelgem              
#>  8    36 SAIL            Town          51.3      3.13 Zuienkerke            
#>  9    37 SAIL            Town          51.3      3.31 Knokke-Heist          
#> 10    38 SAIL            Town          51.3      3.22 Brugge                
#> # ℹ 924 more rows
#> # ℹ 8 more variables: preferredGazetteerNameLang <chr>, status <chr>,
#> #   accepted <int>, minLatitude <dbl>, minLongitude <dbl>, maxLatitude <dbl>,
#> #   maxLongitude <dbl>, precision <dbl>

# With the place type ID
gaz_search_by_type(1)
#> # A tibble: 934 × 14
#>    MRGID gazetteerSource placeType latitude longitude preferredGazetteerName
#>    <int> <chr>           <chr>        <dbl>     <dbl> <chr>                 
#>  1    29 SAIL            Town          51.1      3.23 Oostkamp              
#>  2    30 SAIL            Town          51.1      3.34 Beernem               
#>  3    31 SAIL            Town          51.3      3.14 Blankenberge          
#>  4    32 SAIL            Town          51.3      3.32 Damme                 
#>  5    33 SAIL            Town          51.1      3.10 Torhout               
#>  6    34 SAIL            Town          51.2      3.10 Jabbeke               
#>  7    35 SAIL            Town          51.1      3.14 Zedelgem              
#>  8    36 SAIL            Town          51.3      3.13 Zuienkerke            
#>  9    37 SAIL            Town          51.3      3.31 Knokke-Heist          
#> 10    38 SAIL            Town          51.3      3.22 Brugge                
#> # ℹ 924 more rows
#> # ℹ 8 more variables: preferredGazetteerNameLang <chr>, status <chr>,
#> #   accepted <int>, minLatitude <dbl>, minLongitude <dbl>, maxLatitude <dbl>,
#> #   maxLongitude <dbl>, precision <dbl>

Search by source document

The entries in the Marine Regions Gazetteer are always based on a source. This is either a document, a web site or any sort of authority.

The list of sources is available with gaz_sources()

# List sources
gaz_sources()
#> # A tibble: 689 × 3
#>    sourceID source                                                     sourceURL
#>       <int> <chr>                                                      <chr>    
#>  1        1 SAIL                                                       http://w…
#>  2        2 ASFA thesaurus                                             http://w…
#>  3        4 Nationaal Instituut voor de Statistiek (NIS) / National S… http://s…
#>  4        5 Oosthoek Times Wereldatlas                                 <NA>     
#>  5        6 Lausch, E. (2000). Atlas van de oceanen: met de dieptekaa… <NA>     
#>  6        7 (2001). The Times comprehensive atlas of the world. 10th … <NA>     
#>  7        8 IHO-IOC GEBCO Gazetteer of Undersea Feature Names (2002-1… http://w…
#>  8        9 BIOMARE                                                    http://w…
#>  9       10 (1953). Limits of oceans and seas. 3rd edition. IHO Speci… <NA>     
#> 10       11 Nomenclature des espaces maritimes/List of maritime areas  <NA>     
#> # ℹ 679 more rows

Search by source is possible with the function gaz_search_by_source(), either with the source as text or passing a sourceID

# With text
gaz_search_by_source("Flanders Marine Institute (VLIZ)")
#> # A tibble: 23 × 13
#>    MRGID gazetteerSource     placeType latitude longitude preferredGazetteerName
#>    <int> <chr>               <chr>        <dbl>     <dbl> <chr>                 
#>  1 62642 Seys, J.; Pint, S.… Sampling…     51.3      3.16 SW-Blankenberge-01    
#>  2 62643 Seys, J.; Pint, S.… Sampling…     51.2      2.96 SW-Bredene-01         
#>  3 62644 Seys, J.; Pint, S.… Sampling…     51.3      3.26 SW-Duinbergen-01      
#>  4 62645 Seys, J.; Pint, S.… Sampling…     51.3      3.00 SW-De Haan-Vosseslag-…
#>  5 62646 Seys, J.; Pint, S.… Sampling…     51.3      3.24 SW-Heist-01           
#>  6 62647 Seys, J.; Pint, S.… Sampling…     51.1      2.62 SW-Koksijde-01        
#>  7 62648 Seys, J.; Pint, S.… Sampling…     51.2      2.81 SW-Middelkerke-01     
#>  8 62649 Seys, J.; Pint, S.… Sampling…     51.2      2.71 SW-Nieuwpoort-01      
#>  9 62650 Seys, J.; Pint, S.… Sampling…     51.1      2.69 SW-Oostduinkerke-01   
#> 10 62651 Seys, J.; Pint, S.… Sampling…     51.2      2.94 SW-Oostende_Oosteroev…
#> # ℹ 13 more rows
#> # ℹ 7 more variables: preferredGazetteerNameLang <chr>, status <chr>,
#> #   accepted <int>, minLatitude <dbl>, minLongitude <dbl>, maxLatitude <dbl>,
#> #   maxLongitude <dbl>

# With source ID
gaz_search_by_source(695) 
#> # A tibble: 23 × 13
#>    MRGID gazetteerSource     placeType latitude longitude preferredGazetteerName
#>    <int> <chr>               <chr>        <dbl>     <dbl> <chr>                 
#>  1 62642 Seys, J.; Pint, S.… Sampling…     51.3      3.16 SW-Blankenberge-01    
#>  2 62643 Seys, J.; Pint, S.… Sampling…     51.2      2.96 SW-Bredene-01         
#>  3 62644 Seys, J.; Pint, S.… Sampling…     51.3      3.26 SW-Duinbergen-01      
#>  4 62645 Seys, J.; Pint, S.… Sampling…     51.3      3.00 SW-De Haan-Vosseslag-…
#>  5 62646 Seys, J.; Pint, S.… Sampling…     51.3      3.24 SW-Heist-01           
#>  6 62647 Seys, J.; Pint, S.… Sampling…     51.1      2.62 SW-Koksijde-01        
#>  7 62648 Seys, J.; Pint, S.… Sampling…     51.2      2.81 SW-Middelkerke-01     
#>  8 62649 Seys, J.; Pint, S.… Sampling…     51.2      2.71 SW-Nieuwpoort-01      
#>  9 62650 Seys, J.; Pint, S.… Sampling…     51.1      2.69 SW-Oostduinkerke-01   
#> 10 62651 Seys, J.; Pint, S.… Sampling…     51.2      2.94 SW-Oostende_Oosteroev…
#> # ℹ 13 more rows
#> # ℹ 7 more variables: preferredGazetteerNameLang <chr>, status <chr>,
#> #   accepted <int>, minLatitude <dbl>, minLongitude <dbl>, maxLatitude <dbl>,
#> #   maxLongitude <dbl>

Search geometries: Geocoding

Geocoding marine places is possible with mregions2. As a bare minimum, the entries of the Marine Regions Gazetteer should always have a the centroid of the feature, in the fields latitude and longitude. The bounding box of the feature may also be available via the fields minLatitude, maxLatitude, minLongitude and maxLongitude.

Moreover, many of the entries of the Marine Regions Gazetteer have actual geometries associated. These are typically Polygons or Linestrings. To avoid overloading the server, the geometries are not returned by default with gaz_search(). Adding the geometries is possible with gaz_geometry(): passing the result of gaz_search() will turn the data frame into a sf::sf object with geometry in the field the_geom, of class sf::sfc.

gaz_search(3293) %>% gaz_geometry()
#> Simple feature collection with 1 feature and 14 fields
#> Geometry type: MULTIPOLYGON
#> Dimension:     XY
#> Bounding box:  xmin: 2.238333 ymin: 51.03976 xmax: 4.402039 ymax: 51.87611
#> Geodetic CRS:  WGS 84
#> # A tibble: 1 × 15
#>   MRGID gazetteerSource    placeType latitude longitude minLatitude minLongitude
#>   <int> <chr>              <chr>        <dbl>     <dbl>       <dbl>        <dbl>
#> 1  3293 Flanders Marine I… EEZ           51.5      2.72        51.0         2.24
#> # ℹ 8 more variables: maxLatitude <dbl>, maxLongitude <dbl>, precision <dbl>,
#> #   preferredGazetteerName <chr>, preferredGazetteerNameLang <chr>,
#> #   status <chr>, accepted <int>, the_geom <MULTIPOLYGON [°]>

This is possible cause the result of gaz_search is a data frame including the class mr_df, unique of the mregions2 R package. The geometry function has a S3 method defined for this class: gaz_geometry.mr_df().

You can also use the argument with_geometry as gaz_search(3293, with_geometry = TRUE) to load the geometry directly.

In addition, fetching only the geometries is possible using an ?MRGID on gaz_geometry()

# By MRGID
gaz_geometry(3293)
#> Geometry set for 1 feature 
#> Geometry type: MULTIPOLYGON
#> Dimension:     XY
#> Bounding box:  xmin: 2.238333 ymin: 51.03976 xmax: 4.402039 ymax: 51.87611
#> Geodetic CRS:  WGS 84
#> MULTIPOLYGON (((4.242049 51.35397, 4.230735 51....

By default, this is a simple feature geometry list column, an object of class sf::sfc. But other formats are possible:

As Well-Known Text (WKT):

gaz_geometry(3293, format = "wkt")
#> [1] "MULTIPOLYGON (((4.242049 51.35397, 4.230735 51.35825, 4.226746 51.35976, 4.222067 51.36451, 4.219928 51.36832, 4.218261 51.37221, 4.217578 51.37389, 4.23069 51.37436, 4.242811 51.3748, 4.242808 51.3738, 4.242861 51.37125, 4.243166 51.37118, 4.243472 51.37104, 4.243707 51.37068, 4.243893 51.37009, 4.244108 51.36954, 4.244319 51.36908, 4.244552 51.36867, 4.244764 51.36817, 4.244982 51.36747, 4.245172 51.36666, 4.245409 51.36617, 4.245692 51.36598, 4.245923 51.36579, 4.24611 51.36545, 4.246359 51.36502, 4.246679 51.36452, 4.247084 51.36406, 4.247391 51.36374, 4.24766 51.36358, 4.247939 51.36349, 4.24815 51.36336, 4.248306 51.36319, 4.248528 51.36305, 4.248844 51.36297, 4.249515 51.36255, 4.249644 51.36236, 4.249866 51.36223, 4.250156 51.36212, 4.250399 51.36191, 4.250599 51.36155, 4.250832 51.36113, 4.25105 51.36072, 4.25122 51.36037, 4.251204 51.36006, 4.251056 51.35971, 4.251035 51.3593, 4.251222 51.35887, 4.251533 51.35844, 4.251972 51.35813, 4.252378 51.35795, 4.252641 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As a rdflib::rdf object:

gaz_geometry(3293, format = "rdf")
#> Total of 4 triples, stored in hashes
#> -------------------------------
#> @base <localhost://> .
#> @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
#> 
#> <http://marineregions.org/mrgid/3293>
#>     <http://marineregions.org/ns/ontology#hasGeometry> <http://marineregions.org/mrgid/3293/geometries?source=79&attributeValue=3293> .
#> 
#> <http://marineregions.org/mrgid/3293/geometries?source=79&attributeValue=3293>
#>     <http://www.opengis.net/ont/geosparql#asWKT> "<http://www.opengis.net/def/crs/OGC/1.3/CRS84> MULTIPOLYGON (((4.24204865 51.35396728, 4.23073486 51.35824973, 4.22674608 51.3597591, 4.22206664 51.36451072, 4.21992833 51.36832287, 4.21826057 51.3722099, 4.21757767 51.37388563, 4.23069032 51.37435976, 4.24281066 51.37479669, 4.24280834 51.37379777, 4.24286056 51.37125123, 4.24316621 51.37117624, 4.24347174 51.37103796, 4.24370706 51.37068141, 4.24389255 51.37008905, 4.24410796 51.36954224, 4.24431884 51.36908472, 4.24455225 51.36867034, 4.24476385 51.36816514, 4.244982 51.36747491, 4.24517226 51.36665845, 4.24540901 51.36617172, 4.24569237 51.36597717, 4.24592257 51.36578608, 4.2461102 51.36545002, 4.24635875 51.36502087, 4.24667907 51.36452293, 4.24708426 51.3640573, 4.24739075 51.36374235, 4.24766016 51.36358285, 4.24793911 51.36349225, 4.24815035 51.36336243, 4.24830627 51.36318815, 4.24852848 51.36304903, 4.24884415 51.36296606, 4.24951494 51.36254585, 4.24964416 51.36235881, 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2.39027778 51.26916667, 2.37552528 51.29718832, 2.35365697 51.33872611, 2.30586236 51.42950965, 2.23833333 51.55777778, 2.25333333 51.61305556, 2.30586236 51.65721317, 2.48166667 51.805, 2.53933306 51.87611444, 3.08138889 51.55166667, 3.21222222 51.48472222, 3.29638889 51.45, 3.31192855 51.43093201, 3.33615505 51.40120481, 3.35388889 51.37944444, 3.36458333 51.37361111, 3.37040317 51.36696434, 3.36945856 51.366822)))"^^<http://www.opengis.net/ont/geosparql#wktLiteral> ;
#>     <http://www.w3.org/ns/prov#hadPrimarySource> <http://www.marineregions.org> .

As a sf::sf object:

gaz_geometry(3293, format = "sf")
#> Simple feature collection with 1 feature and 1 field
#> Geometry type: MULTIPOLYGON
#> Dimension:     XY
#> Bounding box:  xmin: 2.238333 ymin: 51.03976 xmax: 4.402039 ymax: 51.87611
#> Geodetic CRS:  WGS 84
#> # A tibble: 1 × 2
#>   MRGID                                                                 the_geom
#> * <int>                                                       <MULTIPOLYGON [°]>
#> 1  3293 (((4.242049 51.35397, 4.230735 51.35825, 4.226746 51.35976, 4.222067 51…

Learn more about using the mregions2 to access the Marine Regions Gazetteer as RDF article.

Search by relations

The Marine Regions Gazetteer is organized hierarchically: All the records got relations with each other. You can either pass the result of gaz_search() to gaz_relations() or an ?MRGID:

# With gaz_search()
gaz_search(3293) %>% gaz_relations()
#> # A tibble: 37 × 14
#>    MRGID gazetteerSource   placeType latitude longitude minLatitude minLongitude
#>    <int> <chr>             <chr>        <dbl>     <dbl>       <dbl>        <dbl>
#>  1  3293 Flanders Marine … EEZ           51.5      2.72        51.0         2.24
#>  2  2419 ASFA thesaurus    Sandbank…     51.5      2.58        NA          NA   
#>  3  2420 ASFA thesaurus    Sandbank…     51.5      2.88        NA          NA   
#>  4  2421 ASFA thesaurus    Sandbank…     51.3      2.64        NA          NA   
#>  5    14 (2001). The Time… Nation        50.5      4.48        49.5         2.55
#>  6  2350 (1953). Limits o… IHO Sea …     56.4      2.74        51.0        -4.45
#>  7  4675 <NA>              Sandbank…     51.3      2.98        NA          NA   
#>  8  2550 ASFA thesaurus    Coast         51.2      2.91        51.1         2.54
#>  9 17401 Aphia             Wreck         51.4      2.32        NA          NA   
#> 10 17409 Aphia             Wreck         51.1      2.33        NA          NA   
#> # ℹ 27 more rows
#> # ℹ 7 more variables: maxLatitude <dbl>, maxLongitude <dbl>, precision <dbl>,
#> #   preferredGazetteerName <chr>, preferredGazetteerNameLang <chr>,
#> #   status <chr>, accepted <int>

# With MRGID
gaz_relations(3293)
#> # A tibble: 37 × 14
#>    MRGID gazetteerSource   placeType latitude longitude minLatitude minLongitude
#>    <int> <chr>             <chr>        <dbl>     <dbl>       <dbl>        <dbl>
#>  1  3293 Flanders Marine … EEZ           51.5      2.72        51.0         2.24
#>  2  2419 ASFA thesaurus    Sandbank…     51.5      2.58        NA          NA   
#>  3  2420 ASFA thesaurus    Sandbank…     51.5      2.88        NA          NA   
#>  4  2421 ASFA thesaurus    Sandbank…     51.3      2.64        NA          NA   
#>  5    14 (2001). The Time… Nation        50.5      4.48        49.5         2.55
#>  6  2350 (1953). Limits o… IHO Sea …     56.4      2.74        51.0        -4.45
#>  7  4675 <NA>              Sandbank…     51.3      2.98        NA          NA   
#>  8  2550 ASFA thesaurus    Coast         51.2      2.91        51.1         2.54
#>  9 17401 Aphia             Wreck         51.4      2.32        NA          NA   
#> 10 17409 Aphia             Wreck         51.1      2.33        NA          NA   
#> # ℹ 27 more rows
#> # ℹ 7 more variables: maxLatitude <dbl>, maxLongitude <dbl>, precision <dbl>,
#> #   preferredGazetteerName <chr>, preferredGazetteerNameLang <chr>,
#> #   status <chr>, accepted <int>

The relations must be one of c("partof", "partlypartof", "adjacentto", "similarto", "administrativepartof", "influencedby") or "all" to get all related records (default). You can also decide if you want records that are upper or lower on the hierarchy of the records, or both (default)

For instance, the Belgian Exclusive Economic Zone with ?MRGID 3293 is part of the North Sea and part of Belgium.

gaz_relations(3293, direction = "upper", type = "partof")
#> # A tibble: 2 × 14
#>   MRGID gazetteerSource    placeType latitude longitude minLatitude minLongitude
#>   <int> <chr>              <chr>        <dbl>     <dbl>       <dbl>        <dbl>
#> 1    14 (2001). The Times… Nation        50.5      4.48        49.5         2.55
#> 2  2350 (1953). Limits of… IHO Sea …     56.4      2.74        51.0        -4.45
#> # ℹ 7 more variables: maxLatitude <dbl>, maxLongitude <dbl>, precision <dbl>,
#> #   preferredGazetteerName <chr>, preferredGazetteerNameLang <chr>,
#> #   status <chr>, accepted <int>

RESTful services

There is a set of functions in mregions2 named as gaz_rest that read the Marine Regions Gazetteer REST API via HTTP requests. These are closer to the definition of the web services. All the gazetteer functions shown above, such as gaz_search() or gaz_relations(), make use of this set of functions.

Main function REST function REST web service
gaz_search() gaz_rest_records_by_name() getGazetteerRecordsByName
gaz_search() gaz_rest_records_by_names() getGazetteerRecordsByNames
gaz_search() gaz_rest_record_by_mrgid() getGazetteerRecordByMRGID
gaz_search() gaz_rest_records_by_lat_long() getGazetteerRecordsByLatLong
gaz_search_by_type() gaz_rest_records_by_type() getGazetteerRecordsByType
gaz_search_by_source() gaz_rest_records_by_source() getGazetteerRecordsBySource
gaz_search_by_source() gaz_rest_source_by_sourceid() getGazetteerSourceBySourceID
gaz_relations() gaz_rest_relations_by_mrgid() getGazetteerRelationsByMRGID
gaz_types() gaz_rest_types() getGazetteerTypes
gaz_sources() gaz_rest_sources() getGazetteerSources
gaz_geometry() gaz_rest_geometries() getGazetteerGeometries
NA gaz_rest_names_by_mrgid() getGazetteerNamesByMRGID
NA gaz_rest_wmses() getGazetteerWMSes
NA NA getFeed

Linked Open Data

You can get a gazetteer item or their geometries as Linked Open Data, in the form of an object of class rdflib::rdf:

gaz_search(3293, rdf = TRUE)
#> Total of 99 triples, stored in hashes
#> -------------------------------
#> @base <localhost://> .
#> @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
#> 
#> <http://marineregions.org/mrgid/14>
#>     a <http://marineregions.org/ns/ontology#MRGeoObject>, <http://marineregions.org/ns/placetypes#Nation> ;
#>     <http://www.w3.org/2004/02/skos/core#prefLabel> "Belgium"@en .
#> 
#> <http://marineregions.org/mrgid/17401>
#>     a <http://marineregions.org/ns/ontology#MRGeoObject>, <http://marineregions.org/ns/placetypes#Wreck> ;
#>     <http://www.w3.org/2004/02/skos/core#prefLabel> "Birkenfels"@en .
#> 
#> ... with 89 more triples

gaz_geometry(3293, format = "rdf")
#> Total of 4 triples, stored in hashes
#> -------------------------------
#> @base <localhost://> .
#> @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
#> 
#> <http://marineregions.org/mrgid/3293>
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#>     <http://www.w3.org/ns/prov#hadPrimarySource> <http://www.marineregions.org> .

See the Marine Regions Gazetteer as RDF article for more information.

Marine Regions Data Products

The main function to load a Marine Regions Data Product into R is mrp_get(). To select a data product, you have to pass the layer argument.

# See the full list of data products
mrp_list
#> # A tibble: 21 × 8
#>    title                   namespace layer license citation doi   imis  abstract
#>    <chr>                   <chr>     <chr> <chr>   <chr>    <chr> <chr> <chr>   
#>  1 Exclusive Economic Zon… MarineRe… eez   Creati… "Flande… http… http… "Versio…
#>  2 Maritime Boundaries (v… MarineRe… eez_… Creati… "Flande… http… http… "Versio…
#>  3 Territorial Seas (12 N… MarineRe… eez_… Creati… "Flande… http… http… "Versio…
#>  4 Contiguous Zones (24 N… MarineRe… eez_… Creati… "Flande… http… http… "Versio…
#>  5 Internal Waters (v3, w… MarineRe… eez_… Creati… "Flande… http… http… "Versio…
#>  6 Archipelagic Waters (v… MarineRe… eez_… Creati… "Flande… http… http… "Versio…
#>  7 High Seas (v1, world, … MarineRe… high… Creati… "Flande… http… http… "High S…
#>  8 Extended Continental S… MarineRe… ecs   Creati… "Flande… http… http… "This d…
#>  9 Extended Continental S… MarineRe… ecs_… Creati… "Flande… http… http… "This d…
#> 10 IHO Sea Areas (v3)      MarineRe… iho   Creati… "Flande… http… http… "World …
#> # ℹ 11 more rows

# Get the Extended Continental Shelves
mrp_get("ecs")
#> Simple feature collection with 134 features and 63 fields
#> Geometry type: MULTIPOLYGON
#> Dimension:     XY
#> Bounding box:  xmin: -180 ymin: -64.03206 xmax: 180 ymax: 90
#> Geodetic CRS:  WGS 84
#> # A tibble: 134 × 64
#>    geoname pol_type territory1 mrgid_ter1 iso_ter1 un_ter1 sovereign1 mrgid_sov1
#>    <chr>   <chr>    <chr>      <chr>      <chr>    <chr>   <chr>           <int>
#>  1 Overla… ECS Ove… New Zeala… 2227       NZL      554     New Zeala…       2227
#>  2 Overla… ECS Ove… Ireland    2114       IRL      372     Ireland          2114
#>  3 Guyane… ECS CLC… Guyana     2124       GUY      328     Guyana           2124
#>  4 Maurit… ECS CLC… Republic … 8614       MUS      480     Republic …       8614
#>  5 Danish… ECS CLC… Faeroe     3297       FRO      234     Denmark          2157
#>  6 Overla… ECS Ove… Barbados   8649       BRB      52      Barbados         8649
#>  7 Brazil… ECS CLC… Brazil     2143       BRA      76      Brazil           2143
#>  8 Overla… ECS Ove… New Zeala… 2227       NZL      554     New Zeala…       2227
#>  9 Japane… ECS CLC… Japan      2121       JPN      392     Japan            2121
#> 10 Overla… ECS Ove… Japan      2121       JPN      392     Japan            2121
#> # ℹ 124 more rows
#> # ℹ 56 more variables: iso_sov1 <chr>, un_sov1 <chr>, territory2 <chr>,
#> #   mrgid_ter2 <chr>, iso_ter2 <chr>, un_ter2 <chr>, sovereign2 <chr>,
#> #   mrgid_sov2 <int>, iso_sov2 <chr>, un_sov2 <chr>, territory3 <chr>,
#> #   mrgid_ter3 <chr>, iso_ter3 <chr>, un_ter3 <chr>, sovereign3 <chr>,
#> #   mrgid_sov3 <int>, iso_sov3 <chr>, un_sov3 <chr>, territory4 <chr>,
#> #   mrgid_ter4 <chr>, iso_ter4 <chr>, un_ter4 <chr>, sovereign4 <chr>, …

However, this is an expensive request that may take some time to complete. mregions2 aims to tackle this with three different strategies:

WMS viewer

Instead of downloading the full product directly, it is a better approach to first have a quick look. mrp_view() renders an interactive visualization:

mrp_view("ecs")

It returns a leaflet::leaflet interactive map with the data product requested added via Web Map Services (WMS).

Note leaflet::leaflet and leaflet.extras2::leaflet.extras2 are required by mrp_view() but listed only as “Suggests”. Install these packages to use mrp_view().

Caching

If you request again a layer that you requested before, you will see a message:

# One more time! Get the Extended Continental Shelves
ecs <- mrp_get("ecs")
#> Cache is fresh. Reading: '/tmp/RtmpfdLvPI/ecs-127feb7d/ecs.shp'
#> (Last Modified: 2024-08-29 13:43:15.216636)

mrp_get() performs a WFS request to get the layer as a zipped Shapefile and writes the response to disk. This saves both bandwith and memory. After downloading, the file is unzipped and read with sf::st_read().

By default, the caching directory is a temporal directory base::tempdir(). To override this behaviour, you can pass a directory to the path argument:

ecs <- mrp_get("ecs", path = "path/to/data")

Or you can set a default directory with options("mregions2.download_path"):

options("mregions2.download_path" = "path/to/data")
ecs <- mrp_get("ecs")

The cache is considered fresh during one month. After that, the requests will be performed again. The Marine Regions products are typically updated every 2 years, so it is unlikely you will be looking at an old product. In case of doubt you can just delete the layers downloaded in the cache path.

OGC and CQL filtering

In some cases, you may be interested in retrieving only a certain amount of records or filtering out some features. You could download the product with mrp_get() and then apply a filter with R base or with the Tidyverse (tidyverse::tidyverse). But getting the full product is slow:

ecs <- mrp_get("ecs") %>% filter(sovereign1 == "Portugal")

Instead, you can write a filter that is applied on the server side:

ecs <- mrp_get("ecs", cql_filter = "sovereign1 = 'Portugal'")

This filter is written in Contextual Query Language (CQL). This is a relatively simple syntax close to SQL.

Writing these filters can be challenging without knowing in advance the names of the columns in a data product, or the unique values that these columns have. If you have to retrieve the full product to get to know the columns and their values then, well, the filter misses a bit its point.

mregions2 has two helpers that help on this mission: mrp_colnames() gets a data frame with the columns and data type of a data product. mrp_col_unique() (or mrp_col_distinct(), they are synonyms) returns the unique values of a column in a data product.

# Columns of the Extended Continental Shelves data product
mrp_colnames("ecs")
#> # A tibble: 63 × 3
#>    layer colname    type  
#>  * <chr> <chr>      <chr> 
#>  1 ecs   geoname    string
#>  2 ecs   pol_type   string
#>  3 ecs   territory1 string
#>  4 ecs   mrgid_ter1 string
#>  5 ecs   iso_ter1   string
#>  6 ecs   un_ter1    string
#>  7 ecs   sovereign1 string
#>  8 ecs   mrgid_sov1 int   
#>  9 ecs   iso_sov1   string
#> 10 ecs   un_sov1    string
#> # ℹ 53 more rows

# Unique values of the column pol_type
mrp_col_unique("ecs", "pol_type")
#> [1] "ECS CLCS Recommendation"       "ECS CLCS Submission"          
#> [3] "ECS DOALOS Deposit"            "ECS Joint CLCS Recommendation"
#> [5] "ECS Joint CLCS Submission"     "ECS Joint DOALOS Deposit"     
#> [7] "ECS Overlapping claim"

# Get all the Overlapping claims
mrp_get("ecs", cql_filter = "pol_type = 'ECS Overlapping claim'")
#> Simple feature collection with 55 features and 63 fields
#> Geometry type: MULTIPOLYGON
#> Dimension:     XY
#> Bounding box:  xmin: -180 ymin: -57.0112 xmax: 180 ymax: 90
#> Geodetic CRS:  WGS 84
#> # A tibble: 55 × 64
#>    geoname pol_type territory1 mrgid_ter1 iso_ter1 un_ter1 sovereign1 mrgid_sov1
#>    <chr>   <chr>    <chr>      <chr>      <chr>    <chr>   <chr>           <int>
#>  1 Overla… ECS Ove… New Zeala… 2227       NZL      554     New Zeala…       2227
#>  2 Overla… ECS Ove… Ireland    2114       IRL      372     Ireland          2114
#>  3 Overla… ECS Ove… Barbados   8649       BRB      52      Barbados         8649
#>  4 Overla… ECS Ove… New Zeala… 2227       NZL      554     New Zeala…       2227
#>  5 Overla… ECS Ove… Japan      2121       JPN      392     Japan            2121
#>  6 Overla… ECS Ove… Fiji       2108       FJI      242     Fiji             2108
#>  7 Overla… ECS Ove… Barbados   8649       BRB      52      Barbados         8649
#>  8 Overla… ECS Ove… Mozambique 2220       MOZ      508     Mozambique       2220
#>  9 Overla… ECS Ove… Fiji       2108       FJI      242     Fiji             2108
#> 10 Overla… ECS Ove… Madagascar 7963       MDG      450     Madagascar       7963
#> # ℹ 45 more rows
#> # ℹ 56 more variables: iso_sov1 <chr>, un_sov1 <chr>, territory2 <chr>,
#> #   mrgid_ter2 <chr>, iso_ter2 <chr>, un_ter2 <chr>, sovereign2 <chr>,
#> #   mrgid_sov2 <int>, iso_sov2 <chr>, un_sov2 <chr>, territory3 <chr>,
#> #   mrgid_ter3 <chr>, iso_ter3 <chr>, un_ter3 <chr>, sovereign3 <chr>,
#> #   mrgid_sov3 <int>, iso_sov3 <chr>, un_sov3 <chr>, territory4 <chr>,
#> #   mrgid_ter4 <chr>, iso_ter4 <chr>, un_ter4 <chr>, sovereign4 <chr>, …

An exhaustive ontology defining the attributes of each data product is available in the data frame mrp_ontology included in this package, or read the article online for further reasoning.

mrp_ontology
#> # A tibble: 374 × 4
#>    layer colname    type   definition                                           
#>    <chr> <chr>      <chr>  <chr>                                                
#>  1 eez   mrgid      int    Marine Regions Geographic Identifier of the feature.…
#>  2 eez   geoname    string Name of the feature.                                 
#>  3 eez   mrgid_ter1 int    Marine Regions Geographic Identifier of the territor…
#>  4 eez   pol_type   string Basis of creation or legal status of feature. One of…
#>  5 eez   mrgid_sov1 int    Marine Regions Geographic Identifier of the sovereig…
#>  6 eez   territory1 string Specific land area which directly relates to the fea…
#>  7 eez   iso_ter1   string ISO 3 code of the territory feature.                 
#>  8 eez   sovereign1 string State that claims jurisdiction over the territory.   
#>  9 eez   mrgid_ter2 int    Marine Regions Geographic Identifier of the territor…
#> 10 eez   mrgid_sov2 int    Marine Regions Geographic Identifier of the sovereig…
#> # ℹ 364 more rows

There are many types of filter allowed via standard OGC or CQL filters. mrp_get() and mrp_view() use OGC WFS and WMS respectively. You can pass filter to both of them using the same syntax. You can also limit the number of features requested with the count parameter.

# Get only one feature
mrp_get("ecs", count = 1)
#> Simple feature collection with 1 feature and 63 fields
#> Geometry type: POLYGON
#> Dimension:     XY
#> Bounding box:  xmin: 177.0364 ymin: -28.0213 xmax: 177.5697 ymax: -26.12738
#> Geodetic CRS:  WGS 84
#> # A tibble: 1 × 64
#>   geoname  pol_type territory1 mrgid_ter1 iso_ter1 un_ter1 sovereign1 mrgid_sov1
#>   <chr>    <chr>    <chr>      <chr>      <chr>    <chr>   <chr>           <int>
#> 1 Overlap… ECS Ove… New Zeala… 2227       NZL      554     New Zeala…       2227
#> # ℹ 56 more variables: iso_sov1 <chr>, un_sov1 <chr>, territory2 <chr>,
#> #   mrgid_ter2 <chr>, iso_ter2 <chr>, un_ter2 <chr>, sovereign2 <chr>,
#> #   mrgid_sov2 <int>, iso_sov2 <chr>, un_sov2 <chr>, territory3 <chr>,
#> #   mrgid_ter3 <chr>, iso_ter3 <chr>, un_ter3 <chr>, sovereign3 <chr>,
#> #   mrgid_sov3 <int>, iso_sov3 <chr>, un_sov3 <chr>, territory4 <chr>,
#> #   mrgid_ter4 <chr>, iso_ter4 <chr>, un_ter4 <chr>, sovereign4 <chr>,
#> #   mrgid_sov4 <int>, iso_sov4 <chr>, un_sov4 <chr>, territory5 <chr>, …

mrp_view() uses leaflet.extras2::addWMS(), which enables passing the filters together with the base URL in the argument baseURL.

# View all Joint submissions, recommendations of deposit to DOALOS with an area larger than 1M square kilometers
verbose <- "
  pol_type IN (
    'ECS Joint CLCS Recommendation', 
    'ECS Joint CLCS Submission', 
    'ECS Joint DOALOS Deposit'
  ) 
  AND area_km2 > 1000000
"
mrp_view("ecs", cql_filter = verbose)

You can also apply a standard OGC filter specification. These are however more verbose:

# View the Extended Continental Shelf of Portugal
verbose <- "
  <Filter>
    <PropertyIsEqualTo>
        <PropertyName>sovereign1</PropertyName>
        <Literal>Portugal</Literal>
    </PropertyIsEqualTo>
  </Filter>
"
mrp_view("ecs", filter = verbose)

Note that all the data products of Marine Regions are served via the VLIZ geoserver. Geoserver implements a more powerful extension of CQL called ECQL (Extended CQL). which allows expressing the full range of filters that OGC Filter 1.1 can encode. ECQL is accepted in many places in GeoServer.

Whenever the documentation refers to CQL, ECQL syntax can be used as well.

I recommend the vignette("ecql_filtering", package = "emodnet.wfs") of the emodnet.wfs R package to know more. The principles explained there are useful also for mregions2.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.