--- title: "Accessing and mapping EMODnet data" output: rmarkdown::html_vignette df_print: "kable" vignette: > %\VignetteIndexEntry{API details} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} --- ## Introduction The package was designed to make EMODnet vector data layers easily accessible in R. The package allows users to query information on and download data from all available [EMODnet Web Feature Service (WFS) endpoints](https://emodnet.ec.europa.eu/geonetwork/srv/eng/catalog.search) directly into their R working environment. Data are managed as [`sf` objects](https://r-spatial.github.io/sf/) which are currently the state-of-the-art in handling of vector spatial data in R. The package also allows user to specify the coordinate reference system of imported data. ## Installation You can install the development version of emodnet.wfs from GitHub with: ``` r pak::pak("EMODnet/emodnet.wfs") ``` ## Explore the EMODnet WFS services with R For this tutorial we will make use of the [`sf`](https://r-spatial.github.io/sf/) and [`mapview`](https://r-spatial.github.io/mapview/) packages. The simple features `sf` package is a well known standard for dealing with geospatial vector data. To visualize geometries, `mapview` will create quick interactive maps. Run this line to install these packages: ``` r install.packages(c("sf", "mapview")) ``` EMODnet is organized into [seven thematic lots](https://emodnet.ec.europa.eu/en/emodnet-themes): Bathymetry, Geology, Seabed Habitats, Chemistry, Biology, Physics, and Human Activities, each focusing on a specific aspect of marine data. With the emodnet.wfs package, we can explore and combine the data served by the EMODnet thematic lots through [OGC Web Feature Services](https://en.wikipedia.org/wiki/Web_Feature_Service) or WFS. Imagine we are interested in seabed substrates. The first step is to choose what EMODnet thematic lot can provide with these data. For that, we can check the services available with the `emodnet_wfs()` function. ``` r library(emodnet.wfs) library(mapview) library(sf) services <- emodnet_wfs() class(services) #> [1] "tbl_df" "tbl" "data.frame" names(services) #> [1] "emodnet_thematic_lot" "service_name" "service_url" services[, c("emodnet_thematic_lot", "service_name")] #> # A tibble: 17 × 2 #> emodnet_thematic_lot service_name #> #> 1 EMODnet Bathymetry bathymetry #> 2 EMODnet Biology biology #> 3 EMODnet Biology biology_occurrence_data #> 4 EMODnet Chemistry chemistry_cdi_data_discovery_and_access_service #> 5 EMODnet Chemistry chemistry_cdi_distribution_observations_per_category_and_region #> 6 EMODnet Chemistry chemistry_contaminants #> 7 EMODnet Chemistry chemistry_marine_litter #> 8 EMODnet Geology geology_coastal_behavior #> 9 EMODnet Geology geology_events_and_probabilities #> 10 EMODnet Geology geology_marine_minerals #> 11 EMODnet Geology geology_sea_floor_bedrock #> 12 EMODnet Geology geology_seabed_substrate_maps #> 13 EMODnet Geology geology_submerged_landscapes #> 14 EMODnet Human Activities human_activities #> 15 EMODnet Physics physics #> 16 EMODnet Seabed Habitats seabed_habitats_general_datasets_and_products #> 17 EMODnet Seabed Habitats seabed_habitats_individual_habitat_map_and_model_datasets ``` EMODnet data covers several disciplines organized in 7 thematic lots: bathymetry, biology, chemistry, geology, human activities, physics, seabed habitats. Some thematic lots organize their data in more than one data source or service. The column `service_name` shows services available, while `service_url` has the corresponding base url to perform a WFS request. The Seabed portal should have the data we are looking for. A WFS client can be created by passing the corresponding `service_name` to the function `emodnet_init_wfs_client()`. The layers available to this WFS client are consulted with `emodnet_get_wfs_info()`. ``` r seabed_wfs_client <- emodnet_init_wfs_client(service = "seabed_habitats_general_datasets_and_products") #> ✔ WFS client created successfully #> ℹ Service: "https://ows.emodnet-seabedhabitats.eu/geoserver/emodnet_open/wfs" #> ℹ Version: "2.0.0" emodnet_get_wfs_info(wfs = seabed_wfs_client) #> # A tibble: 72 × 9 #> # Rowwise: #> data_source service_name service_url layer_name title abstract class format layer_namespace #> #> 1 emodnet_wfs seabed_habitats_gen… https://ow… art17_hab… 2013… "Gridde… WFSF… sf emodnet_open #> 2 emodnet_wfs seabed_habitats_gen… https://ow… art17_hab… 2013… "Gridde… WFSF… sf emodnet_open #> 3 emodnet_wfs seabed_habitats_gen… https://ow… art17_hab… 2013… "Gridde… WFSF… sf emodnet_open #> 4 emodnet_wfs seabed_habitats_gen… https://ow… art17_hab… 2013… "Gridde… WFSF… sf emodnet_open #> 5 emodnet_wfs seabed_habitats_gen… https://ow… art17_hab… 2013… "Gridde… WFSF… sf emodnet_open #> 6 emodnet_wfs seabed_habitats_gen… https://ow… art17_hab… 2013… "Gridde… WFSF… sf emodnet_open #> 7 emodnet_wfs seabed_habitats_gen… https://ow… art17_hab… 2013… "Gridde… WFSF… sf emodnet_open #> 8 emodnet_wfs seabed_habitats_gen… https://ow… art17_hab… 2013… "Gridde… WFSF… sf emodnet_open #> 9 emodnet_wfs seabed_habitats_gen… https://ow… carib_eus… 2023… "Output… WFSF… sf emodnet_open #> 10 emodnet_wfs seabed_habitats_gen… https://ow… biogenic_… Biog… "This l… WFSF… sf emodnet_open #> # ℹ 62 more rows ``` Each layer is explained in the `abstract` column. We can see several layers with the information provided by the EU member states for the [Habitats Directive 92/43/EEC reporting](https://www.eea.europa.eu/data-and-maps/data/article-17-database-habitats-directive-92-43-eec-2). We will select the layers about coastal lagoons, mudflats and sandbanks with their respective `layer_name`. ``` r habitats_directive_layer_names <- c("art17_hab_1110", "art17_hab_1140", "art17_hab_1150") emodnet_get_layer_info( wfs = seabed_wfs_client, layers = habitats_directive_layer_names ) #> # A tibble: 3 × 9 #> # Rowwise: #> data_source service_name service_url layer_name title abstract class format layer_namespace #> #> 1 emodnet_wfs https://ows.emodnet-… seabed_hab… art17_hab… 2013… "Gridde… WFSF… sf emodnet_open #> 2 emodnet_wfs https://ows.emodnet-… seabed_hab… art17_hab… 2013… "Gridde… WFSF… sf emodnet_open #> 3 emodnet_wfs https://ows.emodnet-… seabed_hab… art17_hab… 2013… "Gridde… WFSF… sf emodnet_open ``` We are now ready to read the layers into R with `emodnet_get_layers()`. emodnet.wfs reads the geometries as simple features (See `sf` package) transformed to [4326](https://epsg.io/4326) by default. Specifying another map projection is possible by passing a EPGS code or projection string with `emodnet_get_layers(crs = "your projection")` where crs is a coordinate reference system (CRS). The argument `simplify = TRUE` stack all the layers in one single tibble. Default is FALSE and returns a list of sf objects, one per layer. ``` r habitats_directive_layers <- emodnet_get_layers( wfs = seabed_wfs_client, layers = habitats_directive_layer_names, simplify = TRUE, outputFormat = "application/json" ) habitats_directive_layers #> Simple feature collection with 221 features and 8 fields #> Geometry type: MULTIPOLYGON #> Dimension: XY #> Bounding box: xmin: 950000 ymin: 940000 xmax: 6510000 ymax: 4820000 #> Projected CRS: ETRS89-extended / LAEA Europe #> First 10 features: #> id habitat_code ms region cs_ms country_code #> 1 art17_hab_1110.13 1110 DK ATL U2+ Denmark #> 2 art17_hab_1110.22 1110 ES MAC U1+ Spain #> 3 art17_hab_1110.25 1110 ES MMAC U1+ Spain #> 4 art17_hab_1110.59 1110 PT MMAC XX Portugal #> 5 art17_hab_1110.56 1110 PT MATL U1- Portugal #> 6 art17_hab_1110.53 1110 PL MBAL U1- Poland #> 7 art17_hab_1110.17 1110 DK MBAL U1- Denmark #> 8 art17_hab_1110.31 1110 FR MATL U1x France #> 9 art17_hab_1110.75 1110 UK MATL U1x United Kingdom #> 10 art17_hab_1110.1 1110 BE ATL U1x Belgium #> habitat_code_uri #> 1 http://dd.eionet.europa.eu/vocabulary/art17_2018/habitats/1110 #> 2 http://dd.eionet.europa.eu/vocabulary/art17_2018/habitats/1110 #> 3 http://dd.eionet.europa.eu/vocabulary/art17_2018/habitats/1110 #> 4 http://dd.eionet.europa.eu/vocabulary/art17_2018/habitats/1110 #> 5 http://dd.eionet.europa.eu/vocabulary/art17_2018/habitats/1110 #> 6 http://dd.eionet.europa.eu/vocabulary/art17_2018/habitats/1110 #> 7 http://dd.eionet.europa.eu/vocabulary/art17_2018/habitats/1110 #> 8 http://dd.eionet.europa.eu/vocabulary/art17_2018/habitats/1110 #> 9 http://dd.eionet.europa.eu/vocabulary/art17_2018/habitats/1110 #> 10 http://dd.eionet.europa.eu/vocabulary/art17_2018/habitats/1110 #> habitat_description geometry #> 1 Sandbanks which are slightly covered by sea water all the time MULTIPOLYGON (((4200000 360... #> 2 Sandbanks which are slightly covered by sea water all the time MULTIPOLYGON (((1950000 950... #> 3 Sandbanks which are slightly covered by sea water all the time MULTIPOLYGON (((1960000 950... #> 4 Sandbanks which are slightly covered by sea water all the time MULTIPOLYGON (((1810000 120... #> 5 Sandbanks which are slightly covered by sea water all the time MULTIPOLYGON (((2730000 173... #> 6 Sandbanks which are slightly covered by sea water all the time MULTIPOLYGON (((4610000 346... #> 7 Sandbanks which are slightly covered by sea water all the time MULTIPOLYGON (((4310000 352... #> 8 Sandbanks which are slightly covered by sea water all the time MULTIPOLYGON (((3790000 314... #> 9 Sandbanks which are slightly covered by sea water all the time MULTIPOLYGON (((3780000 319... #> 10 Sandbanks which are slightly covered by sea water all the time MULTIPOLYGON (((3800000 313... ``` Note the use of the `outputFormat` argument in this example. This specifies the file type to request from the service, which can influence how the data is loaded into R. By default, the data is provided in the `GML` format with a geometry type of "MULTISURFACE." However, this geometry type is not widely supported by many software tools, including the `mapview` package. To address this, you can request a different file type, such as GeoJSON, which delivers the geometry as "MULTIPOLYGON"—a format that is more universally compatible. This has been raised before in the [sf community](https://github.com/r-spatial/sf/issues/748). Run the following code to have a quick look at the layers geometries. ``` r mapview(habitats_directive_layers, zcol = "habitat_description", burst = TRUE) ```
Interactive map of layers in the habitat directive

plot of chunk unnamed-chunk-6

EMODnet provides also physics, chemistry, biological or bathymetry data. Explore all the layers available with: ``` r emodnet_get_all_wfs_info() #> # A tibble: 1,734 × 9 #> # Rowwise: #> data_source service_name service_url layer_name title abstract class format layer_namespace #> #> 1 emodnet_wfs bathymetry https://ows.emodne… download_… Bath… "Downlo… WFSF… sf emodnet #> 2 emodnet_wfs bathymetry https://ows.emodne… contours Dept… "Genera… WFSF… sf emodnet #> 3 emodnet_wfs bathymetry https://ows.emodne… hr_bathym… High… "Layer … WFSF… sf emodnet #> 4 emodnet_wfs bathymetry https://ows.emodne… quality_i… Qual… "Repres… WFSF… sf emodnet #> 5 emodnet_wfs bathymetry https://ows.emodne… sea_names Sea … "Mainta… WFSF… sf world #> 6 emodnet_wfs bathymetry https://ows.emodne… source_re… Sour… "Covera… WFSF… sf emodnet #> 7 emodnet_wfs bathymetry https://ows.emodne… undersea_… unde… "" WFSF… sf gebco #> 8 emodnet_wfs biology https://geo.vliz.b… mediseh_c… EMOD… "Coral … WFSF… sf Emodnetbio #> 9 emodnet_wfs biology https://geo.vliz.b… mediseh_c… EMOD… "Coral … WFSF… sf Emodnetbio #> 10 emodnet_wfs biology https://geo.vliz.b… mediseh_c… EMOD… "Cymodo… WFSF… sf Emodnetbio #> # ℹ 1,724 more rows ``` ## More information ### References Blondel, Emmanuel. (2020, May 27). ows4R: R Interface to OGC Web-Services (Version 0.1-5). Zenodo. https://doi.org/10.5281/zenodo.3860330 Flanders Marine Institute (2019). Maritime Boundaries Geodatabase, version 11. Available online at https://www.marineregions.org/. https://doi.org/10.14284/382. Hadley Wickham, Romain François, Lionel Henry and Kirill Müller (2020). dplyr: A Grammar of Data Manipulation. R package version 1.0.2.https://CRAN.R-project.org/package=dplyr Pebesma E (2018). “Simple Features for R: Standardized Support for Spatial Vector Data.” The R Journal, 10(1), 439–446. doi: 10.32614/RJ-2018-009, https://doi.org/10.32614/RJ-2018-009. R Core Team (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/. Tim Appelhans, Florian Detsch, Christoph Reudenbach and Stefan Woellauer (2020). mapview: Interactive Viewing of Spatial Data in R. R package version 2.9.0. https://CRAN.R-project.org/package=mapview ### Code To cite emodnet.wfs, please use the output from `citation(package = "emodnet.wfs")`. ``` r citation(package = "emodnet.wfs") #> To cite package 'emodnet.wfs' in publications use: #> #> Krystalli A, Fernández-Bejarano S, Salmon M (????). _emodnet.wfs: Access EMODnet Web #> Feature Service data through R_. doi:10.14284/679 , R #> package version 2.0.2.9000. Integrated data products created under the European Marine #> Observation Data Network (EMODnet) Biology project #> (EASME/EMFF/2017/1.3.1.2/02/SI2.789013), funded by the by the European Union under #> Regulation (EU) No 508/2014 of the European Parliament and of the Council of 15 May 2014 #> on the European Maritime and Fisheries Fund, . #> #> A BibTeX entry for LaTeX users is #> #> @Manual{, #> title = {{emodnet.wfs}: Access EMODnet Web Feature Service data through R}, #> author = {Anna Krystalli and Salvador Fernández-Bejarano and Maëlle Salmon}, #> note = {R package version 2.0.2.9000. Integrated data products created under the European Marine Observation Data Network (EMODnet) Biology project (EASME/EMFF/2017/1.3.1.2/02/SI2.789013), funded by the by the European Union under Regulation (EU) No 508/2014 of the European Parliament and of the Council of 15 May 2014 on the European Maritime and Fisheries Fund}, #> url = {https://github.com/EMODnet/emodnet.wfs}, #> doi = {10.14284/679}, #> } ```