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Development","sub_category":"Data Catalogs and Interfaces","monthly_downloads":0,"total_dependent_repos":0,"total_dependent_packages":0,"readme":"---\noutput: github_document\n---\n\n\u003c!-- README.md is generated from README.Rmd. Please edit that file --\u003e\n\n```{r setup, include=FALSE}\nknitr::opts_chunk$set(\n  collapse = TRUE,\n  comment = \"#\u003e\",\n  fig.path = \"man/figures/README-\",\n  out.width = \"100%\"\n)\n```\n\n# emodnet.wcs\n\n\u003c!-- badges: start --\u003e\n\n[![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html#experimental) \n[![CRAN status](https://www.r-pkg.org/badges/version/emodnet.wcs)](https://CRAN.R-project.org/package=emodnet.wcs) \n[![R-CMD-check](https://github.com/EMODnet/emodnet.wcs/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/EMODnet/emodnet.wcs/actions/workflows/R-CMD-check.yaml)\n[![codecov](https://codecov.io/gh/EMODnet/emodnet.wcs/branch/main/graph/badge.svg)](https://codecov.io/gh/EMODnet/emodnet.wcs)\n\u003c!-- badges: end --\u003e\n\nThe goal of emodnet.wcs is to allow interrogation of and access to EMODnet geographic raster data in R though the [EMODnet Web Coverage Services](https://github.com/EMODnet/Web-Service-Documentation#web-coverage-service-wcs).\nEMODnet raster datasets, such as habitat maps or bathymetry, are available through Web Coverage Services (WCS). \nThese data are continuous, gridded, and often used for spatial visualization or environmental modeling. \nSee below for available Services (data sources).\nThis package was developed by Sheffield University as part of EMODnet Biology WP4.\n\n[Web Coverage services (WCS)](https://www.ogc.org/standards/wcs) is a standard created by the OGC that refers to the receiving of geospatial information as 'coverages': digital geospatial information representing space-varying phenomena.\nOne can think of it as Web Feature Service (WFS) for raster data.\nIt gets the 'source code' of the map, but in this case it's not raw vectors but raw imagery.\n\nAn important distinction must be made between WCS and Web Map Service (WMS).\nThey are similar, and can return similar formats, but a WCS is able to return more information, including valuable metadata and more formats.\nIt additionally allows more precise queries, potentially against multi-dimensional backend formats.\n\n## Installation\n\nYou can install the development version of emodnet.wcs from GitHub with:\n\n```r\n# install.packages(\"pak\")\npak::pak(\"EMODnet/emodnet.wcs\")\n```\n\nLoad the library\n\n```{r load-lib}\nlibrary(emodnet.wcs)\n```\n\nIf you want to avoid reading messages from emodnet.wcs such as \"WCS client created successfully\", \nset the `\"emodnet.wcs.quiet\"` option to `TRUE`.\n\n```r\noptions(\"emodnet.wcs.quiet\" = TRUE)\n```\n\n## Available data sources (services)\n\nAll available services are contained in the tibble returned by `emdn_wcs()`.\n\n```{r services, echo=FALSE}\n\nknitr::kable(emdn_wcs())\n```\n\n\nTo explore available services you can use `View()` or your usual way to explore `data.frames`.\n\n## Connect to a data source: create service client\n\nCreate new WCS Client.\nSpecify the service using the `service` argument.\n\n```{r wcs-init}\nwcs \u003c- emdn_init_wcs_client(service = \"biology\")\n```\n\n## Get metadata about a service and available data (coverages)\n\nGet service level and a subset of coverage level metadata, compiled for easy review by supplying a `WCSClient` object to `emdn_get_wcs_info`.\n\n```{r wcs-info}\nemdn_get_wcs_info(wcs)\n```\n\nInfo can also be extracted using a service name instead of a `WCSClient` object.\n\n```{r wcs-info-name}\nemdn_get_wcs_info(service = \"biology\")\n```\n\nGet more detailed coverage metadata about specific coverage.\n\n```{r wcs-info-coverage}\nemdn_get_coverage_info(\n  wcs,\n  coverage_ids = \"Emodnetbio__aca_spp_19582016_L1\"\n)\n```\n\n\u003e **Note**\n\u003e \n\u003e To minimize the number of requests sent to webservices, these functions use [`memoise`](https://memoise.r-lib.org/) to cache results inside the active R session.\n\u003e To clear the cache, re-start R or run `memoise::forget(emdn_get_wcs_info)`/`memoise::forget(emdn_get_coverage_info)`\n\nThe package also offers a number of functions for extracting individual metadata in more usable forms. e.g.\n\n```{r}\nemdn_get_coverage_ids(wcs)\n```\n\nFor more details, please refer to the [Getting metadata about Services \\\u0026 Coverages](https://emodnet.github.io/emodnet.wcs/articles/metadata.html) article in the `emodnet.wcs` online documentation.\n\n## Download data (coverages)\n\nThe package also provides a function to download full or subsets of coverages from emodnet.wcs services.\n\nThe following example downloads a spatial subset of a coverage using a bounding box.\n\n```{r}\nwcs \u003c- emdn_init_wcs_client(service = \"human_activities\")\n\ncov \u003c- emdn_get_coverage(\n  wcs,\n  # pseudomercator (EPSG 3857) in this case:\n  crs = \"EPSG:3857\",\n  bbox = c(\n    xmin = 484177.9,\n    ymin = 6957617.3,\n    xmax = 1035747,\n    ymax = 7308616.2\n  ),\n  coverage_id = \"emodnet__vesseldensity_all\",\n  nil_values_as_na = FALSE\n)\n```\n\n```{r}\nterra::plot(log(cov))\n```\n\nFor more details on downloading coverages, please refer to the [Download Coverages](https://emodnet.github.io/emodnet.wcs/articles/coverages.html) article in the `emodnet.wcs` online documentation.\n\n```{r, include=FALSE}\nfs::dir_ls(type = \"file\", glob = \"*.tif\") |\u003e\n  fs::file_delete()\n```\n\n## Citation\n\nTo cite emodnet.wcs, please use the output from `citation(package = \"emodnet.wcs\")`.\n\n```{r}\ncitation(package = \"emodnet.wcs\")\n```\n\n\n## Unlock the Full Potential of the EMODnet Web Services: Access Feature and Gridded datasets.\n\n### Access EMODnet's Web Feature Service data through emodnet.wfs\n\nThe goal of [emodnet.wfs](https://docs.ropensci.org/emodnet.wfs) is to allow interrogation of and access to [EMODnet's, European Marine Observation and Data Network, geographic vector data](https://emodnet.ec.europa.eu/en/emodnet-web-service-documentation#inline-nav-3) in R through the [EMODnet Web Feature Services](https://emodnet.ec.europa.eu/en/data-0). \n[Web Feature services (WFS)](https://www.ogc.org/standards/wfs/) represent a change in the way geographic information is created, modified and exchanged on the Internet and offer direct fine-grained access to geographic information at the feature and feature property level. \nFeatures are representation of geographic entities, such as a coastlines, marine protected areas, offshore platforms, or fishing areas. In WFS, features have geometry (spatial information) and attributes (descriptive data).\nemodnet.wfs aims at offering an user-friendly interface to this rich data.\n\n### Access EMODnet gridded and tabular datasets through the ERDDAP Server and rerddap in R\n\nBoth WFS and WCS EMODnet services are based on a federated system: each EMODnet thematic lot manages their servers and data, ensuring that their data are exposed both via WFS and WCS. The twin R packages `emodnet.wfs` and `emodnet.wcs` simplify the access to all the entry points by collecting them in single places, which are the packages themselves. \n\nIn contrast, the [EMODnet ERDDAP Server](https://erddap.emodnet.eu) is centrally managed by the EMODnet Central Portal, offering a single access point to all gridded and tabular datasets. ERDDAP simplifies access to datasets such as digital terrain models, vessel density or environmental data. It is particularly suited for large-scale, multidimensional data analysis. In R, the `rerddap` package allows users to query and subset ERDDAP data programmatically, enabling efficient analysis and integration into workflows. For example, researchers can retrieve datasets on vessel density. \n\n```{r rerddap}\n# install.packages(\"rerrdap\")\nlibrary(rerddap)\n\n# This is the url where the EMODnet ERDDAP server is located\nerddap_url \u003c- \"https://erddap.emodnet.eu/erddap/\"\n\n# Inspect all available datasets\ned_datasets(url = erddap_url)\n\n# Find datasets with the key words \"vessel density\"\ned_search(query = \"vessel density\", url = erddap_url)\n\n# Inspect more info about the vessel density dataset, using its identifier\nhuman_activities_data_info \u003c- info(\n  datasetid = \"humanactivities_9f8a_3389_f08a\",\n  url = erddap_url\n)\nhuman_activities_data_info\n\n# Retrieve the vessel density at a particular time period\nyear_2020_gridded_data \u003c- griddap(\n  datasetx = human_activities_data_info,\n  time = c(\"2020-03-18\", \"2020-03-19\")\n)\nhead(year_2020_gridded_data$data)\n```\n\nMore functionalities are available through `rerddap`. Feel free to explore the [rerddap website](https://docs.ropensci.org/rerddap/) to find out what else can you do with the EMODnet datasets in ERDDAP.\n\n\n## Code of Conduct\n\nPlease note that the emodnet.wcs project is released with a [Contributor Code of Conduct](https://emodnet.github.io/emodnet.wcs/CODE_OF_CONDUCT.html).\nBy contributing to this project, you agree to abide by its terms.\n\n\n","funding_links":[],"readme_doi_urls":[],"works":{},"citation_counts":{},"total_citations":0,"keywords_from_contributors":["geocoding"],"project_url":"https://ost.ecosyste.ms/api/v1/projects/15607","html_url":"https://ost.ecosyste.ms/projects/15607"}