The World Database on Protected Areas (WDPA) is the most comprehensive global dataset of protected areas. It is used to monitor the performance of existing protected areas and pinpoint priority areas for establishing new protected areas. Additionally, this database receives monthly updates from government agencies and non-governmental organizations. However, this dataset is associated with many issues that need to be addressed prior to analysis and the dynamic nature of this dataset means that the entire data cleaning process needs to be repeated after obtaining a new version of the dataset. The wdpar R package provides an interface to the World Database on Protected Areas (WDPA) and functions for cleaning the data following best practices (outlined in Butchart et al. 2015; Runge et al. 2015; Protected Planet).
The latest official version of the wdpar R package can be installed using the following R code. Please note that this package requires the curl and sf R packages which may require additional software to be installed. If you encounter problems installing the wdpar R package, please consult the installation instructions for these packages.
install.packages("wdpar", repos = "https://cran.rstudio.com/")
Alternatively, the latest developmental version can be installed using the following R code. Please note that while developmental versions may contain additional features not present in the official version, they may also contain coding errors.
Here we will provide a short introduction to the wdpar R package. First, we will load the wdpar R package. We will also load the dplyr and ggmap R packages to help explore the data.
# download protected area data for Malta mlt_raw_pa_data <- wdpa_fetch("Malta", wait = TRUE)
Next, we will clean the data set. Briefly, the cleaning steps include: excluding protected areas that are not yet implemented, excluding protected areas with limited conservation value, replacing missing data codes (e.g.
"0") with missing data values (i.e.
NA), replacing protected areas represented as points with circular protected areas that correspond to their reported extent, repairing any topological issues with the geometries, and erasing overlapping areas. For more information, see
# clean Malta data mlt_pa_data <- wdpa_clean(mlt_raw_pa_data)
Print preview of the data associated with each protected area.
# print preview head(mlt_pa_data)
## Simple feature collection with 6 features and 32 fields ## Geometry type: MULTIPOLYGON ## Dimension: XY ## Bounding box: xmin: 1369012 ymin: 4280784 xmax: 1399694 ymax: 4307909 ## CRS: +proj=cea +lon_0=0 +lat_ts=30 +x_0=0 +y_0=0 +datum=WGS84 +ellps=WGS84 +units=m +no_defs ## Precision: 1500 ## # A tibble: 6 x 33 ## WDPAID WDPA_PID PA_DEF NAME ORIG_NAME DESIG DESIG_ENG DESIG_TYPE IUCN_CAT ## <dbl> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> ## 1 1.94e5 194420 1 Filf… Filfla Riser… Nature Re… National Ia ## 2 1.94e5 194423 1 Il-Ġ… Il-Ġebla… Riser… Nature Re… National Ia ## 3 1.94e5 194425 1 Il-G… Il-Gżejj… Riser… Nature Re… National Ia ## 4 5.56e8 555588631 1 Il-M… Il-Majji… Park … National … National II ## 5 1.75e5 174757 1 Il-Ġ… Il-Ġonna… List … List Of H… National III ## 6 1.75e5 174758 1 Bidn… Bidnija,… List … List Of H… National III ## # … with 24 more variables: INT_CRIT <chr>, MARINE <chr>, REP_M_AREA <dbl>, ## # GIS_M_AREA <dbl>, REP_AREA <dbl>, GIS_AREA <dbl>, NO_TAKE <chr>, ## # NO_TK_AREA <dbl>, STATUS <chr>, STATUS_YR <dbl>, GOV_TYPE <chr>, ## # OWN_TYPE <chr>, MANG_AUTH <chr>, MANG_PLAN <chr>, VERIF <chr>, ## # METADATAID <int>, SUB_LOC <chr>, PARENT_ISO <chr>, ISO3 <chr>, ## # SUPP_INFO <chr>, CONS_OBJ <chr>, GEOMETRY_TYPE <chr>, AREA_KM2 <dbl>, ## # geometry <MULTIPOLYGON [m]>
Finally, after cleaning the data, let’s plot a map showing Malta’s protected areas and color each area according to its management category (as defined by the The International Union for Conservation of Nature).
# reproject data to longitude/latitude for plotting mlt_pa_data <- st_transform(mlt_pa_data, 4326) # download basemap imagery bg <- get_stamenmap(unname(st_bbox(mlt_pa_data)), zoom = 8, maptype = "watercolor", force = TRUE) # make map ggmap(bg) + geom_sf(aes(fill = IUCN_CAT), data = mlt_pa_data, inherit.aes = FALSE) + theme(axis.title = element_blank(), legend.position = "bottom")
If you need to calculate protected area coverage statistics for a country, please note that you will need to manually clip the cleaned protected area data to the countries’ coastline and its Exclusive Economic Zone (EEZ) to obtain accurate results (see official data cleaning guidelines). This step is not performed by the wdpar R package because there is no single “best” coastline and Exclusive Economic Zone (EEZ) dataset, since the “best” dataset for any given project depends on the level of required precision and available computational resources. For more examples—including an example of clipping the cleaned data to a coastline—please refer to the package vignette.
Please cite the wdpar R package and the World Database on Protected Areas (WDPA) in publications.
To cite the wdpar package in publications, use: Hanson JO (2021) wdpar: Interface to the World Database on Protected Areas. R package version 126.96.36.199. https://github.com/prioritizr/wdpar UNEP-WCMC and IUCN (2021) Protected Planet: The World Database on Protected Areas (WDPA), [insert month/year of the version downloaded], Cambridge, UK: UNEP-WCMC and IUCN. Available at: www.protectedplanet.net. Please cite both the World Database on Protected Areas data set and this package. To see these entries in BibTeX format, use 'print(<citation>, bibtex=TRUE)', 'toBibtex(.)', or set 'options(citation.bibtex.max=999)'.