This package was formerly known as nPacMaps. This R package relies on
data downloaded from the Global Self-consistent, Hierarchical,
High-resolution Geography (GSHHG)
Database.
More details on the GSHHG can be found on this website from the
University of Hawaii. The
current version supported in this package is 2.3.7 (July, 2017).
The main objective is to provide a simple interface for loading basemap
polygon land data for the North Pacific region that can be used in the
sf and ggplot2 R package ecosystem. There are a variety of
pre-described regions that are loaded with convenience functions.
However, most regions of the world are supported and custom extractions
are possible with extract_gshhg().
This package is under development and functionality is subject to change and improvement at anytime.
Please cite this package as:
London, Josh M. ptolemy: an R package for accessing global high-resolution geography. 2018. Version 1.0.0. https://github.com/jmlondon/ptolemy. 10.5281/zenodo.1470706
and, also cite the GSHHG dataset:
Wessel, P., and W. H. F. Smith. A Global Self-consistent, Hierarchical, High-resolution Shoreline Database. J. Geophys. Res., 101, 8741-8743, 1996.
The ptolemy package is not available on CRAN and must be installed via
the devtools::install_github() function.
install.packages("devtools")
devtools::install_github('jmlondon/ptolemy')After successfully installing the package from GitHub, you will need to
download and install the GSHGG data. This is handled via the
ptolemy::install_gshhg() function. If you are not prompted, you may
need to run ptolemy::install_gsggh() before using the package.
library(ptolemy)
install_gshhg()The data parameter should be an sf object representing the region of
interest. This can be data points, polygons, lines and should be
projected. If the data are provided in longlat, an epsg parameter code
is required.
The GSHHG dataset has five different resolutions available:
- full resolution: Original (full) data resolution.
- high resolution: About 80 % reduction in size and quality.
- intermediate resolution: Another ~80 % reduction.
- low resolution: Another ~80 % reduction.
- crude resolution: Another ~80 % reduction.
The intermediate reolustion has been set as the default option and
should suffice for most applications. The default resolution can be
overided via the resolution parameter. Users should consider bumping
up to high or full when zooming into smaller scale regions. This
will increase the extraction and drawing time. If you require the
full resolution frequently, creating a custom region via
extract_gshhg() should be considered.
All of the returned maps are provide with projected coordinates based on
the epsg parameter provided. For the pre-built regions, the default
projections are sensible and all users need to do is insure all other
data is transformed to the same projection. A custom projection can be
provided.
The returned map region will be slightly larger than the area of interest represented by the provided data. The default is 5000 meters.
The rmapshaper::ms_simplify function can applied to the returned
objects to improve performance. The function is set to return 20% of the
original points and to preserve small shapes (i.e. small islands and
other features). This improves performance for plotting and should
suffice for most users. However, the original integrity of the GSHHG
data will be changed. Uses for analytical purposes (e.g. calculating
distance to shoreline, least-cost path creation around land) should not
use this option without consideration of impacts.
By default all of the basemap objects are returned as an sf object.
ggplot2 now offers native support for plotting sf objects via the
geom_sf. The examples below demonstrate basic use of geom_sf.
This package relies heavily on the works of other researchers and
developers. The GSHHG dataset is developed and maintained by Paul Wessel
(SOEST, University of Hawai’i, Honolulu, HI) and Walter H. F. Smith
(NOAA Geosciences Lab, National Ocean Service, Silver Spring, MD). The
package also relies on code developed as part of the PBSmapping
package (Jon T. Schnute, Nicholas Boers and Rowan Haigh (2018).
PBSmapping: Mapping Fisheries Data and Spatial Analysis Tools. R package
version 2.70.5. https://CRAN.R-project.org/package=PBSmapping.)
library(ggplot2)
library(ptolemy)
library(sf)
#> Linking to GEOS 3.6.2, GDAL 2.3.0, PROJ 5.1.0
npac_base <- ptolemy::npac()
#> importGSHHS status:
#> --> Pass 1: complete: 15631 bounding boxes within limits.
#> --> Pass 2: complete.
#> --> Clipping...
#> Warning in refocusWorld(as.PolySet(as.data.frame(xres), projection = "LL"), : Removed duplicates of following polygons (Antarctica?): 0, 1, 15
#> importGSHHS: input xlim was (0, 360) and the longitude range of the extracted data is (0, 359.532917).
#> Warning in st_buffer.sfc(st_geometry(x), dist, nQuadSegs, endCapStyle =
#> endCapStyle, : st_buffer does not correctly buffer longitude/latitude data
#> dist is assumed to be in decimal degrees (arc_degrees).
npac_plot <- ggplot() +
geom_sf(data = npac_base,
fill = "grey60", size = 0.2) +
ggtitle('North Pacific Basemap (epsg:3832)')
npac_plot
library(ggplot2)
library(ptolemy)
library(sf)
calcur_base <- ptolemy::calcur()
#> importGSHHS status:
#> --> Pass 1: complete: 5028 bounding boxes within limits.
#> --> Pass 2: complete.
#> --> Clipping...
#> Warning in refocusWorld(as.PolySet(as.data.frame(xres), projection = "LL"), : Removed duplicates of following polygons (Antarctica?): 0, 1, 15
#> importGSHHS: input xlim was (0, 360) and the longitude range of the extracted data is (0, 359.532917).
#> Warning in st_buffer.sfc(st_geometry(x), dist, nQuadSegs, endCapStyle =
#> endCapStyle, : st_buffer does not correctly buffer longitude/latitude data
#> dist is assumed to be in decimal degrees (arc_degrees).
calcur_plot <- ggplot() +
geom_sf(data = calcur_base,
fill = "grey60", size = 0.2) +
ggtitle('California Current Basemap (epsg:3310)')
calcur_plot
library(ggplot2)
library(ptolemy)
library(sf)
bering_base <- ptolemy::bering()
#> importGSHHS status:
#> --> Pass 1: complete: 13265 bounding boxes within limits.
#> --> Pass 2: complete.
#> --> Clipping...
#> Warning in refocusWorld(as.PolySet(as.data.frame(xres), projection = "LL"), : Removed duplicates of following polygons (Antarctica?): 0, 15
#> importGSHHS: input xlim was (0, 360) and the longitude range of the extracted data is (0, 359.442861).
#> Warning in st_buffer.sfc(st_geometry(x), dist, nQuadSegs, endCapStyle =
#> endCapStyle, : st_buffer does not correctly buffer longitude/latitude data
#> dist is assumed to be in decimal degrees (arc_degrees).
bering_plot <- ggplot() +
geom_sf(data = bering_base,
fill = "grey60", size = 0.2) +
ggtitle('Bering Sea Basemap (epsg:3571)')
bering_plot
library(ggplot2)
library(ptolemy)
library(sf)
us_arctic_base <- ptolemy::us_arctic()
#> importGSHHS status:
#> --> Pass 1: complete: 9256 bounding boxes within limits.
#> --> Pass 2: complete.
#> --> Clipping...
#> Warning in refocusWorld(as.PolySet(as.data.frame(xres), projection = "LL"), : Removed duplicates of following polygons (Antarctica?): 0, 15
#> importGSHHS: input xlim was (0, 360) and the longitude range of the extracted data is (4.585778, 359.275833).
#> Warning in st_buffer.sfc(st_geometry(x), dist, nQuadSegs, endCapStyle =
#> endCapStyle, : st_buffer does not correctly buffer longitude/latitude data
#> dist is assumed to be in decimal degrees (arc_degrees).
us_arctic_plot <- ggplot() +
geom_sf(data = us_arctic_base,
fill = "grey60", size = 0.2) +
ggtitle('US Arctic Basemap (epsg:3572)')
us_arctic_plot
library(ggplot2)
library(ptolemy)
library(sf)
ak_base <- ptolemy::alaska()
#> importGSHHS status:
#> --> Pass 1: complete: 10988 bounding boxes within limits.
#> --> Pass 2: complete.
#> --> Clipping...
#> Warning in refocusWorld(as.PolySet(as.data.frame(xres), projection = "LL"), : Removed duplicates of following polygons (Antarctica?): 0, 15
#> importGSHHS: input xlim was (0, 360) and the longitude range of the extracted data is (0, 359.275833).
#> Warning in st_buffer.sfc(st_geometry(x), dist, nQuadSegs, endCapStyle =
#> endCapStyle, : st_buffer does not correctly buffer longitude/latitude data
#> dist is assumed to be in decimal degrees (arc_degrees).
ak_plot <- ggplot() +
geom_sf(data = ak_base,
fill = "grey60", size = 0.2) +
ggtitle('Alaska Basemap (epsg:3338)')
ak_plot
We can also zoom in on a particular region
library(ggplot2)
library(ptolemy)
library(crawl)
#> crawl 2.2.2 (2018-09-17)
#> Demos and documentation can be found at our new GitHub repository:
#> https://dsjohnson.github.io/crawl_examples/
library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
library(sf)
data("harborSeal")
harborSeal <- harborSeal %>%
filter(!is.na(latitude)) %>%
as.data.frame() %>%
sf::st_as_sf(coords = c("longitude","latitude")) %>%
sf::st_set_crs(4326) %>%
sf::st_transform(3338)
map_base <- ptolemy::extract_gshhg(data = harborSeal)
#> importGSHHS status:
#> --> Pass 1: complete: 2198 bounding boxes within limits.
#> --> Pass 2: complete.
#> --> Clipping...
#> Warning in refocusWorld(as.PolySet(as.data.frame(xres), projection = "LL"), : Removed duplicates of following polygons (Antarctica?): 0, 15
#> importGSHHS: input xlim was (0, 360) and the longitude range of the extracted data is (4.854056, 358.222472).
#> Warning in st_buffer.sfc(st_geometry(x), dist, nQuadSegs, endCapStyle =
#> endCapStyle, : st_buffer does not correctly buffer longitude/latitude data
#> dist is assumed to be in decimal degrees (arc_degrees).
ak_plot <- ggplot() +
geom_sf(data = map_base,
fill = "grey60", size = 0.2) +
geom_sf(data = harborSeal,
alpha = 0.1, color = 'blue')
ak_plot
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