- pygmt.datasets.load_earth_mask(resolution='01d', region=None, registration=None)
Load the GSHHG Global Earth Mask in various resolutions.
The grids are downloaded to a user data directory (usually
~/.gmt/server/earth/earth_mask/) the first time you invoke this function. Afterwards, it will load the grid from the data directory. So you’ll need an internet connection the first time around.
These grids can also be accessed by passing in the file name @earth_mask_res[_reg] to any grid plotting/processing function. res is the grid resolution (see below), and reg is grid registration type (p for pixel registration or g for gridline registration).
Refer to https://www.generic-mapping-tools.org/remote-datasets/earth-mask.html for more details.
resolution (str) – The grid resolution. The suffix
sstand for arc-degrees, arc-minutes, and arc-seconds. It can be
registration (str) – Grid registration type. Either
"pixel"for pixel registration or
"gridline"for gridline registration. Default is
xarray.DataArray) – The Earth mask grid. Coordinates are latitude and longitude in degrees. The node values in the mask grids are all in the 0-4 range and reflect different surface types:
0: Oceanic areas beyond the shoreline
1: Land areas inside the shoreline
2: Lakes inside the land areas
3: Islands in lakes in the land areas
4: Smaller lakes in islands that are found within lakes inside the land area
The registration and coordinate system type of the returned
xarray.DataArraygrid can be accessed via the GMT accessors (i.e.,
grid.gmt.gtyperespectively). However, these properties may be lost after specific grid operations (such as slicing) and will need to be manually set before passing the grid to any PyGMT data processing or plotting functions. Refer to
pygmt.GMTDataArrayAccessorfor detailed explanations and workarounds.
>>> from pygmt.datasets import load_earth_mask >>> # load the default grid (gridline-registered 1 arc-degree grid) >>> grid = load_earth_mask() >>> # location (120°E, 50°N) is in land area (1) >>> grid.sel(lon=120, lat=50).values array(1, dtype=int8) >>> # location (170°E, 50°N) is in oceanic area (0) >>> grid.sel(lon=170, lat=50).values array(0, dtype=int8)