Note
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Roads
The pygmt.Figure.plot
method allows us to plot geographical data such
as lines which are stored in a geopandas.GeoDataFrame
object. Use
geopandas.read_file
to load data from any supported OGR format such as
a shapefile (.shp), GeoJSON (.geojson), geopackage (.gpkg), etc. Then, pass the
geopandas.GeoDataFrame
as an argument to the data
parameter of
pygmt.Figure.plot
, and style the geometry using the pen
parameter.
import geopandas as gpd
import pygmt
# Read shapefile data using geopandas
gdf = gpd.read_file(
"http://www2.census.gov/geo/tiger/TIGER2015/PRISECROADS/tl_2015_15_prisecroads.zip"
)
# The dataset contains different road types listed in the RTTYP column,
# here we select the following ones to plot:
roads_common = gdf[gdf.RTTYP == "M"] # Common name roads
roads_state = gdf[gdf.RTTYP == "S"] # State recognized roads
roads_interstate = gdf[gdf.RTTYP == "I"] # Interstate roads
fig = pygmt.Figure()
# Define target region around Oʻahu (Hawaiʻi)
region = [-158.3, -157.6, 21.2, 21.75] # xmin, xmax, ymin, ymax
title = "Main roads of O`ahu (Hawai`i)" # Approximating the Okina letter ʻ with `
fig.basemap(region=region, projection="M12c", frame=["af", f"WSne+t{title}"])
fig.coast(land="gray", water="dodgerblue4", shorelines="1p,black")
# Plot the individual road types with different pen settings and assign labels
# which are displayed in the legend
fig.plot(data=roads_common, pen="5p,dodgerblue", label="CommonName")
fig.plot(data=roads_state, pen="2p,gold", label="StateRecognized")
fig.plot(data=roads_interstate, pen="2p,red", label="Interstate")
# Add legend
fig.legend()
fig.show()
Total running time of the script: (0 minutes 1.584 seconds)