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# !pip install leafmap
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# !pip install xarray rioxarray netcdf4 localtileserver
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from leafmap import leafmap
Download a sample NetCDF dataset.
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url = "https://github.com/opengeos/datasets/releases/download/raster/wind_global.nc"
filename = "wind_global.nc"
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leafmap.download_file(url, output=filename, overwrite=True)
Read the NetCDF dataset.
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data = leafmap.read_netcdf(filename)
data
Convert the NetCDF dataset to GeoTIFF. Note that the longitude range of the NetCDF dataset is [0, 360]. We need to convert it to [-180, 180] by setting shift_lon=True so that it can be displayed on the map.
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tif = "wind_global.tif"
leafmap.netcdf_to_tif(filename, tif, variables=["u_wind", "v_wind"], shift_lon=True)
Add the GeoTIFF to the map. We can also overlay the country boundary on the map.
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geojson = (
"https://github.com/opengeos/leafmap/raw/master/examples/data/countries.geojson"
)
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m = leafmap.Map(layers_control=True)
m.add_raster(tif, indexes=[1], palette="coolwarm", layer_name="u_wind")
m.add_geojson(geojson, layer_name="Countries")
m
You can also use the add_netcdf() function to add the NetCDF dataset to the map without having to convert it to GeoTIFF explicitly.
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m = leafmap.Map(layers_control=True)
m.add_netcdf(
filename,
variables=["v_wind"],
palette="coolwarm",
shift_lon=True,
layer_name="v_wind",
indexes=[1],
)
m.add_geojson(geojson, layer_name="Countries")
m
Visualizing wind velocity.
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m = leafmap.Map(layers_control=True)
m.add_basemap("CartoDB.DarkMatter")
m.add_velocity(
filename,
zonal_speed="u_wind",
meridional_speed="v_wind",
color_scale=[
"rgb(0,0,150)",
"rgb(0,150,0)",
"rgb(255,255,0)",
"rgb(255,165,0)",
"rgb(150,0,0)",
],
)
m
