105_netcdf.ipynb

Kernel: Python 3

Visualizing NetCDF data

Uncomment the following line to install geemap if needed.

# !pip install geemap xarray rioxarray netcdf4 localtileserver

import geemap

Download a sample NetCDF dataset.

url = "https://github.com/giswqs/leafmap/raw/master/examples/data/wind_global.nc"
filename = "wind_global.nc"

geemap.download_file(url, output=filename)

Read the NetCDF dataset.

data = geemap.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.

tif = "wind_global.tif"
geemap.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.

geojson = "https://github.com/giswqs/leafmap/raw/master/examples/data/countries.geojson"

m = geemap.Map(layer_ctrl=True)
m.add_raster(tif, band=[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.

m = geemap.Map(layer_ctrl=True)
m.add_netcdf(
    filename,
    variables=["v_wind"],
    palette="coolwarm",
    shift_lon=True,
    layer_name="v_wind",
)
m.add_geojson(geojson, layer_name="Countries")
m

Visualizing wind velocity.

m = geemap.Map(layer_ctrl=True)
m.add_basemap("CartoDB.DarkMatter")
m.add_velocity(filename, zonal_speed="u_wind", meridional_speed="v_wind")
m