AI-generated Key Takeaways
-
Access the Contrails API using Python with libraries like
requests
andxarray
to retrieve contrail environmental impact data. -
Define parameters such as bounding box, aircraft type, and time to specify your API query.
-
Utilize the provided Google API key and endpoint URL for authentication and data retrieval.
-
Refer to the linked Google Colab notebook for a comprehensive example on querying the API and visualizing the data.
Access the forecast grid API with Python:
import io
import requests
import xarray as xr
API_KEY = "AIza...(replace with your API key)"
params = {"time": "2025-05-15T20:00:00Z"}
response = requests.get(
url="https://contrails.googleapis.com/v2/grids",
params=params,
headers={"x-goog-api-key": API_KEY},
)
response.raise_for_status()
dataset = xr.load_dataset(io.BytesIO(response.content))
To visualize the data, use the Public_Contrails_API_Tester notebook.
To access the forecast region API with Python:
import requests
import geopandas as gpd
API_KEY = "AIza...(replace with your API key)"
params = {"time": "2025-05-15T20:00:00Z"}
response = requests.get(
url="https://contrails.googleapis.com/v2/regions",
params=params,
headers={"x-goog-api-key": API_KEY},
)
response.raise_for_status()
geodataframe = gpd.GeoDataFrame.from_features(response.json())