Get started with Cecil in a few steps.

1. Sign up for an account

Run the following command in your terminal and follow the interactive prompt. The organisation name must start with a letter and contain only letters, numbers, and spaces. You will receive an email with instructions to generate your user API key. By signing up for an account, you agree to each Dataset Pricing and our Terms of Service.

/bin/bash -c "$(curl -fsSL <https://cecil.earth/sign-up.sh>)"

2. Install and configure the SDK

Install the SDK in your project virtual environment. Python ≥ 3.11 is required.

pip install cecil

Configure the SDK by setting the CECIL_API_KEY environment variable. Make sure to store your API key in an encrypted vault or secrets manager. Never store API keys in code or plain/text files.

# Linux and macOS
export CECIL_API_KEY="my-api-key"

# Windows
set CECIL_API_KEY=my-api-key

3. Create an area of interest (AOI)

Create an AOI using the geometry object of a GeoJSON in EPSG:4326 coordinate reference system (CRS). Learn more about the AOI specification in the SDK.

import cecil

client = cecil.Client()

aoi = client.create_aoi(
    geometry={
        "type": "Polygon",
        "coordinates": [
            [
                [132.52934211276073, -12.721072673008706],
                [132.52934211276073, -12.730063400794094],
                [132.54027735328083, -12.730063400794094],
                [132.54027735328083, -12.721072673008706],
                [132.52934211276073, -12.721072673008706]
            ]
        ]
    }
)

print(aoi)

4. Acquire a dataset for your AOI

Create a data request for your AOI using a dataset_id from our available datasets. This step runs in the background and the processing time varies from a few minutes to a few business days depending on the data provider.

import cecil

client = cecil.Client()

planet_forest_carbon_diligence = client.create_data_request(
    aoi_id="my-aoi-id",
    dataset_id="53738a57-a889-43c9-8f7a-7cb306831700",
)

print(planet_forest_carbon_diligence)

5. Analyse your dataset

Install the following Python modules for data visualisation.

pip install geopandas
pip install matplotlib

Visualise canopy cover in 2023 across the entire AOI.