If you’re interested in accessing satellite imagery for remote sensing or geospatial analysis, Sentinel satellites, operated by the European Space Agency (ESA), are an excellent source of high-quality, free, and open data. In this tutorial, we will go through the process of downloading Sentinel satellite imagery using Python.

Step 1

Install Dependencies To start, you’ll need to have some Python libraries installed. You can install the necessary dependencies using pip, the Python package manager. Open a terminal or command prompt and run the following commands:

conda install -c conda-forge sentinelsat
conda install -c conda-forge rasterio

These libraries, sentinelsat and rasterio, are commonly used for downloading and processing satellite imagery in Python.

Step 2

Set Up an Account and Obtain API Credentials Next, you’ll need to create an account on the Copernicus Open Access Hub (https://scihub.copernicus.eu/dhus/#/home) in order to obtain API credentials for accessing the Sentinel data. Once you have an account, you can obtain your API username and password, which will be used in your Python code to authenticate and download the data.

Step 3

Import Libraries and Authenticate In your Python script, you’ll need to import the necessary libraries and authenticate using your API credentials. Here’s an example:

from sentinelsat import SentinelAPI, read_geojson, geojson_to_wkt
import geopandas as gpd

# Replace with your own API credentials
API_USERNAME = 'your_api_username'
API_PASSWORD = 'your_api_password'

# Authenticate with the API
api = SentinelAPI(API_USERNAME, API_PASSWORD, 'https://scihub.copernicus.eu/dhus')

Step 4

Search for and Download Sentinel Imagery You can now use the api object to search for and download Sentinel satellite imagery. For example, you can search for imagery based on location, date, cloud cover, and other parameters. Here’s an example of how you can search for Sentinel-2 Level-1C (top-of-atmosphere reflectance) imagery:

# Define search parameters
footprint = geojson_to_wkt(read_geojson('path/to/your/geojson/file.geojson'))
start_date = '2020-01-01'
end_date = '2020-12-31'
product_type = 'S2MSI1C'
cloud_cover = (0, 30)  # specify cloud cover percentage range

# Search for available products
products = api.query(footprint, date=(start_date, end_date), producttype=product_type, cloudcoverpercentage=cloud_cover)

# Download products
api.download_all(products)

This code will search for Sentinel-2 Level-1C imagery within the specified date range, for a given geographic footprint (defined by a geojson file), with a specified cloud cover percentage range. The downloaded data will be saved to your local machine.

Step 5

Process and Analyze the Downloaded Imagery Once you have downloaded the Sentinel satellite imagery, you can use libraries like rasterio to open, process, and analyze the data in Python. For example, you can read the downloaded image files, perform image processing tasks such as image enhancement, classification, or change detection, and extract relevant information from the imagery for your specific use case.

In this tutorial, we covered the basics of how to download Sentinel satellite imagery using Python. By leveraging the sentinelsat library and the Copernicus Open Access Hub API, you can access a wealth of free and open satellite data for a wide range of remote sensing and geospatial

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