Sentinel-2 is a satellite program operated by the European Space Agency (ESA) that consists of a pair of Earth observation satellites. These satellites provide high-resolution imagery ranging from 10 to 60 meters, which supports the monitoring of vegetation, detection of wildfires, and analysis of land cover changes.
Sentinel-2 data are widely used in fields such as agriculture, environmental monitoring, urban planning, and disaster response. The images are freely available and can be accessed through the Copernicus Open Access Hub.
How to Download Sentinel-2 Images
To acquire Sentinel-2 imagery, follow the steps outlined below:
- Visit the official Copernicus Open Access Hub: https://browser.dataspace.copernicus.eu
- Register for an account or log in with an existing user profile.
- Navigate to the region of interest on the map. For example, for a project in Loja, Ecuador, use the available tools to draw a polygon that defines the study area.
- In the “VISUALIZE” tab, click the icon to the right of “DATE: SINGLE” to open the time selection panel. Then select “Time Range” to define the date range for the imagery search.
- Specify the maximum allowable cloud cover percentage under the “Max. cloud coverage” field to filter images by clarity.
- Define the image collection type. By default, Sentinel-2 L2A is selected, but Sentinel-2 L1C may also be used based on the project’s requirements.
- Click “Find products within selected time range” to generate the list of available scenes.
- A list of matching products will be displayed. Click the “Zoom to Product” icon beneath each thumbnail to preview the selected image.
- To download the image, click on the “Download product” icon below the image preview.
- If the study area spans across multiple image tiles, each one must be downloaded individually. After downloading, extract the compressed files before proceeding with analysis.
Spectral Bands of the Sentinel-2 Satellite.
It is recommended to verify available disk space before starting the download, as satellite imagery files can be large. Using an external hard drive may be helpful when working with extensive datasets.