🌍 Sentinel data at CEDA user guide
Sentinel data—part of the EU Copernicus Earth Observation programme—is one of the richest open datasets available for environmental monitoring. CEDA (the Centre for Environmental Data Analysis) provides UK‑hosted access to a large archive of this data, along with tools and services to help you work with it efficiently.
This guide walks you through everything from discovering Sentinel products to downloading, processing, and using them in your workflows.
📦 1. Understanding What Sentinel Data Is
CEDA hosts data from several Sentinel missions. Each mission has a different purpose:
| Sentinel Mission | What It Measures | Typical Uses |
|---|---|---|
| Sentinel‑1 | Radar (SAR) | Flood mapping, land deformation, sea ice |
| Sentinel‑2 | Multispectral optical imagery | Land cover, vegetation, agriculture |
| Sentinel‑3 | Ocean & land monitoring | SST, ocean colour, altimetry |
| Sentinel‑5P | Atmospheric composition | NO₂, SO₂, aerosols |
Knowing which mission you need is the first step.
đź“Š Sentinel Products & CEDA Archive Policy
| Product | Coverage | Archive Policy |
|---|---|---|
| Sentinel‑1 IW SLC | Global | 4‑month rolling archive |
| Sentinel‑2 L1 MSI | UK and Crown Dependencies | Full archive for this region |
| Sentinel‑3 SLSTR | Global | 3‑year archive |
| Sentinel‑3 OLCI | Global | 1‑year rolling archive |
| Sentinel‑5P (Level 1) | Global | Rolling archive (duration not specified) |
| Sentinel‑1 & Sentinel‑2 ARD (Defra & JNCC) | England, Scotland & Northern Ireland | Full archive of all processed ARD |
🔎 2. Finding Sentinel Data in CEDA
CEDA offers different methods to search this data:
A. CEDA Data Catalogue
You can use the data catalogue to view the metadata, dataset descriptions, file structure, and download options.
- Search Term: Search for "Sentinel" or specific products like "Sentinel-2 ARD".
- Results: This will provide links to the data browser, documentation, and information about data access restrictions (some data may require user registration).
B. CEDA Archive Directory Browser
This provides a tree like view of the archive. If you know the file path, the archive directory browser provides direct file access.
- Location: Navigate through
neodc->sentinel
C. CEDA Satellite Data Finder
The Satellite Data Finder is the primary, visual tool for finding Sentinel data (1, 2, and 3) by area and time.
- Method: Use the map to pan to your location of interest and draw a box to define your study area.
- Filters: Utilize the left-hand menu to filter by specific Sentinel missions (S1, S2, S3), date range, and instrument modes.
- Limitations: The tool displays a maximum of 1000 results on the map to prevent overcrowding.
D. CEDA STAC API
- Programmatic access for automation.
- Ideal for bulk downloads or reproducible workflows.
- For Sentinel 1 SLC and ARD and Sentinel 2 ARD.
đź“Ą 3. Accessing and Downloading Data
CEDA supports several download methods:
A. Direct HTTP/HTTPS Download
- Simple and reliable.
- Best for occasional or small downloads.
B. wget or curl
Use when you want to script downloads:
wget -r -np -nH --cut-dirs=5 https://data.ceda.ac.uk/neodc/sentinel2/data/...
C. CEDA Download API
- Allows authenticated, resumable downloads.
- Good for large datasets.
D. JASMIN Integration (if you have access)
- Access data in place without downloading.
- Ideal for heavy processing or large-scale analysis.
🗂️ 4. Understanding Sentinel File Structure
Sentinel products follow a consistent naming pattern. For example:
S2A_MSIL2A_20230715T112121_N0509_R037_T30UXC_20230715T150123.SAFE
Key components include:
- Mission (S1, S2, etc.)
- Processing level (L1C, L2A)
- Acquisition date/time
- Tile ID (for Sentinel‑2)
- SAFE container (directory with metadata + imagery)
Inside each SAFE file you’ll find:
- Granules
- Metadata XML
- Measurement bands
- Quality masks
🛠️ 5. Working with Sentinel Data
A. Tools for Sentinel‑2
- SNAP (ESA’s toolbox)
- GDAL
- QGIS
- Python libraries:
rasterio,sentinelhub,xarray
B. Tools for Sentinel‑1
- SNAP Toolbox (and it's associated software e.g. GraphBuilder)
C. Tools for Sentinel‑3 & 5P
- SNAP OLCI/SLSTR/TROPOMI modules
- xarray + netCDF4
🧠6. Typical Workflow Example (Sentinel‑2)
Step 1: Search for a tile
Use the CEDA catalogue to find a tile covering your area of interest.
Step 2: Download the L2A product
L2A includes surface reflectance—ideal for analysis.
Step 3: Open in SNAP or Python
Example in Python:
import rasterio import matplotlib.pyplot as plt with rasterio.open("T30UXC_20230715T112121_B04.jp2") as red: red_band = red.read(1) plt.imshow(red_band, cmap='gray') plt.title("Sentinel-2 Red Band") plt.show()
Step 4: Apply corrections or indices
Compute NDVI:
NDVI = NIR - Red / NIR + Red
Step 5: Export or visualise results
Use QGIS, Python, or cloud tools.
🧩 7. Tips for Efficient Use
- Use JASMIN if you’re processing large volumes—no need to download.
- Check cloud cover metadata before downloading Sentinel‑2 scenes.
- Automate with Python if you need regular updates.
- Be aware of data latency—some missions have a delay before data appears in the archive.
đź“š 8. Additional Resources
- SNAP Help Documentation
- Scriptable metadata about satellite scenes for Sentinal 1, 2 and 3 and Sentinel ARD elasticsearch and the ceda-eo index