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Overview🔗

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Key Characteristics🔗

Attribute Value
Sensor / Mission e.g. Sentinel-2 MSI / ESA Copernicus
Platform e.g. Sentinel-2A & 2B (twin constellation)
Processing level e.g. Level-2A (Surface Reflectance)
Spatial resolution e.g. 10 m / 20 m / 60 m (band-dependent)
Revisit time e.g. 5 days (global, at equator)
Temporal coverage e.g. June 2015 – present
Spatial coverage e.g. Global land surface
File format e.g. Cloud-Optimized GeoTIFF (COG)
Projection / CRS e.g. UTM (EPSG:326xx / 327xx), WGS84
Update frequency e.g. Daily, within 6 h of acquisition
License e.g. Copernicus Open Access (CC BY-SA 3.0)

Spectral Bands🔗

Band Name Central Wavelength Bandwidth Resolution Notes
B01 Coastal Aerosol 443 nm 20 nm 60 m Atmospheric correction
B02 Blue 490 nm 65 nm 10 m ★ RGB composite
B03 Green 560 nm 35 nm 10 m ★ RGB composite
B04 Red 665 nm 30 nm 10 m ★ RGB composite / NDVI
B08 NIR 842 nm 115 nm 10 m ★ Vegetation indices
B8A Narrow NIR 865 nm 20 nm 20 m Red-edge vegetation
B11 SWIR-1 1610 nm 90 nm 20 m Moisture / burn scars
B12 SWIR-2 2190 nm 180 nm 20 m Bare soil discrimination
... ... ... ... ... ...

Data Layers🔗

Layer Name Data Type Value Range No-data Description
1 Surface Reflectance Int16 0 – 10 000 -9999 Bottom-of-atmosphere reflectance, scaled × 10 000
2 SCL (Scene Class) UInt8 0 – 11 0 Per-pixel land/cloud/shadow classification
3 ... ... ... ... ...

Processing & Methodology🔗

Processing levels🔗

Level Description Provided by EDS
Level-1C Top-of-atmosphere reflectance, orthorectified ✗
Level-2A Bottom-of-atmosphere reflectance (Sen2Cor / LaSRC) ✓
ARD Analysis-Ready Data with harmonized CRS and tiling ✓

Algorithm🔗

Briefly describe the atmospheric correction, calibration, or classification algorithm. Link to the relevant scientific publication or ATBD (Algorithm Theoretical Basis Document).

Reference: Author et al. (Year). Title of the paper or technical note. Journal/Agency. [DOI or URL]

Quality & Accuracy🔗

Known limitations🔗

  • Cloud contamination: pixels covered by cloud or shadow are flagged in the SCL layer and should be masked prior to analysis.
  • BRDF effects: surface reflectance values vary with sun-sensor geometry, particularly at high latitudes and on steep terrain.
  • Saturation: bright surfaces (snow, salt pans) may saturate in the VNIR bands.

Validation🔗

Metric Value Reference
Absolute reflectance accuracy ±3 % ESA Sentinel-2 Validation Report (2023)
Geolocation accuracy < 12.5 m ESA MPC QA Report
Cloud mask accuracy ~95 % Zupanc (2021)

Metadata Fields🔗

Field Type Range / Values Description
datetime string ISO 8601 Scene acquisition UTC timestamp
platform string sentinel-2a, sentinel-2b Satellite identifier
eo:cloud_cover float 0 – 100 Percentage of scene covered by cloud
s2:mgrs_tile string e.g. 33UUP MGRS grid tile identifier
s2:processing_baseline string e.g. 05.00 ESA processing baseline version
s2:nodata_pixel_percentage float 0 – 100 Percentage of pixels outside the swath footprint
view:sun_azimuth float 0 – 360 ° Sun azimuth angle at scene centre
view:sun_elevation float 0 – 90 ° Sun elevation angle at scene centre

Tiling & Delivery🔗

  • Tiling scheme: MGRS 100 × 100 km tiles (e.g. 33UUP), or EDS internal grid (link to grid spec).
  • Delivery format: Cloud-Optimized GeoTIFF (COG) with internal overviews.
  • Archive structure: s3://eds-collections/<collection-id>/<year>/<month>/<day>/<tile>/
  • Compression: LZW / Deflate, predictor 2.
  • STAC Catalog endpoint: https://stac.eds.earthdaily.com/collections/<collection-id>

API Access🔗

Quick start — Python🔗

import earthdaily

client = earthdaily.EarthDataStore()

items = client.search(
    collections=["<collection-id>"],
    datetime="2024-06-01/2024-06-30",
    bbox=[-95.5, 42.0, -93.5, 44.0],   # [west, south, east, north]
    query={"eo:cloud_cover": {"lt": 20}},
)

# Load first item as an xarray DataArray
da = items[0].assets["B04"].open()

STAC example🔗

curl -X GET "https://stac.eds.earthdaily.com/collections/<collection-id>/items" \
  -H "Authorization: Bearer $EDS_TOKEN" \
  -G \
  --data-urlencode "bbox=-95.5,42.0,-93.5,44.0" \
  --data-urlencode "datetime=2024-06-01/2024-06-30" \
  --data-urlencode "limit=10"

Archive Availability🔗

This collection is available globally from to present (or if discontinued).

Regional availability

Higher temporal density (daily revisit) is available over specific agricultural priority regions from . Contact your EDS account representative for the regional coverage map.

Processing baseline change

Scene products generated before were produced with processing baseline vX.Y and may exhibit radiometric offsets relative to more recent acquisitions. Apply the published offset correction before combining data across this boundary.

Collection Relationship Link
<collection-id-2> Higher-resolution companion (5 m) → Documentation
<collection-id-3> SAR complement for cloud-penetrating observations → Documentation
<analytic-name> Derived analytic built on this collection → Documentation

Use Cases🔗

This collection is used in the following EDS products and analytics:

  • — brief explanation of how this collection feeds the product.
  • — brief explanation.

Example applications🔗

  • Crop monitoring and phenology tracking using time-series NDVI derived from red and NIR bands.
  • Post-disaster damage assessment combining SWIR bands before/after the event.
  • Land-use / land-cover classification at national scale.

License & Citation🔗

License:

How to cite:

<Agency/Provider> (<Year>). <Collection full name> [Data set]. 
EarthDaily Analytics EDS Platform. https://eds.earthdaily.com/collections/<collection-id>. 
Accessed <DATE>.

References🔗

  • Author, A., & Author, B. (Year). Title of paper. Journal Name, Vol(Issue), pp–pp. https://doi.org/xxx
  • Agency (Year). Algorithm Theoretical Basis Document (ATBD) for . Technical Report ESA-EOP-SD/1667. [URL]
  • Agency (Year). User Guide. [URL]