🛰️ SAT-DISCOVERY

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📦 Data Delivery & Format Selection

Understanding satellite data formats and delivery options

Important Notice

This page provides reference information about common satellite data formats and delivery methods. SAT-DISCOVERY does not provide data delivery services. All data access must be obtained through the respective satellite operators and data providers.

Common Data Formats

GeoTIFF
Georeferenced Raster

Standard format for georeferenced raster imagery. Includes spatial reference and coordinate information.

Extension:
.tif, .tiff
Use Case:
Most common format
Applications:
GIS, Remote Sensing
Widely Supported
HDF / NetCDF
Scientific Data Format

Hierarchical data formats used for scientific datasets with multiple variables and metadata.

Extension:
.hdf, .h5, .nc
Use Case:
Multi-band, time-series
Applications:
Scientific analysis
Sentinel Data
COG (Cloud Optimized GeoTIFF)
Cloud-Native Format

GeoTIFF optimized for cloud storage and streaming access without downloading entire files.

Extension:
.tif
Use Case:
Cloud-based access
Applications:
Web mapping, APIs
Modern Standard
JPEG 2000
Compressed Imagery

Advanced compression format providing lossless or lossy compression for large imagery datasets.

Extension:
.jp2, .j2k
Use Case:
Large files, compression
Applications:
Archival, distribution
Sentinel-2
SAFE Format
Sentinel Product Format

Standard Archive Format for Europe - used by Sentinel missions with XML metadata and imagery.

Extension:
.SAFE (folder)
Use Case:
Sentinel data
Applications:
ESA missions
ESA Standard
STAC (SpatioTemporal Asset Catalog)
Metadata Standard

JSON-based metadata standard for describing geospatial data and enabling discovery.

Extension:
.json
Use Case:
Data discovery, catalog
Applications:
APIs, search
Industry Standard

Delivery Methods

Direct Download

Download complete data products directly from provider portals via HTTP/FTP.

Pros: Simple, full control
Cons: Large file sizes, storage needed
API Access

Programmatic access via REST APIs (STAC, OGC services) for automated workflows.

Pros: Automated, scalable
Cons: Requires programming
Cloud Storage

Access data directly in cloud storage (AWS, Azure, Google Cloud) without downloading.

Pros: No download, fast processing
Cons: Cloud platform required
Streaming Services

Stream imagery tiles via WMS, WMTS, or XYZ services for visualization.

Pros: No download, web-ready
Cons: Limited analysis capability
Processing Levels

Satellite data is typically available at different processing levels:

Level 0:
Raw sensor data
Level 1:
Radiometrically corrected
Level 2:
Geometrically corrected, georeferenced
Level 3:
Mosaicked, analysis-ready

Most users work with Level 1 or Level 2 products, which are georeferenced and suitable for analysis.