Electro-Optical Imagery on AWS

Publication date: May 13, 2021 (Diagram history)

This diagram demonstrates how to extract, process, and store electro-optical satellite imagery by using AWS.

Electro-Optical Imagery on AWS Diagram 1

1. Demodulate and decode: Extract baseband waveform from modulated carrier; remove forward error correction.

2. Convert into raw sensor data: Decommutate signal frames; decrypt data.

3. Process raw images and perform QA review.

   • QA review: Confirm Images are sufficient for processing.

   • AWS Batch: Run multiple jobs in parallel.

     • AWS Fargate and AWS Lambda:

     • Sensor correction: Apply corrections for optical distortions.

     • Orthorectify: Sensor perspective.

     • Georeference: Apply image to spatial grid and assign known coordinate system.

     • Generate thumbnails: Create post-processed thumbnails for customer purchase.

4. Store metadata: Store information on latitude/longitude collection, Region collection, time and date of retrieval.

5. Storage: Store preprocessed images in a variety of Amazon Simple Storage Service (Amazon S3) services by balancing cost savings and time of retrieval

6. Post processing and analysis: Complete imagery processing.

   • Feature extraction: Identify features in images (such as ships).

   • Naming/tagging of features: Tag features by name or identification system.

   • Time series creation: Tag images to sort by time.

7. Storage and dissemination: Final storage of images and analytics for end customer.

8. Customer delivery: Deliver final images to end customers.

Electro-Optical Imagery on AWS Diagram 2: Classified Processing

1. Demodulate and decode: Extract baseband waveform from modulated carrier; remove forward error correction.

2. Convert into raw sensor data: Decommutate signal frames; decrypt data.

3. Immutable transaction log: Cryptographically establish provenance and fidelity.

4. Optional classified processing: Throughout the image processing, move data to the appropriate regions for classified processing.

5. Process raw images: Process raw images and perform QA review:

   • QA Review: Confirm Images are sufficient for processing

   • AWS Batch: Run multiple jobs in parallel.

   • AWS Fargate and AWS Lambda:

     • Sensor correction: Apply corrections for optical distortions.

     • Orthorectify: Sensor perspective.

     • Georeference: Apply image to spatial grid and assign known coordinate system.

     • Generate thumbnails: Create post-processed thumbnails for customer purchase.

6. Store metadata: Store information on latitude/longitude collection, Region collection, time, and date of retrieval.

7. Storage: Store preprocessed images in a variety of Amazon S3 services by balancing cost savings and time of retrieval.

8. Post processing and analysis: Complete imagery processing.

   • Feature extraction: Identify features in images (such as ships).

   • Naming/tagging of features: Tag features by name/identification system.

   • Time seriesc reation: Tag images to sort by time.

9. Storage and dissemination: Final storage of images and analytics for end customer.

10. Customer delivery: Deliver final images to end customers.

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Change	Description	Date
Initial publication	Reference architecture diagram first published.	May 13, 2021

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