CBERS on AWS

earth observation gis imaging satellite imagery sustainability disaster response

Description

This project creates a S3 repository with imagery acquired by the China-Brazil Earth Resources Satellite (CBERS). The image files are recorded and processed by Instituto Nacional de Pesquisa Espaciais (INPE) and are converted to Cloud Optimized Geotiff format in order to optimize its use for cloud based applications. The repository contains all CBERS-4 MUX, AWFI, PAN5M and PAN10M scenes acquired since the start of the satellite mission and is daily updated with new scenes.

Update Frequency

Daily

License

https://creativecommons.org/licenses/by-sa/3.0/

Documentation

https://github.com/fredliporace/cbers-on-aws

Contact

https://lists.osgeo.org/mailman/listinfo/cbers-pds

Usage Examples

Resources on AWS

  • Description
    CBERS imagery (COG files, Requester Pays Bucket)
    Resource type
    S3 Bucket
    Amazon Resource Name (ARN)
    arn:aws:s3:::cbers-pds
    AWS Region
    us-east-1
  • Description
    CBERS metadata (Quicklooks, metadata)
    Resource type
    S3 Bucket
    Amazon Resource Name (ARN)
    arn:aws:s3:::cbers-meta-pds
    AWS Region
    us-east-1
  • Description
    Notifications for new MUX quicklooks
    Resource type
    SNS Topic
    Amazon Resource Name (ARN)
    arn:aws:sns:us-east-1:599544552497:NewCB4MUXQuicklook
    AWS Region
    us-east-1
  • Description
    Notifications for new AWFI quicklooks
    Resource type
    SNS Topic
    Amazon Resource Name (ARN)
    arn:aws:sns:us-east-1:599544552497:NewCB4AWFIQuicklook
    AWS Region
    us-east-1
  • Description
    Notifications for new PAN10M quicklooks
    Resource type
    SNS Topic
    Amazon Resource Name (ARN)
    arn:aws:sns:us-east-1:599544552497:NewCB4PAN10MQuicklook
    AWS Region
    us-east-1
  • Description
    Notifications for new PAN5M quicklooks
    Resource type
    SNS Topic
    Amazon Resource Name (ARN)
    arn:aws:sns:us-east-1:599544552497:NewCB4PAN5MQuicklook
    AWS Region
    us-east-1

Edit this dataset entry on GitHub

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