computer vision deep learning earth observation geospatial labeled machine learning satellite imagery


RarePlanes is a unique open-source machine learning dataset from CosmiQ Works and AI.Reverie that incorporates both real and synthetically generated satellite imagery. The RarePlanes dataset specifically focuses on the value of AI.Reverie synthetic data to aid computer vision algorithms in their ability to automatically detect aircraft and their attributes in satellite imagery. Although other synthetic/real combination datasets exist, RarePlanes is the largest openly-available very high resolution dataset built to test the value of synthetic data from an overhead perspective. The real portion of the dataset consists of 253 Maxar WorldView-3 satellite scenes spanning 112 locations and 2,142 km^2 with 14,700 hand-annotated aircraft. The accompanying synthetic dataset is generated via AI.Reverie’s novel simulation platform and features 50,000 synthetic satellite images with ~630,000 aircraft annotations.

Update Frequency

None Planned


CC BY-SA 4.0



Managed By

In-Q-Tel - CosmiQ Works

See all datasets managed by In-Q-Tel - CosmiQ Works.


jss5102@gmail.com and avanetten@iqt.org

Usage Examples

Tools & Applications

Resources on AWS

  • Description
    Real and synthetic satellite imagery, annotations, and metadata
    Resource type
    S3 Bucket
    Amazon Resource Name (ARN)
    AWS Region
    AWS CLI Access (No AWS account required)
    aws s3 ls s3://rareplanes-public/ --no-sign-request

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