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Cloud Cover Assessment Validation Datasets

By Landsat Missions

Landsat Cloud Cover Assessment (CCA) validation datasets are comprised of satellite imagery and accompanying cloud truth masks that specify which Landsat pixels in a scene are cloudy or clear, or have other conditions such as cloud shadow.

Landsat 9 Collection 2

Cloudscape in a BLM wilderness study area.

A cloud validation dataset created using Landsat 9 Collection 2 data. (November 2023)

Access Landsat 9 Cloud Clover Assessment

Landsat 8 Collection 2

Clouds rolling through the mountaintops at Olympic National Park.

A cloud validation dataset created using Landsat 8 Collection 2 data. (September 2021)

Access Landsat 8 Cloud Clover Assessment

Landsat 7 Collection 2

ISB Cloud image.

A cloud validation dataset created using Landsat 7 Collection 2 data. (July 2022)

Access Landsat 7 Cloud Clover Assessment

The cloud truth masks were created manually by operators digitizing clouds by hand using image-editing software.  These cloud truth masks are essential for validating existing CCA algorithms and can also be used to train new cloud detection algorithms. 

Information about the C Function of Mask (CFMask) Algorithm 

Historical cloud truth masks are listed below. 

 

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Clouds are a pervasive and unavoidable issue in satellite-borne optical imagery. Accurate, well-documented, and automated cloud detection algorithms are necessary to effectively leverage large collections of remotely sensed data. The Landsat project is uniquely suited for comparative validation of cloud assessment algorithms because the modular architecture of the Landsat ground system allows for
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