CEOS Data Cube Platform version 2 (CEOS2)

Maestro The Australian Water Detection from Space (WOFS) algorithm was applied to Data Cubes over Lake Baringo, Kenya (left) and the Meta River in Colombia (right). These time-series pixel stacks are used to identify surface water to assess drought and flood extremes. The results show the percent of observations detected as water over the entire 11+ year time series. The CEOS Data Cube architecture allows significant improvements in computation time compared to typical scene-based approaches.

The Committee on Earth Observation Satellites (CEOS) has long recognized a need for data processing infrastructure to support Earth science objectives in developing countries. Forest preservation initiatives, carbon measurement initiatives, water management and agricultural monitoring are just few examples of causes that can benefit greatly from remote sensing data. Currently, however, many developing nations lack the in-country expertise and computational infrastructure to utilize remote sensing data.

The CEOS Data Cube Platform version 2 (CEOS2) provides a flexible model to address these needs. The CEOS Data Cube Platform is a data processing platform for Earth science data, with a focus on remote-sensing data. The platform provides a data ingestion framework that includes support for automated ingestion of a wide variety of remote sensing data products. The data products are ingested into an N-dimensional data array that abstracts away management of distinct acquisitions. The platform has a tiered API for data processing and a data/application platform layer for higher-level access.

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