Remote Sensing Deployable Analysis environmenT

Earth Observation (EO) data has become too large to be downloaded and analyzed on local desktop infrastructures, and even on many local cluster solutions. Although most of the data is freely available, a range of difficulties still hamper achievable benefit, not only for scientists, but also for citizens, industry and society.

In this project, we developed RS-DAT: an environment for exploration and analysis of Remote Sensing (RS) data. The environment provides scientists with tools to access and analyse RS data, enabling them to use the massive storage and infrastructure offered by SURF. We identified eScience projects that address modern EO questions where access to large RS data is crucial, as is efficient data handling. These projects served as use cases to provide us with insight into the common needs of the EO community and acting as drivers to create generic tools to address these needs, with specific focus on data access, retrieval and storage, analysis at scale, and ML supported analysis and exploitation.

This page covers two projects: RS-DAT, funded by the Netherlands eScience Center and SUFR Alliance call 2020 and the project SSP 2023 eRS-DAT funded by the Netherlands eScience Center.