Abstract
Abstract. Earth Observation (EO) remote sensing missions are producing an increasing volume of data due to higher spatial and spectral resolutions, and higher frequency of acquisitions. Thus, in order to prepare the future of image processing pipelines, CNES has carried out Research & Development studies related to the use of Big Data and Cloud technologies for image processing chains made. Since mid-2019, CNES in partnership with Airbus Defense & Space, has started a new High Resolution Optical EO mission dedicated to very high resolution 3D observation called CO3D (“Constellation Optique 3D”). To achieve those objectives, a new image processing pipeline prototype is being developed taking in consideration the lessons learned from the previous studies. The paper will introduce this new image processing pipeline, the processing paradigms used to take advantage of big data technologies and the results of production benchmarks at a large scale. The on-going works to optimize the processing pipeline and Cloud cluster will be also discussed.
Highlights
New Earth Observation (EO) remote sensing missions are dramatically increasing the volume of produced data due to higher resolutions and higher frequency of acquisitions, whereas architectures and technical solutions for ground processing designed in the 2000’s are reaching their limits in terms of computing scalability, data reading/writing speeds, etc
In order to prepare the future of image processing pipelines, CNES has carried out Research & Development studies related to the use of Big Data and Cloud technologies for image processing chains made
Since mid-2019, CNES in partnership with Airbus Defense & Space, has started a new High Resolution Optical EO mission dedicated to very high resolution 3D observation called CO3D (“Constellation Optique 3D”)
Summary
New Earth Observation (EO) remote sensing missions are dramatically increasing the volume of produced data due to higher resolutions and higher frequency of acquisitions, whereas architectures and technical solutions for ground processing designed in the 2000’s are reaching their limits in terms of computing scalability, data reading/writing speeds, etc. In order to prepare the future of image processing pipelines, CNES has carried out Research & Development studies related to the use of Big Data and Cloud technologies for image processing chains made In this context, a Proof Of Concept (POC) was developed in order to explore the ability of massive image production regarding the flexibility, scalability and economic benefits in an environment similar to an operational image processing center (Melet et al 2019). One of the goals of the mission is to generate worldwide, accurate, low cost Digital Surface Model (DSM) within a short time window (launch in mid-2023, disposal of the DSM in 2025) To achieve those objectives, a new image processing pipeline prototype is being developed taking in consideration the lessons learned from the POC.
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