DLR - Earth Observation Center

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Technology

The increasing number of earth observation satellites produces more and more high resolution data records. Thus an exponentially increasing amount of data has to be automatically received, processed and made accessible to users. The Earth Observation Center (EOC) addresses this IT challenge with its concept of an integrated multimission payload ground segment. The components being built-up for the ground segment are coupled and build on each other. The processing chain starts with the acquisition and archiving of raw data. The next step is the operational production of value added products by means of processors. The output products are finally evaluated for various applications by means of image analysis software and visualized as thematic maps or video animations.

Spectrometry

The IMF spectrometric reference lab makes substantial contributions to databases for monitoring atmospheric trace gases. Due to the high number of spectral bands and ambitious accuracy requirements, this task is particularly challenging in the domain of atmospheric sounding. Preconditions are both precise understanding of the measuring equipment and constant monitoring of the instrument’s characteristics over the entire mission duration. The know-how obtained here benefits the conception and operation of hyper-spectrometers such as HySpex, ROSIS or EnMap.

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Data Management and Data Access

Processing remote sensing data is a continuous task which exceeds the lifetime of a satellite mission. The registered data sets have to be safely archived and made accessible for long-term use since their value increases as time progresses, particularly in the domain of environmental monitoring. Safeguarding and migration have to be assured for both data and storage systems. Near-real-time applications, such as disaster monitoring, require instantaneous access to the incoming raw data stream and the derived value-added products. The combination of operational long-term functionality and the flexibility to produce value-added data products and services is an engineering challenge for the management of earth observation data.

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Modeling and retrieval

Earth observation satellites planned for climate research and weather observation measure physical parameters like temperature, radiation density, humidity, and optical thickness, as well as chemical variables such as ozone density or the concentration of trace gases in the atmosphere. In order to perform adequate measurements and assessments, detailed knowledge of the underlying physical and chemical processes is essential. This knowledge is incorporated in mathematical models, which can be optimized after their results are compared with actual measurements.

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Data Processors

The term “operational processors” refers to software-packages that continuously and in near-real-time generate well-defined (calibrated and validated) products from data records. Processors have to work largely without interactive intervention. In the context of ESA and EUMETSAT missions, EOC is in charge of the processor development for the ERS/GOME, ENVISAT/ SCIAMACHY and MetOp/GOME-2 spectrometers. This task comprises constant improvement of the algorithms and reprocessing of time-series for entire missions. The lidar mission ADM-Aeolus, dedicated to the derivation of global wind parameters, poses new challenges. In microwave remote sensing the focus is on generating terrain-corrected data and digital elevation models using radar interferometry. A new field of application is traffic monitoring in real-time. Processors are also used to routinely produce thematic maps, showing, for example, sea surface temperatures, vegetation indices, and suspended matter in water bodies, or for use in vulnerability assessments and fire detection.

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Image processing

Remote sensing of the earth is primarily based on digital raster data recorded by imaging optical or radar sensors. Next to traditional image processing which focuses on geocoding and thematic classification, other advanced technologies are gaining in importance. Among those are three-dimensional processing (radar-interferometry, stereoscopy, integration of digital elevation models), visualization of data by video animation or modeling, and content-based data retrieval (data mining) in large data repositories.

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