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Design and Implementation of Data Usability Processor into an Automated Processing Chain for Optical Remote Sensing Data

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Book cover Leveraging Applications of Formal Methods, Verification, and Validation (ISoLA 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 683))

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Abstract

Diverse anthropogenic impacts will trigger worldwide environmental and social problems as e.g. climate change or social transformation processes. To observe these processes current information about status, direction of development and spatial or temporal dynamics of the processes are required. As the demand for current environmental information is increasing, earth observation (EO) and remote sensing (RS) techniques are moving to the focus of interest.

Generation and dissemination of RS based information products for e.g. time-critical applications can only be guaranteed by state-of-the-art concepts for data processing. This can be realized either by cumbersome and thus expensive interactive processing or by setting-up development and implementation of automated data processing infrastructure. In both cases information about data quality is important for the pre-processing and value adding processing steps. This contribution is focussed on a processor for automated data usability assessment which can be integrated into an automated processing chain adding information valuable for the user.

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Notes

  1. 1.

    Cloud Cover Degree: Ratio of cloud pixels to total pixels of an unit (e.g. complete scene or quadrant of a scene).

  2. 2.

    Data usability: Combination of cloud cover and cloud distribution as well as data errors.

  3. 3.

    Quick-look data are preview images derived from original remote sensing data.

  4. 4.

    Metadata describe remote sensing data (e.g. satellite mission, orbit, track, frame).

  5. 5.

    LANDSAT-7/ETM + data receiving were stopped at the end of 2003 [7].

  6. 6.

    Meta-information: Contain further information on remote sensing data (e.g. satellite mission, orbit, track, frame number, etc.).

  7. 7.

    Assessment unit: scene, quadrant.

  8. 8.

    It has been shown that a threshold value of 10 is optimal because single zero-pixels are often caused by JPEG compression and were no data problem.

  9. 9.

    LANDSAT-handbook: chapter 9.2.4, Table 9.2 ETM+ Thermal Constants.

  10. 10.

    LANDSAT-handbook: chapter 9.2.4, Table 9.2 ETM+ Thermal Constants.

  11. 11.

    The term Satellite Projection as it is used here is no projection in real sense of the word. A LANDSAT data track is resulting of sequential lines along the satellite path. Each line is a central projection from the satellite position.

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Acknowledgement

The authors thank Dr. Berutti, Dr. Pitella, Dr. Biasutti (all European Space Agency) for the provided test data, for the constructive discussions, and the shown interest in our investigations. The authors wish to thanks E. Schwarz from the German Remote Date Center, Department of National Ground Segment Neustrelitz for his activities for determination of the actual equator crossing time.

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Authors and Affiliations

  1. German Aerospace Center, German Remote Sensing Data Center, Kalkhorstweg 53, 17235, Neustrelitz, Germany

    Erik Borg & Bernd Fichtelmann

  2. German Aerospace Center, German Remote Sensing Data Center, Münchner Str. 20, 82234, Wessling, Germany

    Christian Fischer

  3. Department of Geography, University of Potsdam, Karl-Liebknecht-Strasse 24/25, 14476, Potsdam, Germany

    Hartmut Asche

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  1. Erik Borg
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Correspondence to Bernd Fichtelmann .

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Editors and Affiliations

  1. Lero - Irish Software Research Center, University of Limerick, Limerick, Ireland

    Anna-Lena Lamprecht

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Borg, E., Fichtelmann, B., Fischer, C., Asche, H. (2016). Design and Implementation of Data Usability Processor into an Automated Processing Chain for Optical Remote Sensing Data. In: Lamprecht, AL. (eds) Leveraging Applications of Formal Methods, Verification, and Validation . ISoLA 2016. Communications in Computer and Information Science, vol 683. Springer, Cham. https://doi.org/10.1007/978-3-319-51641-7_2

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  • DOI: https://doi.org/10.1007/978-3-319-51641-7_2

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