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Calibration and Pre-processing of a Multi-decadal AVHRR Time Series

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Book cover Remote Sensing Time Series

Part of the book series: Remote Sensing and Digital Image Processing ((RDIP,volume 22))

Abstract

Since the early 1980s, the German Remote Sensing Data Centre (DFD) of the German Aerospace Centre (DLR) has received archived and processed Advanced Very High Resolution Radiometer (AVHRR) data from the Polar Orbiting Environmental Satellites (POES) of the National Oceanic and Atmospheric Administration (NOAA). By December 2013, over 237,000 paths over Europe have since been archived at DLR. Based on these High Resolution Picture Transmission (HRPT) raw datasets, an operational pre-processing and value-adding chain has been developed (Dech et al., Aerosp Sci Technol 2(5):335–346, 1998; Tungalagsaikhan et al., Proc. 23th DGPF (12), 2003). In this chapter, the series of AVHRR sensors is introduced, and information on calibration and system correction procedures is given. Next, the pre-processing part of DLR’s processing chain is described, where focus is set on the calibration aspects. Time series examples are provided to show the influence of changes in calibration over time, and to illustrate the need for consistent pre-processing and data harmonization. According to these requirements DLR’s multi-decadal archive of AVHRR data will be re-processed in the frame of the TIMELINE project, providing consistent and well-calibrated time series data.

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Acknowledgements

The authors would like to thank the anonymous reviewers for their valuable comments on the manuscript. Dr. Derek Rogge is acknowledged for improving the language and structure of this chapter. Also Dr. Claudia Künzer, Dr. Corinne Frey and Dr. Kurt Günther are acknowledged for helpful comments on the text.

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Correspondence to Martin Bachmann .

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Bachmann, M., Tungalagsaikhan, P., Ruppert, T., Dech, S. (2015). Calibration and Pre-processing of a Multi-decadal AVHRR Time Series. In: Kuenzer, C., Dech, S., Wagner, W. (eds) Remote Sensing Time Series. Remote Sensing and Digital Image Processing, vol 22. Springer, Cham. https://doi.org/10.1007/978-3-319-15967-6_3

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