Contrail Detection in Satellite Images

  • Hermann Mannstein
  • Margarita Vázquez-Navarro
  • Kaspar Graf
  • David P. Duda
  • Ulrich Schumann
Chapter
Part of the Research Topics in Aerospace book series (RTA)

Abstract

Methods for detecting linear contrail pixels in satellite infrared images are described. An objective contrail detection algorithm has been developed and extensively applied to data from various polar and geostationary satellite sensors. The method uses the contrast in brightness temperatures near 11 and 12 μm wavelengths and detects linear contrails using image processing techniques. The paper discusses the development of the algorithms, detection efficiency, false alarm rate, some of the results, and their validation. The contrail detection algorithm detects only a fraction of all contrail cirrus. Progress is expected from combining spatiotemporal satellite data in correlation with traffic and meteorological data.

Keywords

False Alarm Rate Advanced Very High Resolution Radiometer Advanced Very High Resolution Radiometer Cirrus Cloud Brightness Temperature Difference 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Bakan, S., Betancor, M., Gayler, V., Grassl, H.: Contrail frequency over Europe from NOAA satellite images. Ann. Geophysicae 12, 962–968 (1994)ADSGoogle Scholar
  2. Graf, K., Mannstein, H., Mayer, B., Schumann, U.: Some evidence of aviation fingerprint in diurnal cycle of cirrus over the North Atlantic. In: Proceedings of the 2nd International Conference on Transport, Atmosphere and Climate (TAC-2), pp. 180–185. DLR-FB 2010-10, ISSN 1434-8454, Aachen, 22–25 June 2009Google Scholar
  3. Joseph, J.H., Levin, Z., Mekler, Y., Ohring, G., Otterman, J.: Study of contrails observed from ERTS I satellite imagery. J. Geophys. Res. 80, 366–372 (1975)ADSCrossRefGoogle Scholar
  4. Mannstein, H., Meyer, R., Wendling, P.: Operational detection of contrails from NOAA-AVHRR data. Int. J. Remote Sens. 20, 1641–1660 (1999)ADSCrossRefGoogle Scholar
  5. Mannstein, H., Brömser, A., Bugliaro, L.: Ground-based observations for the validation of contrails and cirrus detection in satellite imagery. Atmos. Meas. Tech. 3, 655–669 (2010). doi: 10.5194/amt-3-655-2010 CrossRefGoogle Scholar
  6. Meyer, R., Mannstein, H., Meerkötter, R., Schumann, U., Wendling, P.: Regional radiative forcing by line-shaped contrails derived from satellite data. J. Geophys. Res. 107, ACL 17-11–ACL 17-15 (2002). doi:  10.1029/2001jd000426
  7. Meyer, R., Buell, R., Leiter, C., Mannstein, H., Pechtl, S., Oki, T., Wendling, P.: Contrail observations over Southern and Eastern Asia in NOAA/AVHRR data and comparisons to contrail simulations in a GCM. Int. J. Rem. Sens. 28, 2049–2069 (2007). doi: 10.1080/01431160600641707 CrossRefGoogle Scholar
  8. Minnis, P., Palikonda, R., Walter, B.J., Ayers, J.K., Mannstein, H.: Contrail properties over the eastern North Pacific from AVHRR data. Meteorol. Z. 14, 515–523 (2005). doi: 10.1127/0941-2948/2005/0056 CrossRefGoogle Scholar
  9. Palikonda, R., Minnis, P., Duda, D.P., Mannstein, H.: Contrail coverage derived from 2001 AVHRR data over the continental United States of America and surrounding areas. Meteorol. Z. 14, 525–536 (2005). doi: 10.1127/0941-2948/2005/0051 CrossRefGoogle Scholar
  10. Saunders, R.W., Kriebel, K.T.: An improved method for detecting clear sky and cloudy radiances from AVHRR data. Int. J. Rem. Sens. 9, 123–150 (1988)CrossRefGoogle Scholar
  11. Schumann, U., Wendling, P.: Determination of contrails from satellite data and observational results. In: Schumann, U. (ed.) Air Traffic and the Environment—Background, Tendencies and Potential Global Atmospheric Effects, pp. 138–153. Lecture Notes in Engineering. Springer, Berlin (1990)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Hermann Mannstein
    • 1
  • Margarita Vázquez-Navarro
    • 1
  • Kaspar Graf
    • 1
  • David P. Duda
    • 2
  • Ulrich Schumann
    • 1
  1. 1.DLR, Institute of Atmospheric Physics (IPA)OberpfaffenhofenGermany
  2. 2.Science Systems and Applications, Inc.HamptonUSA

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