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Traffic Data Collection with TerraSAR-X and Performance Evaluation

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Part of the Remote Sensing and Digital Image Processing book series (RDIP, volume 15)

Abstract

As the amount of traffic has dramatically increased over the last years, traffic monitoring and traffic data collection have become more and more important. The acquisition of traffic data in almost real-time is essential to immediately react to current traffic situations. Stationary data collectors such as induction loops and video cameras mounted on bridges or traffic lights are matured methods. However, they only provide local data and are not able to observe the traffic situation in a large road network. Hence, traffic monitoring approaches relying on airborne and space-borne remote sensing come into play. Especially space-borne sensors do cover very large areas, even though image acquisition is strictly restricted to certain time slots predetermined by the respective orbit parameters. Space-borne systems thus contribute to the periodic collection of statistical traffic data in order to validate and improve traffic models. On the other hand, the concepts developed for space-borne imagery can be easily transferred to future HALE (High Altitude Long Endurance) systems, which show great potential to meet the demands of both temporal flexibility and spatial coverage.

Keywords

False Alarm Rate Synthetic Aperture Radar Synthetic Aperture Radar Image Synthetic Aperture Radar Data Azimuth Direction 
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. Adam N, Kampes B, Eineder M (2004) Development of a scientific permanent scatterer system: modifications for mixed ERS/ENVISAT time series. In: Proceedings of ENVISAT symposium, Salzburg, AustriaGoogle Scholar
  2. Bamler R, Hartl P (1998) Synthetic aperture radar interferometry. Inverse Probl 14:R1–R54CrossRefGoogle Scholar
  3. Bamler R, Schättler B (1993) SAR geocoding,  Chapter 3. Wichmann, Karlsruhe, pp 53–102Google Scholar
  4. Bethke K-H, Baumgartner S, Gabele M, Hounam D, Kemptner E, Klement D, Krieger G, Erxleben R (2006) Air- and spaceborne monitoring of road traffic using SAR moving target indication – Project TRAMRAD. ISPRS J Photogramm Remote Sens 61(3/4):243–259CrossRefGoogle Scholar
  5. Chiu S, Livingstone C (2005) A comparison of displaced phase centre antenna and along-track interferometry techniques for RADARSAT-2 ground moving target indication. Can J Remote Sens 31(1):37–51Google Scholar
  6. Cumming I, Wong F (2005) Digital processing of synthetic aperture radar data. Artech House, Boston, MAGoogle Scholar
  7. Ender J (1999) Space-time processing for multichannel synthetic aperture radar. Electron Commun Eng J 11(1):29–38CrossRefGoogle Scholar
  8. Ferretti A, Prati C, Rocca F (2001) Permanent scatterers in SAR interferometry. IEEE Trans Geosci Remote Sens 39(1):8–20CrossRefGoogle Scholar
  9. Gierull C (2002) Moving target detection with along-track SAR interferometry. Technical Report DRDC-OTTAWA-TR-2002–084, Defence Research & Development CanadaGoogle Scholar
  10. Hinz S, Bamler R, Stilla U (eds) (2006) ISPRS journal theme issue: “Airborne and spaceborne traffic monitoring”. Int J Photogramm Remote Sens 61(3/4)Google Scholar
  11. Hinz S, Meyer F, Eineder M, Bamler R (2007) Traffic monitoring with spaceborne SAR – theory, simulations, and experiments. Comput Vis Image Underst 106:231–244CrossRefGoogle Scholar
  12. Klemm R (ed.) (1998) Space-time adaptive processing. The Institute of Electrical Engineers, LondonGoogle Scholar
  13. Livingstone C-E, Sikaneta I, Gierull C, Chiu S, Beaudoin A, Campbell J, Beaudoin J, Gong S, Knight T-A (2002) An airborne Synthetic Aperture Radar (SAR) experiment to support RADARSAT-2 Ground Moving Target Indication (GMTI). Can J Remote Sens 28(6):794–813Google Scholar
  14. Meyer F, Hinz S, Laika A, Weihing D, Bamler R (2006) Performance analysis of the TerraSAR-X traffic monitoring concept. ISPRS J Photogramm Remote Sens 61(3–4):225–242CrossRefGoogle Scholar
  15. Müller R, Krauß T, Lehner M, Reinartz P (2007) Automatic production of a European orthoimage coverage within the GMES land fast track service using SPOT 4/5 and IRS-P6 LISS III data. Int Arch Photogramm Remote Sens Spat Info Sci 36(1/W51), on CDGoogle Scholar
  16. Runge H, Laux C, Metzig R, Steinbrecher U (2006) Performance analysis of virtual multi-channel TS-X SAR-Modes. In: Proceedings of EUSAR’06, GermanyGoogle Scholar
  17. Sharma J, Gierull C, Collins M (2006) The influence of target acceleration on velocity estimation in dual-channel SAR-GMTI. IEEE Trans Geosci Remote Sens 44(1):134–147CrossRefGoogle Scholar
  18. Sikaneta I, Gierull C (2005) Two-channel SAR ground moving target indication for traffic monitoring in urban terrain. Int Arch Photogramm Remote Sens Spat Info Sci 61(3–4):95–101Google Scholar
  19. Suchandt S, Eineder M, Müller R, Laika A, Hinz S, Meyer F, Palubinskas G (2006) Development of a GMTI processing system for the extraction of traffic information from TerraSAR-X data. In: Proceedings of EUSAR European Conference on Synthetic Aperture RadarGoogle Scholar
  20. Weihing D, Hinz S, Meyer F, Suchandt S, Bamler R (2007) Detecting moving targets in dual-channel high resolution spaceborne SAR images with a compound detection scheme. In: Proceedings of International Geoscience and Remote Sensing Symposium (IGARSS’07), Barcelona, Spain, on CDGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  1. 1.Photogrammetry and Remote SensingKarlsruhe Institute of TechnologyKarlsruheGermany
  2. 2.Remote Sensing Technology InstituteGerman Aerospace Center DLRBerlinGermany
  3. 3.Remote Sensing Technology, TU MuenchenMuenchenGermany

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