Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography (한국측량학회지)

Korean Society of Surveying, Geodesy, Photogrammetry and Cartography (한국측량학회)
권호 표지
DOI QR코드

DOI QR Code

Atmospheric Correction and Velocity Aberration for Physical Sensor Modeling of High-Resolution Satellite Images

고해상도 위성영상의 센서모델링을 위한 대기 및 속도 보정

  • Oh, Jae-Hong (ETRI(Electronic and Telecommunication Research Institute)) ;
  • Lee, Chang-No (Seoul National University of Science and Technology Civil Engineering)
  • Received : 2011.09.28
  • Accepted : 2011.10.14
  • Published : 2011.10.31
Download PDF
⟨ Previous Next ⟩

Abstract

High-resolution earth-observing satellites acquire substantial amount of geospatial images. In addition to high image quality, high-resolution satellite images (HRSI) provide unprecedented direct georegistration accuracy, which have been enabled by accurate orbit determination technology. Direct georegistration is carried out by relating the determined position and attitude of camera to the ground target, i.e., projecting an image point to the earth ellipsoid using the collinearity equation. However, the apparent position of ground target is displaced due to the atmosphere and satellite velocity causing significant georegistration bias. In other words, optic ray from the earth surface to satellite cameras at 400~900km altitude refracts due to the thick atmosphere which is called atmospheric refraction. Velocity aberration is caused by high traveling speed of earth-observing satellites, approximately 7.7 km/s, relative to the earth surface. These effects should be compensated for accurate direct georegistration of HRSI. Therefore, this study presents the equation and the compensation procedure of atmospheric refraction and velocity aberration. Then, the effects are simulated at different image acquisition geometry to present how much bias is introduced. Finally, these effects are evaluated for Quickbird and WorldView-1 based on the physical sensor model.

Keywords

References

  1. GeoEye, (2011), GeoEye-1, http://launch.geoeye.com/ LaunchSite/about/fact_sheet.aspx.
  2. Grodecki, J. (2001), IKONOS stereo feature extraction - RPC approach, Proceedings of ASPRS 2001 Annual Convention, ASPRS, St. Louis, Missouri, unpaginated CD-ROM.
  3. Kratky, V. (1989), Rigorous photogrammetric processing of SPOT images at CCM Canada, ISPRS Journal of Photogrammetry and Remote Sensing, ISPRS, 44:53-71.
  4. Noerdlinger, P. (1999), Atmospheric refraction effects in Earth remote sensing, ISPRS Journal of Photogrammetry & Remote Sensing, ISPRS, Vol. 54, pp. 360-373.
  5. Oh, J. H., Lee, W.H., Toth, C.K., Grejner-Brzezinska, D.A. and Lee, C.N. (2010), A Piecewise Approach to Epipolar Resampling of Pushbroom Satellite Images Based on RPC, Photogrammetric Engineering & Remote Sensing, ASPRS, Vol. 76, No.12, pp. 1353-1363.
  6. Saastamoinen, J. (1972), Atmospheric correction for the troposphere and stratosphere in radio ranging of satellites, in The Use of Artificial Satellites for Geodesy, Geophysics Monograph Series, Vol. 15, edited by S. W. Henriksen, A. Mancini, and B.H. Chovitz, pp. 247-251, AGU, Washington, D.C.
  7. Stoney, W. E. (2008), ASPRS Guide to Land Imaging Satellites, http://www.asprs.org/news/satellites/ satellites.html.
  8. Toutin, T. (2006), Comparison of 3D Physical and Empirical Models for Generating DSMs From Stereo HR Images, Photogrammetric Engineering & Remote Sensing, ASPRS, Vol.72, No.5, pp. 597-604.