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Integration of sensors for photogrammetry and remote sensing

Integration of sensors for photogrammetry and remote sensing. 8 th semester, MS 2005. Image geometry, georeferencing, orthorectification. Specifications of VHR sensors for RS Camera models for IKONOS Specifications for IKONOS products Task: georeferencing of a Radar image.

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Integration of sensors for photogrammetry and remote sensing

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  1. Integration of sensors for photogrammetry and remote sensing 8th semester, MS 2005

  2. Image geometry, georeferencing,orthorectification • Specifications of VHR sensors for RS • Camera models for IKONOS • Specifications for IKONOS products • Task: georeferencing of a Radar image

  3. Overview on operational satellite sensors www.spotimage.com

  4. VHR sensors for RS • Specifications • Orbital geometry • Sensor geometry • Image acquisition (‘agility’) • Exterior orientation • Interior orientation • Spectral resolution • Radiometric resolution • Spatial resolution • Temporal resolution

  5. Orbit geometry • Determines: • how much of Earth surface can be covered • how often the satellite revisit the same location • Sun-synchronous orbits • Altitude • Orbit inclination

  6. Sensor geometry • Frame • photogrammetric cameras, central projection • Point • across-track scanner • Line • along-track scanner • Panoramic

  7. Across-track scanner (whiskbroom) • Oscillating mirror • Detectors • Instantaneous field of view (IFOV) • Ground sampled distance (GSD) • Angular field of view • Swath • Geometry not as stable as for line sensors • Distortions due to a scanner mirror rotation • Variations of the resolution cell size • One-dimensional relief displacement • Flight parameter distortions (roll, pitch, ‘crab’) • Application: thermal scanners

  8. Along-track scanner (pushbroom) • Linear array of detectors • Focal plane of the image • Lens • GSD • Geometric integrity of a linear array of detectors • Parameters of EO for each line • Perspective along the scan line, orthographic in the direction of flight • Calibration for each detector • Limitation in spectral sensitivity

  9. Image acquisition geometry Viewing direction Nadir angle Stereo views cross-track along-track nadir forward backward nadir position off-nadir

  10. IKONOS - image acquisition geometry

  11. IKONOS – stereo image collection

  12. Exterior orientation • = satellite ephemeris and attitude • Example: IKONOS • Determination of ephemeris • post-processing of on-board GPS data • Determination of attitude • measuring of star trackers + gyroscopes • Important: relation between the satellite attitude co-ordinate system and the sensor co-ordinate system (pre-launched measurements + in-flight calibration)

  13. Interior orientation • Layout of the detector array, usually placed in the focal plane • Optical distortion parameters • Example : IKONOS • Field Angle Map • allows to determine the line of sight vector for each pixel in the sensor co-ordinate system

  14. Spectral resolution

  15. Spatial resolution IKONOS: ground sampled distance [m] depending upon view direction

  16. Radiometric resolution = number of bits used for a multispectral band  IKONOS: 11-bit Temporal resolution IKONOS:  = 40, GSD = 1 m, revisit time 2.9 days

  17. IKONOS camera model • defines relation between object and image co-ordinates • based on interior and exterior orientation parameters of the sensor • specified by a provider of the sensor/system (Spaceimaging) • complex, difficult to implement for a user • simplification by ‘replacement camera models’ • Rational Polynomial Camera (RPC) model • Direct linear transform (DLT) model • Affine model

  18. Physical camera model Position of projective centre (PC) and attitude angles change from scan line to scan line

  19. Rational Polynomial Camera (RPC) model • relation between object co-ordinates (φ,λ,h) and image co-ordinates (r,c) given by rational polynomial functions: • r’ = fr(φ’,λ’,h’)/gr(φ’,λ’,h’) • c’ = fc(φ’,λ’,h’)/gc(φ’,λ’,h’) • x’ … normalised co-ordinates • x’ = (x-x_offset)/x_scale

  20. Rational polynomial functions • usually, 3rd order polynomials are used • fr = a1+a2φ’+a3λ’+a4h’ +a5φ’λ’+a6λ’h’+a7φ’h’+a8λ’2+a9φ’2++a10h’2+a11φ’λ’ h’+a12λ’3+a13φ’2λ’+a14λ’h’2+a15φ’λ’2++a16φ’3+a17φ’ h’2+a18λ’2h’+a19φ’2λ’+a20h’3 • gr = b1+b2φ’+b3λ’+b4h’ +b5φ’λ’+b6λ’h’+b7φ’h’+b8λ’2+b9φ’2++b10h’2+b11φ’λ’ h’+b12λ’3+b13φ’2λ’+b14λ’h’2+b15φ’λ’2++b16φ’3+b17φ’ h’2+b18λ’2h’+b19φ’2λ’+b20h’3 • similarly, RPC coefficients c1, …, c20, d1, …, d20 in functions fc and gc

  21. RPC coefficients • calculated in least-squares adjustment from 3D grid points • co-ordinates of 3D grid points generated using a physical camera model • comparison of RPC and a physical camera model • max. error using independent check points 0.04 pel • RMS error using independent check points 0.01 pel • (Grodecky, J., Dial, G., IKONOS geometric accuracy, Space Imaging, 2001)

  22. 3D grid for derivation RPC coefficients

  23. Refinement of RPC model • improving absolute positional accuracy of the georeferenced image by adding GCPs • finding parameters of affine transformation • rcorr=a1+a2r’+a3c’ • ccorr=b1+b2r’+b3c’ • improvement of accuracy from several m up to 0.5m if accurate and well distributed GCPs are available

  24. Other replacement camera models • Direct linear transform model • derived from collinearity equation (projective geometry) • x=(a1+a2X+a3Y+a4Z)/(c1+c2X+c3Y+c4Z) • y=(b1+b2X+b3Y+b4Z)/(c1+c2X+c3Y+c4Z) • Affine model • x=a1+a2X+a3Y • y=b1+b2X+b3Y

  25. IKONOS products IKONOS product guide

  26. Links • Articles: • Grodecki, J., Dial, G. (2001).: IKONOS Geometric Accuracy. Proceedings of Joint Workshop of ISPRS Working Groups I/2, I/5 and IV/7 on High Resolution Mapping from Space 2001, University of Hanover, Hanover, Germany, Sept. 19 -21, 2001 • Products description • Space Imaging (IKONOS) • DigitalGlobe (QuickBird)

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