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VIIth International Scientific and Technical Conference From Imagery to Map: Digital Photogrammetric Technologies Master class: Photogrammetric processing.

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Presentation on theme: "VIIth International Scientific and Technical Conference From Imagery to Map: Digital Photogrammetric Technologies Master class: Photogrammetric processing."— Presentation transcript:

1 VIIth International Scientific and Technical Conference From Imagery to Map: Digital Photogrammetric Technologies Master class: Photogrammetric processing of pushbroom satellite images Petr S. Titarov, Software Developer September 17-20, 2007, Nessebar, Bulgaria

2 Master class layout Pushbroom imagery acquisition Pushbroom imagery acquisition Pushbroom imaging modes Pushbroom imaging modes Pushbroom stereopairs acquisition methods Pushbroom stereopairs acquisition methods Pushbroom images blocks Pushbroom images blocks Parameters of pushbroom imaging systems Parameters of pushbroom imaging systems I. Basics of space pushbroom imaging Photogrammetric processing problems Photogrammetric processing problems Methods of pushbroom photogrammetry Methods of pushbroom photogrammetry II. Pushbroom photogrammetry Systems of resolution 1 meter and better Systems of resolution 1 meter and better Systems of resolution about 2 meters Systems of resolution about 2 meters Systems of resolution 5 meters Systems of resolution 5 meters Systems of resolution 10-20 meters Systems of resolution 10-20 meters III. Pushbroom imaging systems overview V. Satellite pushbroom imagery processing using PHOTOMOD IV. Taking choice of remote sensing product for photogrammetry

3 Part I Pushbroom imagery acquisition Pushbroom imagery acquisition Pushbroom imaging modes Pushbroom imaging modes Pushbroom stereopairs acquisition methods Pushbroom stereopairs acquisition methods Pushbroom images blocks Pushbroom images blocks Parameters of pushbroom imaging systems Parameters of pushbroom imaging systems Basics of space pushbroom imaging

4 Pushbroom image acquisition Line-by-line (pushbroom) Pixel by pixel (whiskbroom) Geometry of pushbroom imagery significantly differs from central projection one, so the classical photogrammetric methods are not applicable.

5 Pushbroom imaging modes Synchronous pushbroom imaging mode Sensor attitude is kept constant during the image acquisition long strips acquisition is possible the mode simplifies image geometry Most of current imaging systems work in a synchronous way: IKONOS SPOT 1-5 IRS 1C/1D/P5/P6 FORMOSAT-2 Terra ALOS …and others.

6 Pushbroom imaging modes Asynchronous pushbroom imaging mode Sensor attitude is rapidly changing during the image acquisition: to enlarge the exposure to make vector-scenes (not parallel to the satellite track) Asynchronous mode is incident to high-resolution imaging systems like: EROS A QuickBird

7 Pushbroom stereopairs acquisition methods Cross-track stereo imaging Cross-track (roll) tilting possibility is required Two similar satellites can be used Systems implementing this way of stereo imaging are, for example SPOT 1-5 (сенсоры HRV, HRVIR, HRG) IRS 1C/1D

8 Pushbroom stereopairs acquisition methods Along-track stereo imaging retargeting the sensor Short time gap between the stereopair images acquisition High satellite agility is required Systems implementing this way of stereo imaging are, for example: IKONOS EROS

9 Pushbroom stereopairs acquisition methods Along-track imaging using two sensors mounted on the same satellite Short time gap between the stereopair images acquisition Constant base-to-height ratio Long stereo strips can be acquired SPOT 5/HRS Cartosat-1 ALOS Terra/ASTER

10 Blocks of pushbroom images Base-to-height ratio (B:H) in the overlapping areas is arbitrary. Block of single images (“monoblock”) New (ordered) imaging Block composed of archive images

11 Blocks of pushbroom images Block of stereopairs (“stereoblock”) The set of overlapping stereopairs

12 Pushbroom imaging systems parameters Geometric parameters: Example: SPOT/HRG Ground sample distance Swath width Depends on: detector size focal length orbit altitude Depends on: focal length< the two determine detectors size and count < the field of view orbit altitude tilting Tilting capability Depends on: sensor and satellite design

13 Pushbroom imaging systems parameters The main radiometric parameters Spectral channels Count and the wavelength range Radiometric resolution Dynamic range Imaging system productivity Depends on: swath width satellite orbit tilting capability imaging mode (synchronous/asynchronous) stereoscopic imaging method on-board storage capacity parameters and placement of receiving stations

14 Remote sensing satellites orbits Major semi-axis a determines the satellite altitude Eccentricity e  0 (circular orbit) constant satellite altitude Inclination i  98  (near-polar sun-synchronous orbit) almost all the Earth is observable satellite passes nodes every revolution at the same local time Celestial longitude of the ascending node  subject to perturbation Argument of perigee  does not matter for circular orbit Secular perturbation per N revolutions: Geo-synchronous orbit satellite track periodically repeats

15 Remote sensing satellites orbits Polar orbitSun-synchronous orbit

16 Part II Problems solved to perform photogrammetric processing Problems solved to perform photogrammetric processing Methods of pushbroom photogrammetry Methods of pushbroom photogrammetry Pushbroom photogrammetry

17 Space resection and space intersection GCPs Single images DEM 3D vectors Orthoimagery 2D vectors DEM GCPs Stereopairs Ortho- mosaics Export to GIS, CAD, digital maps

18 Methods of pushbroom photogrammetry RigorousReplacement models Methods of pushbroom photogrammetry Modeling imagery acquisition geometry Using abstract relationships that approximate rigorous imaging model Generic Using a-priory relationships containing parameters determined from GCPs

19 Rigorous method Ray’s edges: Ray’s directional vectors: l – line number p – detector number Sensor motion model: Ray’s directional vector: Attitude model: Sensor geometry model: Reconstruction of: Models used: Ray’s edge: Reconstructed vectors:

20 Sensor geometry (interior orientation) Tabulated vector-function2D central projection p p1p1 p2p2  The model defines the directional vector of ray sensed by the detector number p with respect to the sensor reference system S  : The model is the analog of interior orientation elements in classical photogrammetry.

21 Sensor motion model Polynomial model Orbital model Keplerian orbit parameters: major semi-axis a eccentricity e inclination i celestial longitude of the ascending node  argument of perigee  perigee passing time  Parameters to be refined: e, i, , , sometimes a Parameters to be refined: A i, B j, C k applicable in any Cartesian reference system (including ECR) simple to implement inertial reference system must be used physical model only a few parameters to refine

22 Sensor attitude model The model is defined by the three angles , , , which polynomially depend on the line number l, or it can be represented as the sum of the measured in-flight values and polynomial refinements: The model defines the rotation of the sensor reference system with respect to the geocentric Reference system.

23 Rigorous solution of space resection and space intersection Space intersection Space resection Correspondent rays intersection Iterative process

24 Imagery orientation Any two of the three equations are independent: The image orientation is based on the collinearity condition:

25 Generic (parametric) method Using some a-priory equations derived from coarse assumptions concerning imaging geometry which relate image coordinates x, y to ground ones X,Y,Z. The values of the parameters involved into the equations are calculated using GCPs. Direct Linear Transformation (DLT)Parallel-perspective model

26 Replacement models They are models which approximate ground-to-image correspondence calculated using rigorous method: or, more often,

27 RPC = Rational Polynomial Coefficients = Rapid Positioning Capability Basic relationships:, where  N, N, h N - normalized ground coordinates: (-1   N  1, -1  N  1, -1  h N  1) x N, y N - normalized image coordinates: (-1  x N  1, -1  y N  1) Adjustment-derived refinements: или

28 Algebraic solution of space intersection and space resection Space intersection Space resection Based on relationships: Directly by formulaLeast-squares estimation of 3 unknowns X, Y, Z from 4 non-linear equations:

29 Part III Systems of resolution of 1 m or better Systems of resolution of 1 m or better Systems of resolution about 2 m Systems of resolution about 2 m Systems of resolution 5 m Systems of resolution 5 m Systems of resolution 10-20 m Systems of resolution 10-20 m Pushbroom imaging systems overview

30 Systems of resolution 1 m or better

31

32 Systems of resolution about 2 m

33 Systems of resolution 5 m

34 Systems of resolution 10-20 m

35 Part IV Taking choice of remote sensing product for photogrammetry One should take into consideration the following aspects: if the imagery is geometrically pre-processed metadata contents (if it contains the image geometry) possibility to order polygones or sub-scenes data format

36 Geometric preprocessing Rigorous methods are not applicable to the geometrically preprocessed imagery! Example: Imaging system Geometrically raw Geometrically raw Geometrically corrected Remote sensing product SPOT, ASTER 1A1B KOMPSAT, Landsat 1R1G QuickBirdBasicStandard OrbView-3BASICGEO

37 Metadata contents and data file format Cartosat-1 stereopair Stereo Ortho Kit Basic stereo TIFF raster and RPC Super Structured file format, processing using generic methods

38 Part V Satellite pushbroom imagery processing using PHOTOMOD

39 PHOTOMOD supported sensors

40 Remote sensing product files set structure QuickBird Basic product files set Connection between IKONOS Geo Ortho Kit product imagery and RPC files.tif.tif _rpc.txt _rpc.txt

41 QuickBird Standard Tiled Structure QuickBird Standard and Standard Ortho Ready imagery can be tiled. RPC refers to the composed image!

42 Collective processing of imagery acquired by different sensors Possible candidates for collective processing: SPOT-5 Supermode (2.5 m) FORMOSAT 2 PAN (2 m) IKONOS + OrbView-3 + Kompsat-2 IKONOS + OrbView-3 + Kompsat-2 +

43 Thank you for your attention!


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