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    15-Feb-2012
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Radar Course III
43. Texture and image analysis
42. Temporal averaging
12. Synthetic Aperture Radar (SAR)
34. Space, time and processing constraints
15. Slant range / ground range
8. Side-looking radars
19. Shadow
10. Real Aperture Radar: Range resolution
11. Real Aperture Radar: Azimuth resolution
9. Real Aperture Radar (RAR)
7. Radar principles
38. Radar image interpretation
35. The radar equation
36. Parameters affecting radar backscatter
16. Optical vs. microwave image geometry
25. Method
18. Layover
32. Landers Earthquake in South California
23. Introduction
27. Interferogramme of Naples (Italy)
29. Interferogramme and DEM of Gennargentu (Italy)
2. Independence of clouds coverage
40. Image interpretation: Speckle
41. Image interpretation: Speckle filters
39. Image interpretation: Tone
20. Geometric effects for image interpretation
22. Geocoding: Geometry
17. Foreshortening
26. First ERS-1/ERS-2 tandem interferogramme
6. Electromagnetic spectrum
30. Differential interferometry
45. Data reduction: 16 to 8 bit, blockaverage vs incrementing
4. Control of imaging geometry
3. Control of emitted electromagnetic radiation
24. Concept
28. Coherence image of Bonn area (Germany)
44. Classification of ERS-1 SAR images with Neural Networks
37. Bragg scattering
5. Access to different parameters compared to optical systems
13. SAR processing
33. SAR interferometric products
21. SAR image geocoding
14. ERS SAR geometric configuration
31. The Bonn experiment
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SAR image geocoding

The principle of side-looking SAR is measurement of the electromagnetic signal round trip time for the determination of slant ranges to objects and the strength of the returned signal. This principle causes several types of geometrical distortions.
The upper part of the image shows an example of radar image with its characteristic slant range geometry. Severe distortions occur if pronounced terrain relief is present in the imaged zone.

The amount of distortion depends on the particular side-looking geometry and on the magnitude of the undulation of the terrain's surface.
The central part of the figure shows a digital elevation model of the zone that is used to create a grid map necessary to locate correctly the position of the pixels.
In many applications such as agriculture and vegetation mapping, the terrain-induced distortions degrade the usefulness of SAR images and in some cases may even prevent information extraction.

The lower part of the figure map represents the geometrically corrected image.
SAR data geocoding is a very important step for many users because SAR data should be geometrically correct in order to be compared or integrated with other types of data (satellite images, maps, etc.).
Geocoding an image consists of introducing spatial shifts on the original image in order to have a correspondance between the position of points on the final image and their location in a given cartographic projection.
Radiometric distortions also exist in connection with terrain relief and often cannot be completely corrected. In addition, resampling of the image can introduce radiometric errors.
For these reasons, the thematic user of the image needs information on what he should expect in terms of interpretability of geocoded images for a given thematic application.
A layover/shadowing mask and a local incidence angles map are both helpful for many applications.

This figure illustrates a SAR geocoding system consisting of 3 data bases:
- orbital parameters,
- raw radar data,
- geographic data base (Digital Terrain Model, Control Points and parameters of cartographic projection)
ERS-1 SAR looks at the Earth surface with a 23° incidence angle. Due to this, images contain almost no shadow but may contain a large amount of layover and foreshortening.
With the geocoded data, ERS-1 PAFs (Processing and Archiving Facilities) provide on request a data file indicating the layover and shadowed zones as well as the local incidence angle for each element of the picture.
This file is useful for the interpreter prior to thematic mapping. If a Digital Elevation Model is available, it may be possible to correct the terrain influence in SAR images.
This figure illustrates an example of SAR data geocoding.
The reference scene (left of the screen) was acquired on 24 November 1991 over the north-western part of Switzerland and includes the city of Basel and the Rhine (top-left corner), the chain of the Jura mountains (northern part of the image), the Aare river crossing through the centre of the image with the capitol Berne near the lower left corner.
The southern part consists of lowland hills, the Napf area and the pre-alpine mountain chains.
The shores of the Lake of Lucerne (Vierwaldstätter See), in the south-east are not well defined due to wind-roughening effects.
The image presents strong geometric distorsions which are no more visible in the corrected image displayed on the right of the screen.

Keywords: ESA European Space Agency - Agence spatiale europeenne, observation de la terre, earth observation, satellite remote sensing, teledetection, geophysique, altimetrie, radar, chimique atmospherique, geophysics, altimetry, radar, atmospheric chemistry