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Radar Course III
37. Bragg scattering
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
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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Coherence image of Bonn area (Germany)

A series of ERS-1 SAR (Slant Range Complex) data sets of an area near Bonn, acquired during early spring 1994 has been analysed using interferometric methods. As the images were sampled at 3 days intervals, good phase-coherence between image-pairs could be expected. Images between 1st and 28th March were considered and totally 9 coherence images from different image-pairs have been generated.
Agricultural fields appear in general quite bright in the coherence images, however some appear dark, indicating low coherence. In this cases, one can expect that coherence was lost due to farmer activities during the time between the two data acquisitions.
In order to verify this all coherence-images were provided to agricultural experts of the Bonn-University. They inquire about the farmers activities during March 1994, especially with respect to the dark-appearing fields in the coherence images. With respect to the relevant dates all fields were listed for type of crop and farmers activities.
In all cases a reason for the loss of coherence could be identified.
To demonstrate the farmers activities over a longer period a multitemporal colour image was produced (see figure) choosing 3 of the 9 coherence images, namely.
-07/03/1994-10/03/1994 shown in red image channel.
-10/03/1994-13/03/1994 shown in green image channel.
-13/03/1994-16/03/1994 shown in blue image channel.
All fields with equal grey-values in all three channels, i. e. with no change in coherence over the whole period from 07/03/1994 to 16/03/1993 appear not coloured, in black and white. The coloured fields result from different grey values in at least one of the three image planes (red or green or blue). The red fields have low coherence in the green and blue image plane, and hence no contribution from those to the colour-combination.
In fact the farmer ploughed the field twice, once between 13/03/1993 and 16/03/1993 and a second time between 16/03/1993 and 19/03/1993.
In yellow appear the fields with no coherence in the blue image plane, i. e. farming activities in this case must have taken place after the 13/03/1994.
In fact the field verification proved that farmer activities on these field were carried out between the 13th and the 16th of March. In the same manner all other colours could be explained.
Not only farmers activities, but also meteorological effects (rain, wind-fall), irrigation and of course all changes linked to vegetation growth can be reasons for de-correlation.
In our case, a loss of coherence especially related with growth can be neglected as vegetation canopy in March, if available at all is still very low and further, only a rather short time interval between two ERS-1 acquisition was considered.

(Wegmüller, Werner, Nuesch, RSL, Univ.Zurich)

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