![TanDEM-X Data Acquisition Modes Standard DEM Mode July until October 2010 Temporal baseline: 2-3 sec (20-30Km Across Track separation) ,[object Object],[object Object],[object Object],Bistatic ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Alternating Bistatic Pursuit Monostatic](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
Recomendados
Más contenido relacionado
La actualidad más candente
La actualidad más candente (20)
Destacado
Destacado (20)
Similar a IGARSS2011-TDX_Florian_v2.ppt
Similar a IGARSS2011-TDX_Florian_v2.ppt (20)
Más de grssieee
Más de grssieee (20)
Último
Último (20)
IGARSS2011-TDX_Florian_v2.ppt
- 1. Forest Characterisation by means of TanDEM-X Pol-InSAR Data First Results & Experiments. Microwaves and Radar Institute (DLR-HR) German Aerospace Center (DLR) Florian Kugler, Astor Torano Caycoya, Irena Hajnsek, Kostas Papathanassiou
- 4. Test Site: Krycklan, Sweden HH VV DEM 38m 41m 35m Height of ambiguity HH / VV HH / HV HH / VV Polarisation 0.15 32° 125 08. August 2010 0.17 0.18 K Z 32° 137 19. August 2010 32° 141 28. July 2010 Incidence angle Baseline [m] Date
- 5. 28. July / kz=0.18 8. August / kz=0.15 19. August / kz=0.17 Interferometric Coherence: HH
- 6. Temporal Decorrelation 28. Juli K Z = 0.18 08. August K Z = 0.15 19. August K Z = 0.17 3 seconds may be enough !!! > two acquisitons are affected by temporal decorrelation Interferometric Coherence HV 19. August / kz=0.17 HH HV
- 7. SNR correction Coherence VV VV HH HH Terra SAR-X TanDEM-X NESZ Polynomials (from xml files)
- 8. SNR correction Coherence VV VV HH HH Terra SAR-X TanDEM-X NESZ Polynomials (from xml files)
- 9. 28. July 2010 K Z =0.17 HH VV SNR correction Coherence After calibration: 3% (HH) to 5%(VV) of the coherences > 1. Assuming SNR lower by 1 dB reduces the coherences > 1 to 0.6%.
- 11. Test Site: Krycklan, Sweden HH Interferometric Coherence HH 125m 69m Height of ambiguity HH HH Polarisation 0.05 19° 39 11. June 2011 0.09 K Z 19° 69 17. December 2010 Incidence angle Baseline [m] Date
- 12. Test Site: Krycklan, Sweden HH 12.2010 HH 06.2011 125m 69m Height of ambiguity HH HH Polarisation 0.05 19° 39 11. June 2011 0.09 K Z 19° 69 17. December 2010 Incidence angle Baseline [m] Date
- 13. Test Site: Krycklan, Sweden HH 06.2011 Interferometric Coherence HH Interferometric Coherence HH
- 14. VV Jul θ =32° r²=0.65 / RMSE = 8.27m HH Jul θ =32° r²=0.54 / RMSE=9.45m HH Dec θ =19° r²=0.62 / RMSE = 11.80m HH Jun θ =19° r²=0.61 / RMSE = 9.77m Larger @ HH than @ VV Larger in Winter than in Summer Penetration Depth @ X-band Less sensitive to incidence angle Number of stands: 216 Phase Center Height Phase Center Height Phase Center Height Phase Center Height
- 15. Pol-InSAR Phase Difference Pol-InSAR Coherence Region Phase Center Difference Amplitude / Lidar Heights 6m 0m 30 m 0m
- 16. 2 Layer Scattering Model Volume Coherence Interferometric Coherence Volume Coherence Vertical Wavenumber: G/V Ratio: Volume Height Extinction Topography G/V Ratio Volume Coherence Vertical Wavenumber: G/V Ratio: Volume Height Extinction Topography G/V Ratio
- 17. 1 Layer Scattering Model (m=0) Volume Coherence Volume Coherence Vertical Wavenumber: G/V Ratio: Volume Height Extinction Topography G/V Ratio Volume Coherence Vertical Wavenumber: Volume Height Extinction Topography Single Channel X-band Inversion Interferometric Coherence
- 18. Probably Harvested Lidar Data: 2008 Radar Heights Single Pol Inversion Amplitude / Lidar Heights r² = 0.91 - r² = 0.93 (harvested area removed) RMSE = 1.58 Forest Height Estimation: 1 Pol + DEM 30m 0m
- 19. 2 Layer Scattering Model Volume Coherence Interferometric Coherence Volume Coherence Vertical Wavenumber: G/V Ratio: Volume Height Extinction Topography G/V Ratio Volume Coherence Vertical Wavenumber: G/V Ratio: Volume Height Extinction Topography G/V Ratio
- 20. Radar Heights dUAL Pol Inversion Amplitude / Lidar Heights Forest Height Estimation: 2 Pol Probably Harvested r²=0.86 / RMSE = 2.02m r²=0.93 / RMSE = 1.44m 30m 0m
- 22. Forest Characterisation by means of TanDEM-X Pol-InSAR Data First Results & Experiments. Microwaves and Radar Institute (DLR-HR) German Aerospace Center (DLR) Florian Kugler, Astor Torano Caycoya, Irena Hajnsek, Kostas Papathanassiou
- 27. Krüger National Park Amplitude HH Coherence HH DEM (200-450m) Dual-pol: / HH-VV, Incidence: 40deg, kz=0.1 0 [m] 6 0 [m] 30
Notas del editor
- Polarimetry allows to decompose scattering processes but, do not provide sensitivity to the vertical structure of the scatterer, in other words to the vegetation volume itself. This is because of the two-dimensional imaging geometry of the SAR: ground range and height are projected onto slant range and become ambiguous. The key to the vertical structure is provided by InSAR: As many of you may know InSAR is a technique that allows the estimation of the height of the phase center and thus the generation of DEMs. It is based on the acquisition of two images from slightly different look angles. The main observable is the interferometric coherence: the complex cross-correlation of the two images. The inteferometric coherence can be decomposed into different contributions: temporal …, noise induced decorrelation, and volume decorrelation. And this last term is especially important. Why? Because it is directly related to the vertical reflectivity function of the scatterer, i.e. to its vertical stucture as seen by the radar. To illustrate better this important point lets take a slice through the vegetation layer: the scattering is maximum on the top and gets attenuated as the wave propagates through the volume layer. On the bottom you have again a strong ground contribution. I.e. it has a vertical reflectivity function as this: … The interferometric volume coherence for this slice is nothing more than the (normalised) fourier transform of f(z). Thus, interferometry provides an observation space sensitive to vertical structure.
- Polarimetry allows to decompose scattering processes but, do not provide sensitivity to the vertical structure of the scatterer, in other words to the vegetation volume itself. This is because of the two-dimensional imaging geometry of the SAR: ground range and height are projected onto slant range and become ambiguous. The key to the vertical structure is provided by InSAR: As many of you may know InSAR is a technique that allows the estimation of the height of the phase center and thus the generation of DEMs. It is based on the acquisition of two images from slightly different look angles. The main observable is the interferometric coherence: the complex cross-correlation of the two images. The inteferometric coherence can be decomposed into different contributions: temporal …, noise induced decorrelation, and volume decorrelation. And this last term is especially important. Why? Because it is directly related to the vertical reflectivity function of the scatterer, i.e. to its vertical stucture as seen by the radar. To illustrate better this important point lets take a slice through the vegetation layer: the scattering is maximum on the top and gets attenuated as the wave propagates through the volume layer. On the bottom you have again a strong ground contribution. I.e. it has a vertical reflectivity function as this: … The interferometric volume coherence for this slice is nothing more than the (normalised) fourier transform of f(z). Thus, interferometry provides an observation space sensitive to vertical structure.
- Polarimetry allows to decompose scattering processes but, do not provide sensitivity to the vertical structure of the scatterer, in other words to the vegetation volume itself. This is because of the two-dimensional imaging geometry of the SAR: ground range and height are projected onto slant range and become ambiguous. The key to the vertical structure is provided by InSAR: As many of you may know InSAR is a technique that allows the estimation of the height of the phase center and thus the generation of DEMs. It is based on the acquisition of two images from slightly different look angles. The main observable is the interferometric coherence: the complex cross-correlation of the two images. The inteferometric coherence can be decomposed into different contributions: temporal …, noise induced decorrelation, and volume decorrelation. And this last term is especially important. Why? Because it is directly related to the vertical reflectivity function of the scatterer, i.e. to its vertical stucture as seen by the radar. To illustrate better this important point lets take a slice through the vegetation layer: the scattering is maximum on the top and gets attenuated as the wave propagates through the volume layer. On the bottom you have again a strong ground contribution. I.e. it has a vertical reflectivity function as this: … The interferometric volume coherence for this slice is nothing more than the (normalised) fourier transform of f(z). Thus, interferometry provides an observation space sensitive to vertical structure.