SlideShare una empresa de Scribd logo
1 de 18
Descargar para leer sin conexión
Tandem-L: Estimation of Vertical Forest Structure by means of
Multi-Baseline Pol-InSAR @ L-band for Global Biomass Mapping




M. Padrini, A. Torano Caioya, S-K. Lee, F. Kugler, I. Hajnsek & K. Papathanassiou

Microwaves and Radar Institute (DLR-HR)
German Aerospace Center (DLR) Microwaves and Radar Institute   / Pol - InSAR Research Group
Interferometric                ~( S S )               S1 S  
                                                                                                                                  2
                S1       S2                                                                         γ 1 2
                                                                        Coherence                                  S1 S1   S 2 S  
                                                                                                                        
                                                                                                                                    2




SAR Interferometry for Volume Structure
                                                    hv

                                                         f ( z ) eik z z dz
      Volume             ~ ( f ( z ))  eik z z o
                         γ Vol                      o
                                                         hv
     Coherence
                                                             f ( z ) dz                   f ( z)
                                                         o




                                                                                            f ( z ) … vertical reflectivity function
  ~~
  γ γ Temporal γ SNR ~ Volume
                     γ                                                                                                                   κΔ θ
                                                                                            Vertical Wavenumber: κ z 
                                                                                                                                       sin( θ0 )
   ~
   γ Temporal   … temporal decorrelation

   γ SNR         … additive noise decorrelation
    ~
    γ Volume      … geometric decorrelation


                                                                                                                                       VU 2 > Autor Name
                                                          Microwaves and Radar Institute
                                                                                                                     Microwaves and Radar Institute > 30.05.2006
Interferometric                ~( S S )              S1 S  
                                                                                                                                                 2
                        S1               S2                                                                         γ 1 2
                                                                                        Coherence                                  S1 S1   S 2 S  
                                                                                                                                        
                                                                                                                                                    2




                                                                    hv

                                                                         f ( z ) eik z z dz
             Volume                      ~ ( f ( z ))  eik z z o
                                         γ Vol                      o
                                                                         hv
            Coherence
                                                                             f ( z ) dz                   f ( z)
                                                                         o




                                                                                                            f ( z )2 Layer reflectivity function
                                                                                                                   … vertical Inversion Model
                                                                          2 σ( z ) z 
                                                                                     
                                                                                                                                              κΔ θ 
                                                                                                                                    κ iz ) ~V  m( w )
                                                                          cos θ 0 
                                                        f ( z)  f0 e                                                    ~
                                                                                           m δ( z  z 0 )Vertical Wavenumber: φ0          γ
                                                                                             G                          γ( w )  exp(      sin( θ0() )
                                                                                                                                             1 m w



                                hV                                                                         
                                                   2 σ ( z ) z'                                  mG (w )
                                                  cos θ dz'
                             I  exp(iκ z z' ) exp                                        m( w )                     σ( z) has to be parameterised
Coherence




                                                                                                   m V ( w )I0
                                                            0 
 Volume




            ~
                    I           0                                                                                       Volume Height h V
            γV                     hV
                   I0                      2 σ( z ) z'                                                     κΔ θ       Topography    φ0
                             I0    0
                                           cos θ dz'
                                       exp
                                                   0 
                                                                                                   κz 
                                                                          Microwaves and Radar Institute   sin( θ0 )    G/V Ratio
                                                                                                                                        
                                                                                                                                     m( w ) > Autor Name
                                                                                                                                        VU 3
                                                                                                                                    Microwaves and Radar Institute > 30.05.2006
Traunstein Test Site                                Forest type             Temperate
                                                    Topography           Moderate slopes
                             2003 Oct.              Height                   25 ~ 35m
                                                    Species        N. Spruce, E. Beech, White Fir
                                                    Biomass                40 ~ 450 t/ha




                        50


                        40


                        30


                        20


                        10

   HV Amplitude Image          Pol-InSAR Forest Height                   Elevation Model
                        0m


                                                                                                VU 4 > Autor Name
                                  Microwaves and Radar Institute
                                                                              Microwaves and Radar Institute > 30.05.2006
Traunstein Test Site

                            2003 Oct.                             2008 June




                       50


                       40


                       30


                       20


                       10


                       0m


                                                                                                VU 5 > Autor Name
                                 Microwaves and Radar Institute
                                                                              Microwaves and Radar Institute > 30.05.2006
Microwaves and Radar Institute
                                 Microwaves and Radar Institute > 30.05.2006
Source: Marc Simard, JPL,Microwaves and Radar Institute
                          NASA                            0   10   20   30          40             50 [m] 60
                                                                             Microwaves and Radar Institute > 30.05.2006
-15 m   -5 m Master 5 m                             10 m
Traunstein Test Site




                                                                                                                 50


                                                                                                                 40


                                                                                                                 30


                                                                                                                 20


                                                                                                                 10

       LIDAR DTM       SAR DTM (Relax)
                                                                                                                 0m


                                                                                     VU 9 > Autor Name
                       Microwaves and Radar Institute
                                                                   Microwaves and Radar Institute > 30.05.2006
-15 m     -5 m Master 5 m                              10 m
Traunstein Test Site


                       Bias: 0.1 m                           Bias: 0.2 m
                       Std: 1.7 m                            Std: 2.8 m




                                                                                                                     50


                                                                                                                     40


                                                                                                                     30


                                                                                                                     20


                                                                                                                     10

       LIDAR DTM        SAR DTM (Relax)
                        SAR – LIDAR DTM
                                                                                                                     0m



                        Microwaves and Radar Institute
                                                                       Microwaves and Radar Institute > 30.05.2006
-15 m     -5 m Master 5 m                10 m   -15 m   -5 m Master 5 m                             10 m
Traunstein Test Site




       LIDAR DTM               SAR DTM (Relax)                                 SAR DTM (Relax)


                                                                                                  VU 11 > Autor Name
                               Microwaves and Radar Institute
                                                                                  Microwaves and Radar Institute > 30.05.2006
-15 m      -5 m Master 5 m                10 m   -15 m          -5 m Master 5 m                              10 m
Traunstein Test Site


                               Small Baselines / Large Baselines                Small Baselines / Large Baselines

                               Bias: 0.1                                        Bias: 1 m
                               Std: 2.2                                         Std: 3.1 m
                               Bias: 0.1                                        Bias: -1.3 m
                               Std: 2.6                                         Std: 6.0 m




       LIDAR DTM                SAR DTM (Relax)                                       SAR DTM (Relax)


                                                                                                           VU 12 > Autor Name
                                Microwaves and Radar Institute
                                                                                           Microwaves and Radar Institute > 30.05.2006
Traunstein Test Site

                                                                  X-band
                            2003 Oct.




                                                                  Phase Center Height
                       50


                       40


                       30


                       20


                       10


                       0m


                                                                                                        VU 13 > Autor Name
                                 Microwaves and Radar Institute
                                                                                        Microwaves and Radar Institute > 30.05.2006
Polarimetric Coherence Tomography

                                                                                                     f ( z ) … vertical reflectivity function



                                                         hv

                                                              f ( z ) eik z z dz
 Volume                       ~ ( f ( z ))  eik z z o
                              γ Vol                      o
                                                              hv
Coherence
                                                                  f ( z ) dz                       f ( z)
                                                              o




                                                                                                     f ( z ) … vertical reflectivity function

                                                                                                                                                                  κΔ θ
            f(z)                                                                                    Vertical Wavenumber:                             κz 
                                                                                                                                                                sin( θ0 )
                         hv                                         hv                                       k zh v 1                         k zh v
                                                                                                 h i                                      i          z'
                                                                                                                  (1  f ( z' ))
                                        ik z z                                      ik z z
                               f ( z) e          dz                      f (z) e             dz  v e          2
                                                                                                                                      e         2
                                                                                                                                                          dz '
~ ( f ( z))  eik z zo   o                                          0                             2                1
γ Vol                         hv                                    hv                          1
                                                                                     h
                                  f ( z) dz                            f ( z ) dz  v
                                                                                      2          (1  f ( z ' ))       dz '
                              o                                     0                           1
                                                                                                                                                 1
                                                                                                                               2n  1
              Fourier Legendre Series:                             f ( z' )     anPn (z' )
                                                               Microwaves and Radar Institute
                                                                                                         where            an 
                                                                                                                                 2               
                                                                                                                                      f ( z' )VUn14 z'Autor Name
                                                                                                                                              P ( > )dz'
                                                                                n                                                               1
                                                                                                                                              Microwaves and Radar Institute > 30.05.2006
690
           Topo Height [m]                                      Vertical Forest Profile Reconstruction




                                   Mixed Forest Stand

570
                                                 Mature Spruce Stand
           Topo Height [m]




                                                    PCT Reconstruction from 2 Baselines
                             570
Height H




                                         f(z)
                                                    a0          a1     a2          a3

                  Test site: Traunstein, Germany, L-band @ HVand Radar Institute
                                                        Microwaves
                                                                   Polarisation           Microwaves and Radar Institute > 30.05.2006
Structure-to-Biomass Allometry
                           B = la * 1.66 H 1 . 50




                                                     H     3
                             B = 3.11         a P(z )
                                                 i =0 j =1
                                                                   j   j   i




                                             Height (m)

                                           Biomass Mg/ha
                                                               f (z)
                                                                               a0   a1     a2                          a3


    z
        x

y
                                  Microwaves and Radar Institute
                                                                                         Microwaves and Radar Institute > 30.05.2006
Microwaves and Radar Institute
                                 Microwaves and Radar Institute > 30.05.2006
Summary

Multi-Baseline (Single-Pass) Polarimetric SAR Interferometry:

   Accurate (<10%) estimation of forest top height at high spatial resolutions (20-50m Grid);

   Estimation of Ground DEM – Removal of Vegetation Bias;

   Resolving low frequency vertical forest structure using by a “realistic” number of acqisitions.



Above ground forest Biomass:

   Structure based (AG) Biomass estimators promise accuracy & stability across very different
   forest conditions;

   Mapping of “radar” structure to biomass structure has to be resolved.




                                                                                                   VU 19 > Autor Name
                                          Microwaves and Radar Institute
                                                                                   Microwaves and Radar Institute > 30.05.2006
Tandem-L: Estimation of Vertical Forest Structure by means of
Multi-Baseline Pol-InSAR @ L-band for Global Biomass Mapping




M. Padrini A. Torano Caioya, S-K. Lee, Florian Kugler, Irena Hajnsek & K. Papathanassiou

Microwaves and Radar Institute (DLR-HR)
German Aerospace Center (DLR) Microwaves and Radar Institute   / Pol - InSAR Research Group

Más contenido relacionado

Similar a IGARSS2011-TDX_TandemL_v1.pdf

Within the Resolution Cell_Super-resolution in Tomographic SAR Imaging.pdf
Within the Resolution Cell_Super-resolution in Tomographic SAR Imaging.pdfWithin the Resolution Cell_Super-resolution in Tomographic SAR Imaging.pdf
Within the Resolution Cell_Super-resolution in Tomographic SAR Imaging.pdf
grssieee
 
TWO-POINT STATISTIC OF POLARIMETRIC SAR DATA TWO-POINT STATISTIC OF POLARIMET...
TWO-POINT STATISTIC OF POLARIMETRIC SAR DATA TWO-POINT STATISTIC OF POLARIMET...TWO-POINT STATISTIC OF POLARIMETRIC SAR DATA TWO-POINT STATISTIC OF POLARIMET...
TWO-POINT STATISTIC OF POLARIMETRIC SAR DATA TWO-POINT STATISTIC OF POLARIMET...
grssieee
 

Similar a IGARSS2011-TDX_TandemL_v1.pdf (8)

Interference
InterferenceInterference
Interference
 
Within the Resolution Cell_Super-resolution in Tomographic SAR Imaging.pdf
Within the Resolution Cell_Super-resolution in Tomographic SAR Imaging.pdfWithin the Resolution Cell_Super-resolution in Tomographic SAR Imaging.pdf
Within the Resolution Cell_Super-resolution in Tomographic SAR Imaging.pdf
 
TWO-POINT STATISTIC OF POLARIMETRIC SAR DATA TWO-POINT STATISTIC OF POLARIMET...
TWO-POINT STATISTIC OF POLARIMETRIC SAR DATA TWO-POINT STATISTIC OF POLARIMET...TWO-POINT STATISTIC OF POLARIMETRIC SAR DATA TWO-POINT STATISTIC OF POLARIMET...
TWO-POINT STATISTIC OF POLARIMETRIC SAR DATA TWO-POINT STATISTIC OF POLARIMET...
 
N24108113
N24108113N24108113
N24108113
 
Lecture3
Lecture3Lecture3
Lecture3
 
Diffraction part i
Diffraction part iDiffraction part i
Diffraction part i
 
Output-Sensitive Voronoi Diagrams and Delaunay Triangulations
Output-Sensitive Voronoi Diagrams and Delaunay Triangulations Output-Sensitive Voronoi Diagrams and Delaunay Triangulations
Output-Sensitive Voronoi Diagrams and Delaunay Triangulations
 
Short-time homomorphic wavelet estimation
Short-time homomorphic wavelet estimation Short-time homomorphic wavelet estimation
Short-time homomorphic wavelet estimation
 

Más de grssieee

Tangent height accuracy of Superconducting Submillimeter-Wave Limb-Emission S...
Tangent height accuracy of Superconducting Submillimeter-Wave Limb-Emission S...Tangent height accuracy of Superconducting Submillimeter-Wave Limb-Emission S...
Tangent height accuracy of Superconducting Submillimeter-Wave Limb-Emission S...
grssieee
 
SEGMENTATION OF POLARIMETRIC SAR DATA WITH A MULTI-TEXTURE PRODUCT MODEL
SEGMENTATION OF POLARIMETRIC SAR DATA WITH A MULTI-TEXTURE PRODUCT MODELSEGMENTATION OF POLARIMETRIC SAR DATA WITH A MULTI-TEXTURE PRODUCT MODEL
SEGMENTATION OF POLARIMETRIC SAR DATA WITH A MULTI-TEXTURE PRODUCT MODEL
grssieee
 
THE SENTINEL-1 MISSION AND ITS APPLICATION CAPABILITIES
THE SENTINEL-1 MISSION AND ITS APPLICATION CAPABILITIESTHE SENTINEL-1 MISSION AND ITS APPLICATION CAPABILITIES
THE SENTINEL-1 MISSION AND ITS APPLICATION CAPABILITIES
grssieee
 
GMES SPACE COMPONENT:PROGRAMMATIC STATUS
GMES SPACE COMPONENT:PROGRAMMATIC STATUSGMES SPACE COMPONENT:PROGRAMMATIC STATUS
GMES SPACE COMPONENT:PROGRAMMATIC STATUS
grssieee
 
PROGRESSES OF DEVELOPMENT OF CFOSAT SCATTEROMETER
PROGRESSES OF DEVELOPMENT OF CFOSAT SCATTEROMETERPROGRESSES OF DEVELOPMENT OF CFOSAT SCATTEROMETER
PROGRESSES OF DEVELOPMENT OF CFOSAT SCATTEROMETER
grssieee
 
DEVELOPMENT OF ALGORITHMS AND PRODUCTS FOR SUPPORTING THE ITALIAN HYPERSPECTR...
DEVELOPMENT OF ALGORITHMS AND PRODUCTS FOR SUPPORTING THE ITALIAN HYPERSPECTR...DEVELOPMENT OF ALGORITHMS AND PRODUCTS FOR SUPPORTING THE ITALIAN HYPERSPECTR...
DEVELOPMENT OF ALGORITHMS AND PRODUCTS FOR SUPPORTING THE ITALIAN HYPERSPECTR...
grssieee
 
EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...
EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...
EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...
grssieee
 
EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...
EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...
EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...
grssieee
 
EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...
EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...
EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...
grssieee
 
test 34mb wo animations
test  34mb wo animationstest  34mb wo animations
test 34mb wo animations
grssieee
 
2011_Fox_Tax_Worksheets.pdf
2011_Fox_Tax_Worksheets.pdf2011_Fox_Tax_Worksheets.pdf
2011_Fox_Tax_Worksheets.pdf
grssieee
 
DLR open house
DLR open houseDLR open house
DLR open house
grssieee
 
DLR open house
DLR open houseDLR open house
DLR open house
grssieee
 
DLR open house
DLR open houseDLR open house
DLR open house
grssieee
 
Tana_IGARSS2011.ppt
Tana_IGARSS2011.pptTana_IGARSS2011.ppt
Tana_IGARSS2011.ppt
grssieee
 
Solaro_IGARSS_2011.ppt
Solaro_IGARSS_2011.pptSolaro_IGARSS_2011.ppt
Solaro_IGARSS_2011.ppt
grssieee
 
Sakkas.ppt
Sakkas.pptSakkas.ppt
Sakkas.ppt
grssieee
 

Más de grssieee (20)

Tangent height accuracy of Superconducting Submillimeter-Wave Limb-Emission S...
Tangent height accuracy of Superconducting Submillimeter-Wave Limb-Emission S...Tangent height accuracy of Superconducting Submillimeter-Wave Limb-Emission S...
Tangent height accuracy of Superconducting Submillimeter-Wave Limb-Emission S...
 
SEGMENTATION OF POLARIMETRIC SAR DATA WITH A MULTI-TEXTURE PRODUCT MODEL
SEGMENTATION OF POLARIMETRIC SAR DATA WITH A MULTI-TEXTURE PRODUCT MODELSEGMENTATION OF POLARIMETRIC SAR DATA WITH A MULTI-TEXTURE PRODUCT MODEL
SEGMENTATION OF POLARIMETRIC SAR DATA WITH A MULTI-TEXTURE PRODUCT MODEL
 
THE SENTINEL-1 MISSION AND ITS APPLICATION CAPABILITIES
THE SENTINEL-1 MISSION AND ITS APPLICATION CAPABILITIESTHE SENTINEL-1 MISSION AND ITS APPLICATION CAPABILITIES
THE SENTINEL-1 MISSION AND ITS APPLICATION CAPABILITIES
 
GMES SPACE COMPONENT:PROGRAMMATIC STATUS
GMES SPACE COMPONENT:PROGRAMMATIC STATUSGMES SPACE COMPONENT:PROGRAMMATIC STATUS
GMES SPACE COMPONENT:PROGRAMMATIC STATUS
 
PROGRESSES OF DEVELOPMENT OF CFOSAT SCATTEROMETER
PROGRESSES OF DEVELOPMENT OF CFOSAT SCATTEROMETERPROGRESSES OF DEVELOPMENT OF CFOSAT SCATTEROMETER
PROGRESSES OF DEVELOPMENT OF CFOSAT SCATTEROMETER
 
DEVELOPMENT OF ALGORITHMS AND PRODUCTS FOR SUPPORTING THE ITALIAN HYPERSPECTR...
DEVELOPMENT OF ALGORITHMS AND PRODUCTS FOR SUPPORTING THE ITALIAN HYPERSPECTR...DEVELOPMENT OF ALGORITHMS AND PRODUCTS FOR SUPPORTING THE ITALIAN HYPERSPECTR...
DEVELOPMENT OF ALGORITHMS AND PRODUCTS FOR SUPPORTING THE ITALIAN HYPERSPECTR...
 
EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...
EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...
EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...
 
EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...
EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...
EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...
 
EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...
EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...
EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...
 
Test
TestTest
Test
 
test 34mb wo animations
test  34mb wo animationstest  34mb wo animations
test 34mb wo animations
 
Test 70MB
Test 70MBTest 70MB
Test 70MB
 
Test 70MB
Test 70MBTest 70MB
Test 70MB
 
2011_Fox_Tax_Worksheets.pdf
2011_Fox_Tax_Worksheets.pdf2011_Fox_Tax_Worksheets.pdf
2011_Fox_Tax_Worksheets.pdf
 
DLR open house
DLR open houseDLR open house
DLR open house
 
DLR open house
DLR open houseDLR open house
DLR open house
 
DLR open house
DLR open houseDLR open house
DLR open house
 
Tana_IGARSS2011.ppt
Tana_IGARSS2011.pptTana_IGARSS2011.ppt
Tana_IGARSS2011.ppt
 
Solaro_IGARSS_2011.ppt
Solaro_IGARSS_2011.pptSolaro_IGARSS_2011.ppt
Solaro_IGARSS_2011.ppt
 
Sakkas.ppt
Sakkas.pptSakkas.ppt
Sakkas.ppt
 

Último

Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Victor Rentea
 
Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire business
panagenda
 

Último (20)

Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
 
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data DiscoveryTrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
 
Strategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a FresherStrategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a Fresher
 
Introduction to Multilingual Retrieval Augmented Generation (RAG)
Introduction to Multilingual Retrieval Augmented Generation (RAG)Introduction to Multilingual Retrieval Augmented Generation (RAG)
Introduction to Multilingual Retrieval Augmented Generation (RAG)
 
Elevate Developer Efficiency & build GenAI Application with Amazon Q​
Elevate Developer Efficiency & build GenAI Application with Amazon Q​Elevate Developer Efficiency & build GenAI Application with Amazon Q​
Elevate Developer Efficiency & build GenAI Application with Amazon Q​
 
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
 
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
 
Artificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyArtificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : Uncertainty
 
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
 
presentation ICT roal in 21st century education
presentation ICT roal in 21st century educationpresentation ICT roal in 21st century education
presentation ICT roal in 21st century education
 
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, AdobeApidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
 
FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024
 
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
 
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWEREMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
 
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
 
ICT role in 21st century education and its challenges
ICT role in 21st century education and its challengesICT role in 21st century education and its challenges
ICT role in 21st century education and its challenges
 
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
 
Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin WoodPolkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
 
Exploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with MilvusExploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with Milvus
 
Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire business
 

IGARSS2011-TDX_TandemL_v1.pdf

  • 1. Tandem-L: Estimation of Vertical Forest Structure by means of Multi-Baseline Pol-InSAR @ L-band for Global Biomass Mapping M. Padrini, A. Torano Caioya, S-K. Lee, F. Kugler, I. Hajnsek & K. Papathanassiou Microwaves and Radar Institute (DLR-HR) German Aerospace Center (DLR) Microwaves and Radar Institute / Pol - InSAR Research Group
  • 2. Interferometric ~( S S )   S1 S   2 S1 S2 γ 1 2 Coherence  S1 S1   S 2 S    2 SAR Interferometry for Volume Structure hv  f ( z ) eik z z dz Volume ~ ( f ( z ))  eik z z o γ Vol o hv Coherence  f ( z ) dz f ( z) o f ( z ) … vertical reflectivity function ~~ γ γ Temporal γ SNR ~ Volume γ κΔ θ Vertical Wavenumber: κ z  sin( θ0 ) ~ γ Temporal … temporal decorrelation γ SNR … additive noise decorrelation ~ γ Volume … geometric decorrelation VU 2 > Autor Name Microwaves and Radar Institute Microwaves and Radar Institute > 30.05.2006
  • 3. Interferometric ~( S S )   S1 S   2 S1 S2 γ 1 2 Coherence  S1 S1   S 2 S    2 hv  f ( z ) eik z z dz Volume ~ ( f ( z ))  eik z z o γ Vol o hv Coherence  f ( z ) dz f ( z) o f ( z )2 Layer reflectivity function … vertical Inversion Model  2 σ( z ) z    κΔ θ  κ iz ) ~V  m( w )  cos θ 0  f ( z)  f0 e   ~  m δ( z  z 0 )Vertical Wavenumber: φ0 γ G γ( w )  exp( sin( θ0() ) 1 m w hV   2 σ ( z ) z'   mG (w )   cos θ dz' I  exp(iκ z z' ) exp m( w )   σ( z) has to be parameterised Coherence  m V ( w )I0  0  Volume ~ I 0 Volume Height h V γV  hV I0  2 σ( z ) z'  κΔ θ Topography φ0 I0  0  cos θ dz' exp  0   κz  Microwaves and Radar Institute sin( θ0 ) G/V Ratio  m( w ) > Autor Name VU 3 Microwaves and Radar Institute > 30.05.2006
  • 4. Traunstein Test Site Forest type Temperate Topography Moderate slopes 2003 Oct. Height 25 ~ 35m Species N. Spruce, E. Beech, White Fir Biomass 40 ~ 450 t/ha 50 40 30 20 10 HV Amplitude Image Pol-InSAR Forest Height Elevation Model 0m VU 4 > Autor Name Microwaves and Radar Institute Microwaves and Radar Institute > 30.05.2006
  • 5. Traunstein Test Site 2003 Oct. 2008 June 50 40 30 20 10 0m VU 5 > Autor Name Microwaves and Radar Institute Microwaves and Radar Institute > 30.05.2006
  • 6. Microwaves and Radar Institute Microwaves and Radar Institute > 30.05.2006
  • 7. Source: Marc Simard, JPL,Microwaves and Radar Institute NASA 0 10 20 30 40 50 [m] 60 Microwaves and Radar Institute > 30.05.2006
  • 8. -15 m -5 m Master 5 m 10 m Traunstein Test Site 50 40 30 20 10 LIDAR DTM SAR DTM (Relax) 0m VU 9 > Autor Name Microwaves and Radar Institute Microwaves and Radar Institute > 30.05.2006
  • 9. -15 m -5 m Master 5 m 10 m Traunstein Test Site Bias: 0.1 m Bias: 0.2 m Std: 1.7 m Std: 2.8 m 50 40 30 20 10 LIDAR DTM SAR DTM (Relax) SAR – LIDAR DTM 0m Microwaves and Radar Institute Microwaves and Radar Institute > 30.05.2006
  • 10. -15 m -5 m Master 5 m 10 m -15 m -5 m Master 5 m 10 m Traunstein Test Site LIDAR DTM SAR DTM (Relax) SAR DTM (Relax) VU 11 > Autor Name Microwaves and Radar Institute Microwaves and Radar Institute > 30.05.2006
  • 11. -15 m -5 m Master 5 m 10 m -15 m -5 m Master 5 m 10 m Traunstein Test Site Small Baselines / Large Baselines Small Baselines / Large Baselines Bias: 0.1 Bias: 1 m Std: 2.2 Std: 3.1 m Bias: 0.1 Bias: -1.3 m Std: 2.6 Std: 6.0 m LIDAR DTM SAR DTM (Relax) SAR DTM (Relax) VU 12 > Autor Name Microwaves and Radar Institute Microwaves and Radar Institute > 30.05.2006
  • 12. Traunstein Test Site X-band 2003 Oct. Phase Center Height 50 40 30 20 10 0m VU 13 > Autor Name Microwaves and Radar Institute Microwaves and Radar Institute > 30.05.2006
  • 13. Polarimetric Coherence Tomography f ( z ) … vertical reflectivity function hv  f ( z ) eik z z dz Volume ~ ( f ( z ))  eik z z o γ Vol o hv Coherence  f ( z ) dz f ( z) o f ( z ) … vertical reflectivity function κΔ θ f(z) Vertical Wavenumber: κz  sin( θ0 ) hv hv k zh v 1 k zh v h i i z'    (1  f ( z' )) ik z z ik z z f ( z) e dz f (z) e dz  v e 2 e 2 dz ' ~ ( f ( z))  eik z zo o 0 2 1 γ Vol hv hv 1 h  f ( z) dz  f ( z ) dz  v 2  (1  f ( z ' )) dz ' o 0 1 1 2n  1 Fourier Legendre Series: f ( z' )   anPn (z' ) Microwaves and Radar Institute where an  2  f ( z' )VUn14 z'Autor Name P ( > )dz' n 1 Microwaves and Radar Institute > 30.05.2006
  • 14. 690 Topo Height [m] Vertical Forest Profile Reconstruction Mixed Forest Stand 570 Mature Spruce Stand Topo Height [m] PCT Reconstruction from 2 Baselines 570 Height H f(z) a0 a1 a2 a3 Test site: Traunstein, Germany, L-band @ HVand Radar Institute Microwaves Polarisation Microwaves and Radar Institute > 30.05.2006
  • 15. Structure-to-Biomass Allometry B = la * 1.66 H 1 . 50 H 3 B = 3.11  a P(z ) i =0 j =1 j j i  Height (m) Biomass Mg/ha f (z) a0 a1 a2 a3 z x y Microwaves and Radar Institute Microwaves and Radar Institute > 30.05.2006
  • 16. Microwaves and Radar Institute Microwaves and Radar Institute > 30.05.2006
  • 17. Summary Multi-Baseline (Single-Pass) Polarimetric SAR Interferometry: Accurate (<10%) estimation of forest top height at high spatial resolutions (20-50m Grid); Estimation of Ground DEM – Removal of Vegetation Bias; Resolving low frequency vertical forest structure using by a “realistic” number of acqisitions. Above ground forest Biomass: Structure based (AG) Biomass estimators promise accuracy & stability across very different forest conditions; Mapping of “radar” structure to biomass structure has to be resolved. VU 19 > Autor Name Microwaves and Radar Institute Microwaves and Radar Institute > 30.05.2006
  • 18. Tandem-L: Estimation of Vertical Forest Structure by means of Multi-Baseline Pol-InSAR @ L-band for Global Biomass Mapping M. Padrini A. Torano Caioya, S-K. Lee, Florian Kugler, Irena Hajnsek & K. Papathanassiou Microwaves and Radar Institute (DLR-HR) German Aerospace Center (DLR) Microwaves and Radar Institute / Pol - InSAR Research Group