SlideShare une entreprise Scribd logo
1  sur  29
Télécharger pour lire hors ligne
Orfeo Toolbox
Radiometric corrections

      Stéphane MAY
  stephane.may@cnes.fr




                          orfeo-toolbox.org
                                          1
Radiometry

Radiometry = science of electromagnetic radiations
Interest for Remote Sensing
   Physical interpretation of signals
   Enhance detection
   Estimate physical values related to ground and / or
   atmospheric effects




                                                         orfeo-toolbox.org
                                                                         2
Radiometry : from DN to TOA reflectance
Goal : using physical measures
   TOA reflectance (Top of Atmosphere)
   TOC reflectance (Top of Canopy)
Calibration of images : DN (digital numbers) converted into
TOA reflectance
   Application of calibration coefficient inserted into metadata
   files → Luminance
   Normalisation with solar effect →
   Reflectance
   Example for Spot :



                                                                   orfeo-toolbox.org
                                                                                   3
Luminance




            orfeo-toolbox.org
                            4
Luminance
Definition
   Emitted power per unit area and per unit solid angle
Unit
   W.m-2.sr-1
Numerical example:
   Luminance of the sky (visible): ~ 6 W.m-2.sr-1




                                                          orfeo-toolbox.org
                                                                          5
TOA reflectance




                  orfeo-toolbox.org
                                  6
Radiometry : from TOA reflectance to TOC reflectance
Atmospheric correction : inversion of surface TOC reflectance
   Need to caracterise atmospheric conditions
    ➢TOMS / TOAST data : (grid : 1,25°lon x 1°lat ~ 135 x 110
      km) : stratospheric Ozone amount
      NCEP meteo data : (grid : 2,5°lon x 2,5°lat ~ 270 x 270
      km) : Atmospheric Pressuree, water vapor, wetness
      SeaWiFS or MODIS data : (grid : 5’ x 5’ ~ 9 x 9 km) ) :
      Optical aerosols thickness
      Cimel of aeronet network : information
      about aerosols, and water amount
                                                 Absorption        Ozone
                                                 Scattering                   Cloud

                                                 Emission                      Water vapor
                                                            Molecules

                                                                                  Aerosols
                                                 Reflection                orfeo-toolbox.org
                                                                                             7
Atmospheric effects
Atmosphere
   Thickness ~100 km
  Filter descending and ascending radiations
Composition of the atmosphere:
   Molecules
      nitrogen (78%), oxygen (21%), argon, carbon oxides,
      ozone, water vapor (highly variable, even locally) ...
   Aerosols
      small solid or liquid particles suspended in the
      atmosphere. Microparticles, water particles, ice crystals,
      smoke ...
      Dimensions: mainly from 0.1 to 10 µm
   Abundance and type varies geographically and with time          orfeo-toolbox.org
                                                                                   8
Atmospheric effects
Altitude (km)
                               EXOSPHERE
800


                THERMOSPHERE



                               -90°C
85        Mesopause


                                                      Profil de Températures
                MESOSPHERE




50        Stratopause                                              0°C



                STRATOSPHERE
                               Ozone

10        Tropopause                                       -55°C




                TROPOSPHERE
                                                        Nuages
                                           Aérosols
                               Vapeur
                                d'eau                                     +15°C
  0       Sol

                                                                                  orfeo-toolbox.org
                                                                                                  9
Atmospheric effects




                      orfeo-toolbox.org
                                     10
Atmospheric effects
Three main phenomena, depending of wavelength
   Absorption
   Diffusion (in the visible and NIR, up to ~ 3 µm)
   Emission (in the thermic IR, from ~ 3 µm)
   Optional : refraction, usually neglected for high elevation
   acquisition and not included spatial resolutions greater than
   10 cm
The contribution of the signal from the ground in the measured
signal is disturbed by filtering effects and luminance of the
atmosphere
   Need to correct measures
   Need to understand the phenomena
                                                                   orfeo-toolbox.org
                                                                                  11
Radiometry : 6S model
Atmospheric corrections : invert the TOC surface reflectance.
Simulation with radiative transfer code
       6S code
           Diffusion : code of the successive diffusion orders
           Absorptions : O2, CO2, H2O, O3, N2O, CH4
           Spectro data at 10 cm-1« AFGL atmospheric absorption
           line parameters compilation » (1991)
           Look-Up Tables : refl. TOC -> TOA
                     Mesure
       ρTOA
                                Simulations TOA

                               Géo d’observation
                               Conditions atmosphériques
ρTOC
       0      0,01   0,02 0,03                         0,8
                         Valeur sol interpolée                    orfeo-toolbox.org
                                                                                 12
orfeo-toolbox.org
               13
Radiometry : 6S parameters
Atmospheric parameters => parameters of radiative transfer
   The zenithal and azimutal solar angles that describe the
   solar incidence configuration (in degrees)
   The zenithal and azimuthal viewing angles that describe the
   viewing direction (in degrees)
   The month and the day of the acquisition
   The atmospheric pressure
   The water vapor amount, that is, the total water vapor
   content over vertical atmospheric column




                                                                 orfeo-toolbox.org
                                                                                14
Radiometry : 6S parameters
Atmospheric parameters => parameters of radiative transfer
   The ozone amount that is the Stratospheric ozone layer
   content;
      The aerosol model that is the kind of particles (no
      aerosol, continental, maritime, urban, desertic)
      The aerosol optical thickness at 550 nm that is the is the
      Radiative impact of aerosol for the reference wavelength
      550 nm
      The filter function that is the values of the filter function
      for one spectral band, from λinf to λsup by step of 2.5
      nm. One filter function by channel is required. This last
      parameter are read in text files, the other one are directly
      given to the class.                                           orfeo-toolbox.org
                                                                                    15
Radiometry : 6S parameters
Spectral sensitivity file
   Data provided in OTB-Data (not with Monteverdi)
     ➢OTB-Data/Input/Radiometry/
   For each band with a step of 0.25 nm, the spectral band
   sensitivity of the instrument
     ➢Input file : values in the Atmospheric parameters window
     ➢No input file : iso sensitivity (1 everywhere) or default file
       automatically loaded (>OTB V3.10)




                                                                       orfeo-toolbox.org
                                                                                      16
Aeronet data
AERONET (AErosol RObotic NETwork)
  This program is a federation of ground-based remote sensing
  aerosol networks established by NASA and LOA-PHOTONS
  (CNRS) and is greatly expanded by collaborators




                                                           orfeo-toolbox.org
                                                                          17
Aeronet data and OTB

Aerosol optical depth data are computed for three data quality
levels
   Level 1.0 (unscreened)
   Level 1.5 (cloud-screened)
   Level 2.0 (cloud screened and quality-assured).
Extract Aerosol thickness (épaisseur) and Water amount

Download site
   http://aeronet.gsfc.nasa.gov/cgi-bin/webtool_opera_v2_new



                                                           orfeo-toolbox.org
                                                                          18
Radiometry – Reference reflectances

Mesure of the reflectance of a source
   Principle : use a source and measure reflected luminance
    ➢ Direct measure : known source
    ➢ Indirect measure : use of a known reference reflectance
      surface (spectralon, or BaSO4)
   Measures in laboratory
    ➢ Artificial source : directional, mobile (lamp, laser)
    ➢ Sensor (radiometer or spectro-radiometer) : mobile
         Direct measure or indirect measure




                                                                orfeo-toolbox.org
                                                                               19
Radiometry

Spectral signature of the chlorophyllian vegetation


                                        Proche
                         Visible                             Moyen Infra-Rouge
                                     Infra-Rouge


REFLECTION due à :    pigment         Structure
                                                               Teneur en eau
                     de la feuille    cellulaire

ABSORPTION due à :    Chlorophylle                                 Eau




                                            Longueur d’onde (µm)
                                                                                 orfeo-toolbox.org
                                                                                                20
Radiometry processing - Synthesis

3 processing steps
   Digital Number to Luminance
   Luminance to TOA reflectance
  TOA reflectance to TOC surface reflectance
Many parameters available in the metadata of sensors
    Importance of aerosols to quantify the effects of the
    atmosphere
Difficulties
   Aerosol model used?
   Validation of results?
   Ground truth?
                                                            orfeo-toolbox.org
                                                                           21
Optical calibration module (1/2)




                                   orfeo-toolbox.org
                                                  22
Optical calibration module (2/2)




                                   orfeo-toolbox.org
                                                  23
Use case 1 : radiometric correction
Menu File > Open
   ./img_kalideos_reunion/2009-03-21/IMAGERY.TIF
Menu Calibration > Optical calibration
   Load Aeronet file
     ➢ ./aeronet/070101_091231_REUNION_ST_DENIS.lev20
   Load spectral sensity file
     ➢ ./OTB-Data/Input/Radiometry/SPOT5/HRG1/rep6S.dat
   Change correction parameters
   Change Radiative terms
   Save / quit
File > Save (Luminance, TOA, TOC, TOA-TOC files)
Repeat the Calibration process with other parameters set
Visualization > Viewer : compare results
                                                           orfeo-toolbox.org
                                                                          24
Use case 1b : radiometric correction
Use the commande line tool :
   OtbOpticalCalibration-cli -h
   otbOpticalCalibration-cli -in IMAGERY.TIF -out img_toc.tif -level TOC
   -AerosolModel 0 –OzoneAmount 0 --AtmosphericPressure 1030
   --AerosolOptical 0.0329 –WaterVaporAmount 4.226 -aeronet file.lev20
   -srs rep6S.dat




                                                                 orfeo-toolbox.org
                                                                                25
Spectral viewer (1/2)




                        orfeo-toolbox.org
                                       26
Spectral viewer (2/2)




                        orfeo-toolbox.org
                                       27
Use case 2 : Spectral viewer
Menu File > Open
   ./img_kalideos_reunion/2009-03-21/IMAGERY.TIF
Menu Viewer > Spectral viewer
   Left click : select your area
   Right click : select pixel
   Spectral angle menu > Select one curve ID
     ➢ Click on Compute button
File > Save (the Spectral angle file). Use Float data type
Create several reference spectral angle images : roads, houses, sea,
clouds, vegetation, bare soil




                                                                 orfeo-toolbox.org
                                                                                28
Monteverdi




Thank you for your attention !




                                 orfeo-toolbox.org
                                                29

Contenu connexe

Tendances

A new single grating spectrograph for ultra violet raman scattering studies
A new single grating spectrograph for ultra violet raman scattering studiesA new single grating spectrograph for ultra violet raman scattering studies
A new single grating spectrograph for ultra violet raman scattering studies
John Clarkson
 
Pitt Conn 2012 Fi Cs As Invited Sers Talks Ba Assay
Pitt Conn 2012 Fi Cs As Invited Sers Talks Ba AssayPitt Conn 2012 Fi Cs As Invited Sers Talks Ba Assay
Pitt Conn 2012 Fi Cs As Invited Sers Talks Ba Assay
inscore
 
CLEO_AT-2014-AW1L.2
CLEO_AT-2014-AW1L.2CLEO_AT-2014-AW1L.2
CLEO_AT-2014-AW1L.2
Gen Vigil
 
Cavity Ring Down Spectroscopy - CRDS: Principle, Instrumentation and Results
Cavity Ring Down Spectroscopy - CRDS: Principle, Instrumentation and ResultsCavity Ring Down Spectroscopy - CRDS: Principle, Instrumentation and Results
Cavity Ring Down Spectroscopy - CRDS: Principle, Instrumentation and Results
Haseeb Gerraddict
 
fr2.t03.5.2-micron IPDA Presentation at IGARSS-2011-Final-Revised-1.pptx
fr2.t03.5.2-micron IPDA Presentation at IGARSS-2011-Final-Revised-1.pptxfr2.t03.5.2-micron IPDA Presentation at IGARSS-2011-Final-Revised-1.pptx
fr2.t03.5.2-micron IPDA Presentation at IGARSS-2011-Final-Revised-1.pptx
grssieee
 
Summer Research 2016_EVIL
Summer Research 2016_EVILSummer Research 2016_EVIL
Summer Research 2016_EVIL
Willie Zuniga
 
The relation between_gas_and_dust_in_the_taurus_molecular_cloud
The relation between_gas_and_dust_in_the_taurus_molecular_cloudThe relation between_gas_and_dust_in_the_taurus_molecular_cloud
The relation between_gas_and_dust_in_the_taurus_molecular_cloud
Sérgio Sacani
 

Tendances (20)

Calibration of spectrophotometer
Calibration of spectrophotometerCalibration of spectrophotometer
Calibration of spectrophotometer
 
A new single grating spectrograph for ultra violet raman scattering studies
A new single grating spectrograph for ultra violet raman scattering studiesA new single grating spectrograph for ultra violet raman scattering studies
A new single grating spectrograph for ultra violet raman scattering studies
 
Brief information for use nmr in geophysics1
Brief information for use nmr in geophysics1Brief information for use nmr in geophysics1
Brief information for use nmr in geophysics1
 
Atomic absorption spectroscopy
Atomic absorption spectroscopyAtomic absorption spectroscopy
Atomic absorption spectroscopy
 
Informe de enlace de radion enlace
Informe de enlace de radion enlaceInforme de enlace de radion enlace
Informe de enlace de radion enlace
 
Pitt Conn 2012 Fi Cs As Invited Sers Talks Ba Assay
Pitt Conn 2012 Fi Cs As Invited Sers Talks Ba AssayPitt Conn 2012 Fi Cs As Invited Sers Talks Ba Assay
Pitt Conn 2012 Fi Cs As Invited Sers Talks Ba Assay
 
CLEO_AT-2014-AW1L.2
CLEO_AT-2014-AW1L.2CLEO_AT-2014-AW1L.2
CLEO_AT-2014-AW1L.2
 
PhD Seminar David Dahan 2005
PhD Seminar David Dahan 2005PhD Seminar David Dahan 2005
PhD Seminar David Dahan 2005
 
Simpkins strong vibrational coupling - aps mar 2020
Simpkins   strong vibrational coupling - aps mar 2020Simpkins   strong vibrational coupling - aps mar 2020
Simpkins strong vibrational coupling - aps mar 2020
 
Analytical instruments introduction
Analytical instruments introductionAnalytical instruments introduction
Analytical instruments introduction
 
Cavity Ring Down Spectroscopy - CRDS: Principle, Instrumentation and Results
Cavity Ring Down Spectroscopy - CRDS: Principle, Instrumentation and ResultsCavity Ring Down Spectroscopy - CRDS: Principle, Instrumentation and Results
Cavity Ring Down Spectroscopy - CRDS: Principle, Instrumentation and Results
 
fr2.t03.5.2-micron IPDA Presentation at IGARSS-2011-Final-Revised-1.pptx
fr2.t03.5.2-micron IPDA Presentation at IGARSS-2011-Final-Revised-1.pptxfr2.t03.5.2-micron IPDA Presentation at IGARSS-2011-Final-Revised-1.pptx
fr2.t03.5.2-micron IPDA Presentation at IGARSS-2011-Final-Revised-1.pptx
 
Journal Discussions -Tip enhanced Raman spectroscopy imaging of opaque sample...
Journal Discussions -Tip enhanced Raman spectroscopy imaging of opaque sample...Journal Discussions -Tip enhanced Raman spectroscopy imaging of opaque sample...
Journal Discussions -Tip enhanced Raman spectroscopy imaging of opaque sample...
 
Summer Research 2016_EVIL
Summer Research 2016_EVILSummer Research 2016_EVIL
Summer Research 2016_EVIL
 
The relation between_gas_and_dust_in_the_taurus_molecular_cloud
The relation between_gas_and_dust_in_the_taurus_molecular_cloudThe relation between_gas_and_dust_in_the_taurus_molecular_cloud
The relation between_gas_and_dust_in_the_taurus_molecular_cloud
 
MODELLING AND ATMOSPHERIC ERRORS IN GPS SIGNAL PROPAGATION
MODELLING AND ATMOSPHERIC ERRORS IN GPS SIGNAL PROPAGATIONMODELLING AND ATMOSPHERIC ERRORS IN GPS SIGNAL PROPAGATION
MODELLING AND ATMOSPHERIC ERRORS IN GPS SIGNAL PROPAGATION
 
Spectroscopy chapter 9 textbook of organic chemistry arun bahl-
Spectroscopy chapter 9  textbook of organic chemistry arun bahl-Spectroscopy chapter 9  textbook of organic chemistry arun bahl-
Spectroscopy chapter 9 textbook of organic chemistry arun bahl-
 
Influence of artificial soiling on the power losses of different PV technologies
Influence of artificial soiling on the power losses of different PV technologiesInfluence of artificial soiling on the power losses of different PV technologies
Influence of artificial soiling on the power losses of different PV technologies
 
FOURIER TRANSFORM SPECTROSCOPY 1
FOURIER TRANSFORM SPECTROSCOPY 1FOURIER TRANSFORM SPECTROSCOPY 1
FOURIER TRANSFORM SPECTROSCOPY 1
 
Spectral data fusion for quantitative assessment of soils from Brazil, Dr. Fa...
Spectral data fusion for quantitative assessment of soils from Brazil, Dr. Fa...Spectral data fusion for quantitative assessment of soils from Brazil, Dr. Fa...
Spectral data fusion for quantitative assessment of soils from Brazil, Dr. Fa...
 

Similaire à Madagascar2011 - 07 - OTB radiometry processing

2004-10-14 AIR-257: Satellite Detection of Aerosols Concepts and Theory
2004-10-14 AIR-257: Satellite Detection of Aerosols Concepts and Theory2004-10-14 AIR-257: Satellite Detection of Aerosols Concepts and Theory
2004-10-14 AIR-257: Satellite Detection of Aerosols Concepts and Theory
Rudolf Husar
 
Retrieval & monitoring of atmospheric green house gases (gh gs) through remot...
Retrieval & monitoring of atmospheric green house gases (gh gs) through remot...Retrieval & monitoring of atmospheric green house gases (gh gs) through remot...
Retrieval & monitoring of atmospheric green house gases (gh gs) through remot...
debasishagri
 
2004-06-23 Retrieval of smoke aerosol loading from remote sensing data
2004-06-23 Retrieval of smoke aerosol loading from remote sensing data2004-06-23 Retrieval of smoke aerosol loading from remote sensing data
2004-06-23 Retrieval of smoke aerosol loading from remote sensing data
Rudolf Husar
 
Nakata_Mukai_IGARSS2011.ppt
Nakata_Mukai_IGARSS2011.pptNakata_Mukai_IGARSS2011.ppt
Nakata_Mukai_IGARSS2011.ppt
grssieee
 
2004-10-03 Co-retrieval of Aerosol and Surface Reflectance: Analysis of Daily...
2004-10-03 Co-retrieval of Aerosol and Surface Reflectance: Analysis of Daily...2004-10-03 Co-retrieval of Aerosol and Surface Reflectance: Analysis of Daily...
2004-10-03 Co-retrieval of Aerosol and Surface Reflectance: Analysis of Daily...
Rudolf Husar
 
2004-10-03 Co-retrieval of Aerosol and Surface Reflectance: Analysis of Daily...
2004-10-03 Co-retrieval of Aerosol and Surface Reflectance: Analysis of Daily...2004-10-03 Co-retrieval of Aerosol and Surface Reflectance: Analysis of Daily...
2004-10-03 Co-retrieval of Aerosol and Surface Reflectance: Analysis of Daily...
Rudolf Husar
 
2005-12-05 Aerosol Characterization Using the SeaWiFS Sensor and Surface Data
2005-12-05 Aerosol Characterization Using the SeaWiFS Sensor and Surface Data2005-12-05 Aerosol Characterization Using the SeaWiFS Sensor and Surface Data
2005-12-05 Aerosol Characterization Using the SeaWiFS Sensor and Surface Data
Rudolf Husar
 
1148_DAILY_ESTIMATES_OF_THE_TROPOSPHERIC_AEROSOL_OPTICAL_THICKNESS_OVER_LAND_...
1148_DAILY_ESTIMATES_OF_THE_TROPOSPHERIC_AEROSOL_OPTICAL_THICKNESS_OVER_LAND_...1148_DAILY_ESTIMATES_OF_THE_TROPOSPHERIC_AEROSOL_OPTICAL_THICKNESS_OVER_LAND_...
1148_DAILY_ESTIMATES_OF_THE_TROPOSPHERIC_AEROSOL_OPTICAL_THICKNESS_OVER_LAND_...
grssieee
 
1148_DAILY_ESTIMATES_OF_THE_TROPOSPHERIC_AEROSOL_OPTICAL_THICKNESS_OVER_LAND_...
1148_DAILY_ESTIMATES_OF_THE_TROPOSPHERIC_AEROSOL_OPTICAL_THICKNESS_OVER_LAND_...1148_DAILY_ESTIMATES_OF_THE_TROPOSPHERIC_AEROSOL_OPTICAL_THICKNESS_OVER_LAND_...
1148_DAILY_ESTIMATES_OF_THE_TROPOSPHERIC_AEROSOL_OPTICAL_THICKNESS_OVER_LAND_...
grssieee
 
Compiled presentations MOS
Compiled presentations MOSCompiled presentations MOS
Compiled presentations MOS
Roman Hodson
 

Similaire à Madagascar2011 - 07 - OTB radiometry processing (20)

Aerosol retrieval using modis data & rt code
Aerosol retrieval using modis data & rt codeAerosol retrieval using modis data & rt code
Aerosol retrieval using modis data & rt code
 
061018 Sea Wi Fs Work
061018 Sea Wi Fs Work061018 Sea Wi Fs Work
061018 Sea Wi Fs Work
 
1 Sat Intro
1 Sat Intro1 Sat Intro
1 Sat Intro
 
2004-10-14 AIR-257: Satellite Detection of Aerosols Concepts and Theory
2004-10-14 AIR-257: Satellite Detection of Aerosols Concepts and Theory2004-10-14 AIR-257: Satellite Detection of Aerosols Concepts and Theory
2004-10-14 AIR-257: Satellite Detection of Aerosols Concepts and Theory
 
Retrieval & monitoring of atmospheric green house gases (gh gs) through remot...
Retrieval & monitoring of atmospheric green house gases (gh gs) through remot...Retrieval & monitoring of atmospheric green house gases (gh gs) through remot...
Retrieval & monitoring of atmospheric green house gases (gh gs) through remot...
 
2004-06-23 Retrieval of smoke aerosol loading from remote sensing data
2004-06-23 Retrieval of smoke aerosol loading from remote sensing data2004-06-23 Retrieval of smoke aerosol loading from remote sensing data
2004-06-23 Retrieval of smoke aerosol loading from remote sensing data
 
Nakata_Mukai_IGARSS2011.ppt
Nakata_Mukai_IGARSS2011.pptNakata_Mukai_IGARSS2011.ppt
Nakata_Mukai_IGARSS2011.ppt
 
Smirnov_Algorithm.ppt
Smirnov_Algorithm.pptSmirnov_Algorithm.ppt
Smirnov_Algorithm.ppt
 
07 big skyearth_dlr_7_april_2016
07 big skyearth_dlr_7_april_201607 big skyearth_dlr_7_april_2016
07 big skyearth_dlr_7_april_2016
 
Raman spectroscopy
Raman spectroscopyRaman spectroscopy
Raman spectroscopy
 
0421026 Visib Satellite
0421026 Visib Satellite0421026 Visib Satellite
0421026 Visib Satellite
 
2004-10-03 Co-retrieval of Aerosol and Surface Reflectance: Analysis of Daily...
2004-10-03 Co-retrieval of Aerosol and Surface Reflectance: Analysis of Daily...2004-10-03 Co-retrieval of Aerosol and Surface Reflectance: Analysis of Daily...
2004-10-03 Co-retrieval of Aerosol and Surface Reflectance: Analysis of Daily...
 
2004-10-03 Co-retrieval of Aerosol and Surface Reflectance: Analysis of Daily...
2004-10-03 Co-retrieval of Aerosol and Surface Reflectance: Analysis of Daily...2004-10-03 Co-retrieval of Aerosol and Surface Reflectance: Analysis of Daily...
2004-10-03 Co-retrieval of Aerosol and Surface Reflectance: Analysis of Daily...
 
Radar
RadarRadar
Radar
 
2005-12-05 Aerosol Characterization Using the SeaWiFS Sensor and Surface Data
2005-12-05 Aerosol Characterization Using the SeaWiFS Sensor and Surface Data2005-12-05 Aerosol Characterization Using the SeaWiFS Sensor and Surface Data
2005-12-05 Aerosol Characterization Using the SeaWiFS Sensor and Surface Data
 
1148_DAILY_ESTIMATES_OF_THE_TROPOSPHERIC_AEROSOL_OPTICAL_THICKNESS_OVER_LAND_...
1148_DAILY_ESTIMATES_OF_THE_TROPOSPHERIC_AEROSOL_OPTICAL_THICKNESS_OVER_LAND_...1148_DAILY_ESTIMATES_OF_THE_TROPOSPHERIC_AEROSOL_OPTICAL_THICKNESS_OVER_LAND_...
1148_DAILY_ESTIMATES_OF_THE_TROPOSPHERIC_AEROSOL_OPTICAL_THICKNESS_OVER_LAND_...
 
1148_DAILY_ESTIMATES_OF_THE_TROPOSPHERIC_AEROSOL_OPTICAL_THICKNESS_OVER_LAND_...
1148_DAILY_ESTIMATES_OF_THE_TROPOSPHERIC_AEROSOL_OPTICAL_THICKNESS_OVER_LAND_...1148_DAILY_ESTIMATES_OF_THE_TROPOSPHERIC_AEROSOL_OPTICAL_THICKNESS_OVER_LAND_...
1148_DAILY_ESTIMATES_OF_THE_TROPOSPHERIC_AEROSOL_OPTICAL_THICKNESS_OVER_LAND_...
 
lecture3.pptx
lecture3.pptxlecture3.pptx
lecture3.pptx
 
Compiled presentations MOS
Compiled presentations MOSCompiled presentations MOS
Compiled presentations MOS
 
Poster gss
Poster gssPoster gss
Poster gss
 

Plus de otb

ONLINE IMAGE PROCESSING WITH ORFEOTOOLBOX WPS
ONLINE IMAGE PROCESSING WITH ORFEOTOOLBOX WPSONLINE IMAGE PROCESSING WITH ORFEOTOOLBOX WPS
ONLINE IMAGE PROCESSING WITH ORFEOTOOLBOX WPS
otb
 
0 intro
0 intro0 intro
0 intro
otb
 
Madagascar2011 - 09 OTB Change detection framework
Madagascar2011 - 09 OTB Change detection frameworkMadagascar2011 - 09 OTB Change detection framework
Madagascar2011 - 09 OTB Change detection framework
otb
 

Plus de otb (20)

General presentation of OTB
General presentation of OTBGeneral presentation of OTB
General presentation of OTB
 
Orfeo ToolBox workshop at FOSS4G Europe 2015
Orfeo ToolBox workshop at FOSS4G Europe 2015Orfeo ToolBox workshop at FOSS4G Europe 2015
Orfeo ToolBox workshop at FOSS4G Europe 2015
 
Ice: lightweight, efficient rendering for remote sensing images
Ice: lightweight, efficient rendering for remote sensing imagesIce: lightweight, efficient rendering for remote sensing images
Ice: lightweight, efficient rendering for remote sensing images
 
Développement des chaînes de traitement d'images GEOSUD
Développement des chaînes de traitement d'images GEOSUDDéveloppement des chaînes de traitement d'images GEOSUD
Développement des chaînes de traitement d'images GEOSUD
 
ONLINE IMAGE PROCESSING WITH ORFEOTOOLBOX WPS
ONLINE IMAGE PROCESSING WITH ORFEOTOOLBOX WPSONLINE IMAGE PROCESSING WITH ORFEOTOOLBOX WPS
ONLINE IMAGE PROCESSING WITH ORFEOTOOLBOX WPS
 
Build OTB with the SuperBuild
Build OTB with the SuperBuildBuild OTB with the SuperBuild
Build OTB with the SuperBuild
 
ORFEO ToolBox Project Steering committee
ORFEO ToolBox Project Steering committeeORFEO ToolBox Project Steering committee
ORFEO ToolBox Project Steering committee
 
OTB modular architecture
OTB modular architectureOTB modular architecture
OTB modular architecture
 
0 intro
0 intro0 intro
0 intro
 
ORFEO ToolBox at CS-SI From research to operational applications
ORFEO ToolBox at CS-SI From research to operational applicationsORFEO ToolBox at CS-SI From research to operational applications
ORFEO ToolBox at CS-SI From research to operational applications
 
Usages of OTB at SERTIT OTB Users meeting and hackfest 2015
Usages of OTB at SERTIT OTB Users meeting and hackfest 2015Usages of OTB at SERTIT OTB Users meeting and hackfest 2015
Usages of OTB at SERTIT OTB Users meeting and hackfest 2015
 
USING ORFEO TOOLBOX A GROWING COMPETENCE IN A COLLABORATIVE ENVIRONMENT
USING ORFEO TOOLBOX A GROWING COMPETENCE IN A COLLABORATIVE ENVIRONMENTUSING ORFEO TOOLBOX A GROWING COMPETENCE IN A COLLABORATIVE ENVIRONMENT
USING ORFEO TOOLBOX A GROWING COMPETENCE IN A COLLABORATIVE ENVIRONMENT
 
Teaching Remote Sensing with OTB Applications & Monterverdi (and a little of ...
Teaching Remote Sensing with OTB Applications & Monterverdi (and a little of ...Teaching Remote Sensing with OTB Applications & Monterverdi (and a little of ...
Teaching Remote Sensing with OTB Applications & Monterverdi (and a little of ...
 
Monitoring tropical forest cover Activities of ONFI in remote sensing
Monitoring tropical forest cover Activities of ONFI in remote sensingMonitoring tropical forest cover Activities of ONFI in remote sensing
Monitoring tropical forest cover Activities of ONFI in remote sensing
 
Présentation générale de l'Orfeo ToolBox (12.2014)
Présentation générale de l'Orfeo ToolBox (12.2014)Présentation générale de l'Orfeo ToolBox (12.2014)
Présentation générale de l'Orfeo ToolBox (12.2014)
 
Monteverdi 2.0 - Remote sensing software for Pleiades images analysis
Monteverdi 2.0 - Remote sensing software for Pleiades images analysisMonteverdi 2.0 - Remote sensing software for Pleiades images analysis
Monteverdi 2.0 - Remote sensing software for Pleiades images analysis
 
OTB: logiciel libre de traitement d'images satellites
OTB: logiciel libre de traitement d'images satellitesOTB: logiciel libre de traitement d'images satellites
OTB: logiciel libre de traitement d'images satellites
 
Présentation de l'ORFEO ToolBox au FROG2013
Présentation de l'ORFEO ToolBox au FROG2013Présentation de l'ORFEO ToolBox au FROG2013
Présentation de l'ORFEO ToolBox au FROG2013
 
Pragmatic remote sensing handout
Pragmatic remote sensing handoutPragmatic remote sensing handout
Pragmatic remote sensing handout
 
Madagascar2011 - 09 OTB Change detection framework
Madagascar2011 - 09 OTB Change detection frameworkMadagascar2011 - 09 OTB Change detection framework
Madagascar2011 - 09 OTB Change detection framework
 

Dernier

Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Safe Software
 

Dernier (20)

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
 
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
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt Robison
 
Powerful Google developer tools for immediate impact! (2023-24 C)
Powerful Google developer tools for immediate impact! (2023-24 C)Powerful Google developer tools for immediate impact! (2023-24 C)
Powerful Google developer tools for immediate impact! (2023-24 C)
 
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost SavingRepurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
 
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
 
A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?
 
Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...
 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processors
 
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
 
A Beginners Guide to Building a RAG App Using Open Source Milvus
A Beginners Guide to Building a RAG App Using Open Source MilvusA Beginners Guide to Building a RAG App Using Open Source Milvus
A Beginners Guide to Building a RAG App Using Open Source Milvus
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
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
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Script
 
GenAI Risks & Security Meetup 01052024.pdf
GenAI Risks & Security Meetup 01052024.pdfGenAI Risks & Security Meetup 01052024.pdf
GenAI Risks & Security Meetup 01052024.pdf
 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdf
 
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 Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
 
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
 
MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024
 

Madagascar2011 - 07 - OTB radiometry processing

  • 1. Orfeo Toolbox Radiometric corrections Stéphane MAY stephane.may@cnes.fr orfeo-toolbox.org 1
  • 2. Radiometry Radiometry = science of electromagnetic radiations Interest for Remote Sensing Physical interpretation of signals Enhance detection Estimate physical values related to ground and / or atmospheric effects orfeo-toolbox.org 2
  • 3. Radiometry : from DN to TOA reflectance Goal : using physical measures TOA reflectance (Top of Atmosphere) TOC reflectance (Top of Canopy) Calibration of images : DN (digital numbers) converted into TOA reflectance Application of calibration coefficient inserted into metadata files → Luminance Normalisation with solar effect → Reflectance Example for Spot : orfeo-toolbox.org 3
  • 4. Luminance orfeo-toolbox.org 4
  • 5. Luminance Definition Emitted power per unit area and per unit solid angle Unit W.m-2.sr-1 Numerical example: Luminance of the sky (visible): ~ 6 W.m-2.sr-1 orfeo-toolbox.org 5
  • 6. TOA reflectance orfeo-toolbox.org 6
  • 7. Radiometry : from TOA reflectance to TOC reflectance Atmospheric correction : inversion of surface TOC reflectance Need to caracterise atmospheric conditions ➢TOMS / TOAST data : (grid : 1,25°lon x 1°lat ~ 135 x 110 km) : stratospheric Ozone amount NCEP meteo data : (grid : 2,5°lon x 2,5°lat ~ 270 x 270 km) : Atmospheric Pressuree, water vapor, wetness SeaWiFS or MODIS data : (grid : 5’ x 5’ ~ 9 x 9 km) ) : Optical aerosols thickness Cimel of aeronet network : information about aerosols, and water amount Absorption Ozone Scattering Cloud Emission Water vapor Molecules Aerosols Reflection orfeo-toolbox.org 7
  • 8. Atmospheric effects Atmosphere Thickness ~100 km Filter descending and ascending radiations Composition of the atmosphere: Molecules nitrogen (78%), oxygen (21%), argon, carbon oxides, ozone, water vapor (highly variable, even locally) ... Aerosols small solid or liquid particles suspended in the atmosphere. Microparticles, water particles, ice crystals, smoke ... Dimensions: mainly from 0.1 to 10 µm Abundance and type varies geographically and with time orfeo-toolbox.org 8
  • 9. Atmospheric effects Altitude (km) EXOSPHERE 800 THERMOSPHERE -90°C 85 Mesopause Profil de Températures MESOSPHERE 50 Stratopause 0°C STRATOSPHERE Ozone 10 Tropopause -55°C TROPOSPHERE Nuages Aérosols Vapeur d'eau +15°C 0 Sol orfeo-toolbox.org 9
  • 10. Atmospheric effects orfeo-toolbox.org 10
  • 11. Atmospheric effects Three main phenomena, depending of wavelength Absorption Diffusion (in the visible and NIR, up to ~ 3 µm) Emission (in the thermic IR, from ~ 3 µm) Optional : refraction, usually neglected for high elevation acquisition and not included spatial resolutions greater than 10 cm The contribution of the signal from the ground in the measured signal is disturbed by filtering effects and luminance of the atmosphere Need to correct measures Need to understand the phenomena orfeo-toolbox.org 11
  • 12. Radiometry : 6S model Atmospheric corrections : invert the TOC surface reflectance. Simulation with radiative transfer code 6S code Diffusion : code of the successive diffusion orders Absorptions : O2, CO2, H2O, O3, N2O, CH4 Spectro data at 10 cm-1« AFGL atmospheric absorption line parameters compilation » (1991) Look-Up Tables : refl. TOC -> TOA Mesure ρTOA Simulations TOA Géo d’observation Conditions atmosphériques ρTOC 0 0,01 0,02 0,03 0,8 Valeur sol interpolée orfeo-toolbox.org 12
  • 14. Radiometry : 6S parameters Atmospheric parameters => parameters of radiative transfer The zenithal and azimutal solar angles that describe the solar incidence configuration (in degrees) The zenithal and azimuthal viewing angles that describe the viewing direction (in degrees) The month and the day of the acquisition The atmospheric pressure The water vapor amount, that is, the total water vapor content over vertical atmospheric column orfeo-toolbox.org 14
  • 15. Radiometry : 6S parameters Atmospheric parameters => parameters of radiative transfer The ozone amount that is the Stratospheric ozone layer content; The aerosol model that is the kind of particles (no aerosol, continental, maritime, urban, desertic) The aerosol optical thickness at 550 nm that is the is the Radiative impact of aerosol for the reference wavelength 550 nm The filter function that is the values of the filter function for one spectral band, from λinf to λsup by step of 2.5 nm. One filter function by channel is required. This last parameter are read in text files, the other one are directly given to the class. orfeo-toolbox.org 15
  • 16. Radiometry : 6S parameters Spectral sensitivity file Data provided in OTB-Data (not with Monteverdi) ➢OTB-Data/Input/Radiometry/ For each band with a step of 0.25 nm, the spectral band sensitivity of the instrument ➢Input file : values in the Atmospheric parameters window ➢No input file : iso sensitivity (1 everywhere) or default file automatically loaded (>OTB V3.10) orfeo-toolbox.org 16
  • 17. Aeronet data AERONET (AErosol RObotic NETwork) This program is a federation of ground-based remote sensing aerosol networks established by NASA and LOA-PHOTONS (CNRS) and is greatly expanded by collaborators orfeo-toolbox.org 17
  • 18. Aeronet data and OTB Aerosol optical depth data are computed for three data quality levels Level 1.0 (unscreened) Level 1.5 (cloud-screened) Level 2.0 (cloud screened and quality-assured). Extract Aerosol thickness (épaisseur) and Water amount Download site http://aeronet.gsfc.nasa.gov/cgi-bin/webtool_opera_v2_new orfeo-toolbox.org 18
  • 19. Radiometry – Reference reflectances Mesure of the reflectance of a source Principle : use a source and measure reflected luminance ➢ Direct measure : known source ➢ Indirect measure : use of a known reference reflectance surface (spectralon, or BaSO4) Measures in laboratory ➢ Artificial source : directional, mobile (lamp, laser) ➢ Sensor (radiometer or spectro-radiometer) : mobile Direct measure or indirect measure orfeo-toolbox.org 19
  • 20. Radiometry Spectral signature of the chlorophyllian vegetation Proche Visible Moyen Infra-Rouge Infra-Rouge REFLECTION due à : pigment Structure Teneur en eau de la feuille cellulaire ABSORPTION due à : Chlorophylle Eau Longueur d’onde (µm) orfeo-toolbox.org 20
  • 21. Radiometry processing - Synthesis 3 processing steps Digital Number to Luminance Luminance to TOA reflectance TOA reflectance to TOC surface reflectance Many parameters available in the metadata of sensors Importance of aerosols to quantify the effects of the atmosphere Difficulties Aerosol model used? Validation of results? Ground truth? orfeo-toolbox.org 21
  • 22. Optical calibration module (1/2) orfeo-toolbox.org 22
  • 23. Optical calibration module (2/2) orfeo-toolbox.org 23
  • 24. Use case 1 : radiometric correction Menu File > Open ./img_kalideos_reunion/2009-03-21/IMAGERY.TIF Menu Calibration > Optical calibration Load Aeronet file ➢ ./aeronet/070101_091231_REUNION_ST_DENIS.lev20 Load spectral sensity file ➢ ./OTB-Data/Input/Radiometry/SPOT5/HRG1/rep6S.dat Change correction parameters Change Radiative terms Save / quit File > Save (Luminance, TOA, TOC, TOA-TOC files) Repeat the Calibration process with other parameters set Visualization > Viewer : compare results orfeo-toolbox.org 24
  • 25. Use case 1b : radiometric correction Use the commande line tool : OtbOpticalCalibration-cli -h otbOpticalCalibration-cli -in IMAGERY.TIF -out img_toc.tif -level TOC -AerosolModel 0 –OzoneAmount 0 --AtmosphericPressure 1030 --AerosolOptical 0.0329 –WaterVaporAmount 4.226 -aeronet file.lev20 -srs rep6S.dat orfeo-toolbox.org 25
  • 26. Spectral viewer (1/2) orfeo-toolbox.org 26
  • 27. Spectral viewer (2/2) orfeo-toolbox.org 27
  • 28. Use case 2 : Spectral viewer Menu File > Open ./img_kalideos_reunion/2009-03-21/IMAGERY.TIF Menu Viewer > Spectral viewer Left click : select your area Right click : select pixel Spectral angle menu > Select one curve ID ➢ Click on Compute button File > Save (the Spectral angle file). Use Float data type Create several reference spectral angle images : roads, houses, sea, clouds, vegetation, bare soil orfeo-toolbox.org 28
  • 29. Monteverdi Thank you for your attention ! orfeo-toolbox.org 29