APPROACHES FOR
ATMOSPHERIC
CORRECTION
NIRMAL KUMAR
AP140
Atmospheric correction
relationship between radiance
received at the sensor (above
atmosphere) and radiance
leaving the ground
Ls =HρT + Lp
To retrieve surface reflectance from RS imagery
Ls ndash at sensor radiance
H ndash total downwelling radiance
ρ ndash reflectance of target
T ndash atmospheric transmittance
Lp ndash atmospheric path radiance
(wavelength dependent)
Why do atmospheric correction
Physical relation of radiance to surface property (surface normal surface roughness reflectance)
Atmospheric component needs to be removed
Image ratios (NDVI) leads to biased estimate Scattering increases inversely with wavelength
The involved channels will be unequally affected
Time difference between image acquisition and ground truth measurements
Comparison of RS data captured at different times Conditions may be different
Atmospheric correction methods
Image ndash based methods
Dark pixel method
Regression method
Empirical line method
Radiative transfer models
Relative correction method (PIFs)
Dark pixel subtraction methodLs =HρT + Lp
Pixel values of low reflectance areas near zero Exposure of dark colored rocks
Deep shadows
Clear water
Lowest pixel values in visible and NIR are approximation to atmospheric path radiance
Minimum values subtracted from image
Regression method
NIR pixel values are plotted against values in other bands
Apply a straight line using the least square
method
If there was no haze the line would pass through origin
resulting offset is approximation for atmospheric path radiance
offset subtracted from image
Empirical line correction method
Use target of ldquoknownrdquo low and high reflectance
targets in one channel eg non-turbid water amp desert
or dense dark vegetation amp snow
Assume radiance L = gain DN + offset
Offset is assumed to be atmospheric part of signal
Target DN values
DN
Radiance L
Regression line L = GDN + O
Offset assumed to be atmospheric
path radiance
Conversion of DNs to absolute
radiance value
3 stepsbull Convert DN to apparent radiance Lapp
bull Convert Lapp to apparent reflectance (knowing
response of sensor)
bull Convert to at-ground reflectance ie intrinsic surface
property by accounting for atmosphere
Use Radiative transfer models
Radiative transfer models
Limited by the need to supply data about
atmospheric conditions at time of acquisition
Mostly used with standard atmospheres
Available numerical models 1048696 LOWTRAN 7
1048696 MODTRAN 4
1048696 ATREM
1048696 ATCOR
1048696 6S (Second Simulation of the Satellite Signal in
the solar spectrum)
THANK YOU
Atmospheric correction
relationship between radiance
received at the sensor (above
atmosphere) and radiance
leaving the ground
Ls =HρT + Lp
To retrieve surface reflectance from RS imagery
Ls ndash at sensor radiance
H ndash total downwelling radiance
ρ ndash reflectance of target
T ndash atmospheric transmittance
Lp ndash atmospheric path radiance
(wavelength dependent)
Why do atmospheric correction
Physical relation of radiance to surface property (surface normal surface roughness reflectance)
Atmospheric component needs to be removed
Image ratios (NDVI) leads to biased estimate Scattering increases inversely with wavelength
The involved channels will be unequally affected
Time difference between image acquisition and ground truth measurements
Comparison of RS data captured at different times Conditions may be different
Atmospheric correction methods
Image ndash based methods
Dark pixel method
Regression method
Empirical line method
Radiative transfer models
Relative correction method (PIFs)
Dark pixel subtraction methodLs =HρT + Lp
Pixel values of low reflectance areas near zero Exposure of dark colored rocks
Deep shadows
Clear water
Lowest pixel values in visible and NIR are approximation to atmospheric path radiance
Minimum values subtracted from image
Regression method
NIR pixel values are plotted against values in other bands
Apply a straight line using the least square
method
If there was no haze the line would pass through origin
resulting offset is approximation for atmospheric path radiance
offset subtracted from image
Empirical line correction method
Use target of ldquoknownrdquo low and high reflectance
targets in one channel eg non-turbid water amp desert
or dense dark vegetation amp snow
Assume radiance L = gain DN + offset
Offset is assumed to be atmospheric part of signal
Target DN values
DN
Radiance L
Regression line L = GDN + O
Offset assumed to be atmospheric
path radiance
Conversion of DNs to absolute
radiance value
3 stepsbull Convert DN to apparent radiance Lapp
bull Convert Lapp to apparent reflectance (knowing
response of sensor)
bull Convert to at-ground reflectance ie intrinsic surface
property by accounting for atmosphere
Use Radiative transfer models
Radiative transfer models
Limited by the need to supply data about
atmospheric conditions at time of acquisition
Mostly used with standard atmospheres
Available numerical models 1048696 LOWTRAN 7
1048696 MODTRAN 4
1048696 ATREM
1048696 ATCOR
1048696 6S (Second Simulation of the Satellite Signal in
the solar spectrum)
THANK YOU
Why do atmospheric correction
Physical relation of radiance to surface property (surface normal surface roughness reflectance)
Atmospheric component needs to be removed
Image ratios (NDVI) leads to biased estimate Scattering increases inversely with wavelength
The involved channels will be unequally affected
Time difference between image acquisition and ground truth measurements
Comparison of RS data captured at different times Conditions may be different
Atmospheric correction methods
Image ndash based methods
Dark pixel method
Regression method
Empirical line method
Radiative transfer models
Relative correction method (PIFs)
Dark pixel subtraction methodLs =HρT + Lp
Pixel values of low reflectance areas near zero Exposure of dark colored rocks
Deep shadows
Clear water
Lowest pixel values in visible and NIR are approximation to atmospheric path radiance
Minimum values subtracted from image
Regression method
NIR pixel values are plotted against values in other bands
Apply a straight line using the least square
method
If there was no haze the line would pass through origin
resulting offset is approximation for atmospheric path radiance
offset subtracted from image
Empirical line correction method
Use target of ldquoknownrdquo low and high reflectance
targets in one channel eg non-turbid water amp desert
or dense dark vegetation amp snow
Assume radiance L = gain DN + offset
Offset is assumed to be atmospheric part of signal
Target DN values
DN
Radiance L
Regression line L = GDN + O
Offset assumed to be atmospheric
path radiance
Conversion of DNs to absolute
radiance value
3 stepsbull Convert DN to apparent radiance Lapp
bull Convert Lapp to apparent reflectance (knowing
response of sensor)
bull Convert to at-ground reflectance ie intrinsic surface
property by accounting for atmosphere
Use Radiative transfer models
Radiative transfer models
Limited by the need to supply data about
atmospheric conditions at time of acquisition
Mostly used with standard atmospheres
Available numerical models 1048696 LOWTRAN 7
1048696 MODTRAN 4
1048696 ATREM
1048696 ATCOR
1048696 6S (Second Simulation of the Satellite Signal in
the solar spectrum)
THANK YOU
Atmospheric correction methods
Image ndash based methods
Dark pixel method
Regression method
Empirical line method
Radiative transfer models
Relative correction method (PIFs)
Dark pixel subtraction methodLs =HρT + Lp
Pixel values of low reflectance areas near zero Exposure of dark colored rocks
Deep shadows
Clear water
Lowest pixel values in visible and NIR are approximation to atmospheric path radiance
Minimum values subtracted from image
Regression method
NIR pixel values are plotted against values in other bands
Apply a straight line using the least square
method
If there was no haze the line would pass through origin
resulting offset is approximation for atmospheric path radiance
offset subtracted from image
Empirical line correction method
Use target of ldquoknownrdquo low and high reflectance
targets in one channel eg non-turbid water amp desert
or dense dark vegetation amp snow
Assume radiance L = gain DN + offset
Offset is assumed to be atmospheric part of signal
Target DN values
DN
Radiance L
Regression line L = GDN + O
Offset assumed to be atmospheric
path radiance
Conversion of DNs to absolute
radiance value
3 stepsbull Convert DN to apparent radiance Lapp
bull Convert Lapp to apparent reflectance (knowing
response of sensor)
bull Convert to at-ground reflectance ie intrinsic surface
property by accounting for atmosphere
Use Radiative transfer models
Radiative transfer models
Limited by the need to supply data about
atmospheric conditions at time of acquisition
Mostly used with standard atmospheres
Available numerical models 1048696 LOWTRAN 7
1048696 MODTRAN 4
1048696 ATREM
1048696 ATCOR
1048696 6S (Second Simulation of the Satellite Signal in
the solar spectrum)
THANK YOU
Dark pixel subtraction methodLs =HρT + Lp
Pixel values of low reflectance areas near zero Exposure of dark colored rocks
Deep shadows
Clear water
Lowest pixel values in visible and NIR are approximation to atmospheric path radiance
Minimum values subtracted from image
Regression method
NIR pixel values are plotted against values in other bands
Apply a straight line using the least square
method
If there was no haze the line would pass through origin
resulting offset is approximation for atmospheric path radiance
offset subtracted from image
Empirical line correction method
Use target of ldquoknownrdquo low and high reflectance
targets in one channel eg non-turbid water amp desert
or dense dark vegetation amp snow
Assume radiance L = gain DN + offset
Offset is assumed to be atmospheric part of signal
Target DN values
DN
Radiance L
Regression line L = GDN + O
Offset assumed to be atmospheric
path radiance
Conversion of DNs to absolute
radiance value
3 stepsbull Convert DN to apparent radiance Lapp
bull Convert Lapp to apparent reflectance (knowing
response of sensor)
bull Convert to at-ground reflectance ie intrinsic surface
property by accounting for atmosphere
Use Radiative transfer models
Radiative transfer models
Limited by the need to supply data about
atmospheric conditions at time of acquisition
Mostly used with standard atmospheres
Available numerical models 1048696 LOWTRAN 7
1048696 MODTRAN 4
1048696 ATREM
1048696 ATCOR
1048696 6S (Second Simulation of the Satellite Signal in
the solar spectrum)
THANK YOU
Regression method
NIR pixel values are plotted against values in other bands
Apply a straight line using the least square
method
If there was no haze the line would pass through origin
resulting offset is approximation for atmospheric path radiance
offset subtracted from image
Empirical line correction method
Use target of ldquoknownrdquo low and high reflectance
targets in one channel eg non-turbid water amp desert
or dense dark vegetation amp snow
Assume radiance L = gain DN + offset
Offset is assumed to be atmospheric part of signal
Target DN values
DN
Radiance L
Regression line L = GDN + O
Offset assumed to be atmospheric
path radiance
Conversion of DNs to absolute
radiance value
3 stepsbull Convert DN to apparent radiance Lapp
bull Convert Lapp to apparent reflectance (knowing
response of sensor)
bull Convert to at-ground reflectance ie intrinsic surface
property by accounting for atmosphere
Use Radiative transfer models
Radiative transfer models
Limited by the need to supply data about
atmospheric conditions at time of acquisition
Mostly used with standard atmospheres
Available numerical models 1048696 LOWTRAN 7
1048696 MODTRAN 4
1048696 ATREM
1048696 ATCOR
1048696 6S (Second Simulation of the Satellite Signal in
the solar spectrum)
THANK YOU
Empirical line correction method
Use target of ldquoknownrdquo low and high reflectance
targets in one channel eg non-turbid water amp desert
or dense dark vegetation amp snow
Assume radiance L = gain DN + offset
Offset is assumed to be atmospheric part of signal
Target DN values
DN
Radiance L
Regression line L = GDN + O
Offset assumed to be atmospheric
path radiance
Conversion of DNs to absolute
radiance value
3 stepsbull Convert DN to apparent radiance Lapp
bull Convert Lapp to apparent reflectance (knowing
response of sensor)
bull Convert to at-ground reflectance ie intrinsic surface
property by accounting for atmosphere
Use Radiative transfer models
Radiative transfer models
Limited by the need to supply data about
atmospheric conditions at time of acquisition
Mostly used with standard atmospheres
Available numerical models 1048696 LOWTRAN 7
1048696 MODTRAN 4
1048696 ATREM
1048696 ATCOR
1048696 6S (Second Simulation of the Satellite Signal in
the solar spectrum)
THANK YOU
Conversion of DNs to absolute
radiance value
3 stepsbull Convert DN to apparent radiance Lapp
bull Convert Lapp to apparent reflectance (knowing
response of sensor)
bull Convert to at-ground reflectance ie intrinsic surface
property by accounting for atmosphere
Use Radiative transfer models
Radiative transfer models
Limited by the need to supply data about
atmospheric conditions at time of acquisition
Mostly used with standard atmospheres
Available numerical models 1048696 LOWTRAN 7
1048696 MODTRAN 4
1048696 ATREM
1048696 ATCOR
1048696 6S (Second Simulation of the Satellite Signal in
the solar spectrum)
THANK YOU
Radiative transfer models
Limited by the need to supply data about
atmospheric conditions at time of acquisition
Mostly used with standard atmospheres
Available numerical models 1048696 LOWTRAN 7
1048696 MODTRAN 4
1048696 ATREM
1048696 ATCOR
1048696 6S (Second Simulation of the Satellite Signal in
the solar spectrum)
THANK YOU
THANK YOU