10
APPROACHES FOR ATMOSPHERIC CORRECTION NIRMAL KUMAR AP:140

Atmospheric correction

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Page 1: Atmospheric correction

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

Page 2: Atmospheric correction

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

Page 3: Atmospheric correction

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

Page 4: Atmospheric correction

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

Page 5: Atmospheric correction

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

Page 6: Atmospheric correction

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

Page 7: Atmospheric correction

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

Page 8: Atmospheric correction

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

Page 9: Atmospheric correction

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

Page 10: Atmospheric correction

THANK YOU