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Atmospheric Correction for Smoke


ben-jamin

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Hi all,

 

I am a research intern researching atmospheric correction for smoke, because a lot of the data AVIRIS has given me has smoke in them from wildfires in CA. My study has been using FLAASH and I am trying to see if I can find a set of parameters that best correct for smoke, and I am wondering if anyone here has any good suggestions for settings I should try. Also I have been noticing that overall FLAASH has been doing a really poor job at correcting for smoke in general, does anyone have a reason why or what part of the theory that makes up FLAASH could be failing at modeling smoke? I hope to try ATCOR too hopefully and do the same thing I'm doing for FLAASH. 

 

Thanks,

 

Ben

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Hi all,

 

I am a research intern researching atmospheric correction for smoke, because a lot of the data AVIRIS has given me has smoke in them from wildfires in CA. My study has been using FLAASH and I am trying to see if I can find a set of parameters that best correct for smoke, and I am wondering if anyone here has any good suggestions for settings I should try. Also I have been noticing that overall FLAASH has been doing a really poor job at correcting for smoke in general, does anyone have a reason why or what part of the theory that makes up FLAASH could be failing at modeling smoke? I hope to try ATCOR too hopefully and do the same thing I'm doing for FLAASH. 

 

Thanks,

 

Ben

 

I fear it will be impossible to filter the smoke from a hyperspectral image any way.

 

Greetings,

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  • 2 weeks later...

The FLAASH algorithm isn't the issue, it's the smoke.  Smoke is an aerosol that has major attenuation effects at all optical wavelengths.  There is no radiative transfer model out there, be it FLAASH, MODTRAN, 6S, etc. that will model at-surface reflectance if the sensor and specified wavelength cannot see the reflected surface.  Furthermore, this is exacerbated by the narrow channels (lower reflected energy captured) on hyperspectral sensors.

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