Dear Shouvik Jha,

Unfortunately hard to say exactly what is the best for you. 

In theory, for coastal zones 6S algorithm (available in ERDAS ATCOR, GRASS GIS i.atcorr), providing correction for aerosols is needed to get appropriate results. ENVI FLAASH  module (MODTRAN) is also commonly used.

In practice...one of DOS methods may be enough for certain site.

There are different methods for atmospheric correction accuracy assesment depend on the aims of your study.

See some papers below as the examples.

Hope it helps,

Regards,

Maria

1. Steven Vanonckelena, Stefaan Lhermitteb, Anton Van Rompaeya. The effect of atmospheric and topographic correction methods on land cover classification accuracy. International Journal of Applied Earth Observation and Geoinformation 24 (2013) 9–21

Hi Shouvik,

It is really hard to say which method is the best. It largely depends on the objectives of your study. The paper 2001 paper by Song et al. (provided by Maria above) is a good reference to start with.

In addition, here are links to a couple of papers that provide examples on atmospheric corrections applied to Landsat imagery, particularly Landsat 8:

Ke et al. (2015): Characteristics of Landsat 8 OLI-derived NDVI by comparison with multiple satellite sensors and in-situ observations (http://dx.doi.org/10.1016/j.rse.2015.04.004)

Estoque & Murayama (2015): Intensity and spatial pattern of urban land changes in the megacities of Southeast Asia (http://dx.doi.org/10.1016/j.landusepol.2015.05.017)

I hope this helps.

Best, Don

Dear Shouvik,

The DOS and FLAASH are totally different methods, i.e. DOS is an image based method which do not consider the atmospheric conditions which were there during the image acquisition, while on the other hand FLAASH considers different atmospheric parameters (e.g. Visibility, Aerosol types, solar zenith and azimuth angles etc). Attached is a paper for further reading and selection of a best atmospheric correction method over an urban coastal environment.

Really, if you don't have any other choice, then I would suggest to use FLAASH.

Best of luck!

Article Evaluation of atmospheric correction models and Landsat surf...

I am the person who developed the 'Improved DOS' and 'COST' atmospheric corrections models (the COST model is in the paper titled 'Image Based Atmospheric Corrections --- revisited and improved' published in 1996). Keep in mind that either the DOS or COST corrections can be done with a simple stretch function which all software package contain somewhere within their tool boxes of processing procedures.

A very critical aspect of image based correction models, such as these two, is that a 'VALID DARK OBJECT' that can be used to compute the haze values exist within the image. At times the minimum DN value of the image is used blindly as the dark object for atmospheric haze corrections which can lead to over correcting for haze and the surface reflectance values will be under estimated. Perhaps the links below might be useful to you:

Link to slides about Radiometric Calibration and Atmospheric corrections using DOS / Improved DOS / COST models:

https://www.researchgate.net/publication/275042873_Presentation_-_Radiometric_Calibration_and_Atmospheric_Corrections

Link to COST paper:

https://www.researchgate.net/publication/236769129_Image-Based_Atmospheric_Corrections_-_Revisited_and_Improved

Link to the Improved DOS paper:

https://www.researchgate.net/publication/223795843_Chavez_PS._An_improved_dark-object_subtraction_technique_for_atmospheric_scattering_correction_of_multispectral_data._Remote_Sensing_of_Environment

Data Presentation - Radiometric Calibration and Atmospheric Corrections

Article Image-Based Atmospheric Corrections - Revisited and Improved

Article An improved dark-object subtraction technique for atmospheri...

Dear Shouvik Jha,

If you just want to use Landsat reflectance product rather than compare different atmospheric correction methods, you can directly download reflectance product from USGS http://landsat.usgs.gov/CDR_LSR.php. They are generated by LEDAPS.

Xiaolin

Dark Object Subtraction

– assumes that the atmosphere is horizontally uniform over the image

– atmospheric correction limited to removal of path radiance effects.

– not a true atmospheric correction, only an "adjustment"