Atmospheric correction is the process of removing the scattering and absorption effects of the atmosphere on the reflectance values of images taken by satellite or airborne sensors.[1][2] Atmospheric effects in optical remote sensing are significant and complex, dramatically altering the spectral nature of the radiation reaching the remote sensor.[3] The atmosphere both absorbs and scatters various wavelengths of the visible spectrum which must pass through the atmosphere twice, once from the sun to the object and then again as it travels back up the image sensor. These distortions are corrected using various approaches and techniques, as described below.[4]
Sensor | Approach |
---|---|
MSS | band-to-band regression [5] |
MSS | all-band spectral covariance [6] |
airborne MSS | band-to-band regression [7] |
AVHRR | iterative estimation [8] |
MSS, TM | DOS with exponential scattering model [9] |
TM | DOS with exponential scattering model, downwelling atmospheric radiance measurements [10] |
TM | pixel-by-pixel tasseled cap haze parameter [11] |
AVHRR | DOS, NDVI, AVHRR band 3 [12] |
airborne TMS, Landsat TM | ground and airborne solar measurements, atmospheric modeling code [13] |
TM | comparison of ten DOS and atmospheric modeling code variations with field data [14] |
TM | dark target, modeling code [15] |
TM (all bands) | atmospheric modeling code, region histogram matching [16] |
TM | DOS with estimated atmospheric transmittance [17] |
TM | dark target, atmospheric modeling code |
TM, ETM+ | empirical line method, single target, ground measurements |
TM | water reservoirs, comparison of 7 methods for 12 dates |
AVHRR | 2-band PCT used to separate aerosol components |