Atmospheric correction is the process of adjusting images taken by satellite or airborne sensors to remove distortions caused by the atmosphere. These distortions—mainly due to the scattering and absorption of sunlight by particles and gases—can affect how accurately the sensor captures the true reflectance (or brightness) of the Earth's surface.
In remote sensing, atmospheric effects can significantly alter the spectral characteristics of the radiation detected by sensors. This occurs because light must pass through the atmosphere twice—first as sunlight traveling to the Earth's surface, and again as reflected light returning to the sensor—undergoing both absorption and scattering along the way. These distortions can affect the accuracy of surface reflectance measurements and are typically corrected through a range of physical and statistical methods. Examples of atmospheric correction methods
+ Examples of atmospheric correction techniques for multispectral remote-sensing images, ordered chronologically to show the historical development of atmospheric correction methods in remote-sensing. Sensor Approach MSS band-to-band regression MSS all-band spectral covariance airborne MSS band-to-band regression AVHRR iterative estimation MSS, TM DOS with exponential scattering model TM DOS with exponential scattering model, downwelling atmospheric radiance measurements TM pixel-by-pixel tasseled cap haze parameter AVHRR DOS, NDVI, AVHRR band 3 airborne TMS, Landsat TM ground and airborne solar measurements, atmospheric modeling code TM comparison of ten DOS and atmospheric modeling code variations with field data TM dark target, modeling code TM (all bands) atmospheric modeling code, region histogram matching TM DOS with estimated atmospheric transmittance 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
See also Adaptive optics
References
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