A number of methods have been proposed for the atmospheric correction of the multispectral satellite images, based on
either atmosphere modelling or images themselves. Full radiative transfer models require a lot of ancillary information
about the atmospheric conditions at the acquisition time. Whereas, image based methods cannot account for all the
Therefore, the aim of this paper is the comparison of different atmospheric correction methods for multispectral satellite
images. The experimentation was carried out on a study area located in the catchment area of Yialias river, 20 km South
of Nicosia, the Cyprus capital. The following models were tested, both empirical and physically based: Dark object
subtraction, QUAC, Empirical line, 6SV, and FLAASH. They were applied on a Landsat 8 multispectral image.
The spectral signatures of ten different land cover types were measured during a field campaign in 2013 and 15 samples
were collected for laboratory measurements in a second campaign in 2014. GER 1500 spectroradiometer was used; this
instrument can record electromagnetic radiation from 350 up to 1050 nm, includes 512 different channels and each
channel covers about 1.5 nm. The spectral signatures measured were used to simulate the reflectance values for the
multispectral sensor bands by applying relative spectral response filters. These data were considered as ground truth to
assess the accuracy of the different image correction models.
Results do not allow to establish which method is the most accurate. The physics-based methods describe better the
shape of the signatures, whereas the image-based models perform better regarding the overall albedo.