In the last years, many approaches have been developed for deriving Phytoplankton Functional Types (PFTs) or phytoplankton size classes from remote sensing observations. However most, if not all approaches are made at global scale. In this study, we focus on the Southern Ocean. We determine and compare the spatial distribution of PFTs using the methods developed by Bracher et al. (2009) and Hirata et al. (2011). The method of Hirata et al. (2011) consists of two steps. First, significant relationships are established between chlorophyll-a and biomarker pigments, as they presented using a global data set of High-Performance Liquid Chromatography (HPLC). These relationships are then applied to the chlorophyll-a (chl-a) observations by remote sensing, as they presented using the Sea-viewing-Wide-Field-of-View-Sensor (SeaWiFS). The result is the spatial distribution of microplankton (diatoms and dinoflagellates), nanoplankton, picoplankton (prokaryotes, PicoEukaryotes, Prochlorococcus sp.) and green algae. Alternatively, Bracher et al. (2009) applied the Differential Optical Absorption Spectroscopy (DOAS) technique on data derived from the sensor Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) (PhytoDOAS method) for retrieving diatoms, dinoflagellates, cyanobacterias, prymnesiophytes and coccolithophores. The difference of PhytoDOAS to the method of Hirata et al. (2011) is the direct retrieval of the PFTs from spectrally resolved satellite data, without the use of empirical relationships. Within this study, we apply the Hirata et al. (2011) method to the GlobColour 9km Level-3 monthly chl-a data set. The empirical relationships were determined from a large HPLC pigment data set restricted to the Southern Ocean. Climatological aspects are considered for comparison of the PFTs spatial distributions for the period of 2003-2010. Limitations of both methods are discussed and improvements are suggested.