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In this thesis, we derive a catalogue of robust structural parameters for thecomponents of a large sample of nearby GAMA galaxies while at the same timecontributing to the advancement of image analysis, surface brightness fittingand post-processing routines for quality assurance in the context of automatedlarge-scale bulge-disk decomposition studies. The sample consists of 13096galaxies at redshifts z < 0.08 with imaging data from the Kilo-Degree Surveyand the VISTA Kilo-Degree INfrared Galaxy survey spanning the optical andnear-infrared. We fit three models to the surface brightness distribution ofeach galaxy in each band: a single S\'ersic model, a S\'ersic plus exponentialand a point source plus exponential. The fitting is performed with a fullyautomated Markov-chain Monte Carlo (MCMC) analysis using the Bayesiantwo-dimensional profile fitting code ProFit. All preparatory work is carriedout using the image analysis package ProFound. After fitting the galaxies, weperform model selection and flag galaxies for which none of our models areappropriate, mainly mergers and irregular galaxies. The fit quality is assessedby visual inspections, comparison to previous works, comparison of independentfits of galaxies in the overlap regions between KiDS tiles and bespokesimulations. The latter two are also used for a detailed investigation ofsystematic error sources. We find that our fit results are robust acrossvarious galaxy types and image qualities with minimal biases. Errors given bythe MCMC underestimate the true errors typically by factors 2-3. Automatedmodel selection criteria are accurate to > 90 % as calibrated by visualinspection of a subsample of galaxies. We also present g-r component coloursand the corresponding colour-magnitude diagram, consistent with previous worksdespite our increased fit flexibility. All results are integrated into the GAMAdatabase.

Galaxy And Mass Assembly (GAMA): Bulge-disk decomposition of KiDS and VIKING data in the nearby universe