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In order to generate credible 0.1-2 {mu}m SEDs, the GAMA project requires many Gigabytes of imaging data from a number of instruments to be re-processed into a standard format. In this paper we discuss the software infrastructure we use, and create self-consistent ugrizYJHK photometry for all sources within the GAMA sample. Using UKIDSS and SDSS archive data, we outline the pre-processing necessary to standardise all images to a common zeropoint, the steps taken to correct for seeing bias across the dataset, and the creation of Gigapixel-scale mosaics of the three 4x12 deg GAMA regions in each filter. From these mosaics, we extract source catalogues for the GAMA regions using elliptical Kron and Petrosian matched apertures. We also calculate Sersic magnitudes for all galaxies within the GAMA sample using SIGMA, a galaxy component modelling wrapper for GALFIT 3. We compare the resultant photometry directly, and also calculate the r band galaxy LF for all photometric datasets to highlight the uncertainty introduced by the photometric method. We find that (1) Changing the object detection threshold has a minor effect on the best-fitting Schechter parameters of the overall population (M* +/- 0.055mag, {alpha} +/- 0.014, {Phi}* +/- 0.0005 h^3 Mpc^{-3}). (2) An offset between datasets that use Kron or Petrosian photometry regardless of the filter. (3) The decision to use circular or elliptical apertures causes an offset in M* of 0.20mag. (4) The best-fitting Schechter parameters from total-magnitude photometric systems (such as SDSS modelmag or Sersic magnitudes) have a steeper faint-end slope than photometry dependent on Kron or Petrosian magnitudes. (5) Our Universes total luminosity density, when calculated using Kron or Petrosian r-band photometry, is underestimated by at least 15%.
We report the morphological classification of 3727 galaxies from the Galaxy and Mass Assembly survey with M_r < -17.4 mag and in the redshift range 0.025 < z < 0.06 (2.1 x 10^5 Mpc^3 ) into E, S0-Sa, SB0-SBa, Sab-Scd, SBab-SBcd, Sd-Irr and little blu
Using the complete GAMA-I survey covering ~142 sq. deg. to r=19.4, of which ~47 sq. deg. is to r=19.8, we create the GAMA-I galaxy group catalogue (G3Cv1), generated using a friends-of-friends (FoF) based grouping algorithm. Our algorithm has been te
The Galaxy And Mass Assembly (GAMA) survey is a multiwavelength photometric and spectroscopic survey, using the AAOmega spectrograph on the Anglo-Australian Telescope to obtain spectra for up to ~300000 galaxies over 280 square degrees, to a limiting
We measure the projected 2-point correlation function of galaxies in the 180 deg$^2$ equatorial regions of the GAMA II survey, for four different redshift slices between z = 0.0 and z=0.5. To do this we further develop the Cole (2011) method of produ
A heuristic greedy algorithm is developed for efficiently tiling spatially dense redshift surveys. In its first application to the Galaxy and Mass Assembly (GAMA) redshift survey we find it rapidly improves the spatial uniformity of our data, and nat