Theories of how galaxies form and evolve depend greatly on constraints provided by observations. However, when those observations come from different datasets, systematic offsets may occur. This causes difficulties measuring variations in parameters between filters. In this thesis I present the variation in total luminosity density with wavelength in the nearby Universe (z<0.1), produced from a consistent reanalysis of NIR and optical observations, taken from the MGC, UKIDSS and SDSS surveys. I derive luminosity distributions, best-fitting Schechter function parameterisations and total luminosity densities in ugrizYJHK, and compare the variation in luminosity density with cosmic star formation history (CSFH) and initial mass function (IMF) models. I examine the r band luminosity distribution produced using different aperture definitions, the joint luminosity- surface brightness (bivariate brightness) distribution in ugrizYJHK, comparing them to previously derived distributions, and how the total luminosity density varies with wavelength when surface brightness incompleteness is accounted for. I find the following results. (1) The total luminosity density calculated using a non-Sersic (e.g. Kron or Petrosian) aperture is underestimated by at least 15%, (2) Changing the detection threshold has a minor effect on the best-fitting Schecter parameters, but the choice of Kron or Petrosian apertures causes an offset between datasets, regardless of the filter used to define the source list, (3) The decision to use circular or elliptical apertures causes an offset in M* of 0.20 mag, and best-fitting Schechter parameters from total magnitude photometric systems have a flatter faint-end slope than Kron or Petrosian photometry, (4) There is no surface brightness distribution evolution with luminosity for luminous galaxies, but at fainter magnitudes the distribution broadens and the peak surface brightness dims. A Choloniewski function that is modified to account for this surface brightness evolution fits the bivariate-brightness distribution better than an unmodified Choloniewski function, (5) The energy density per unit interval, vf(v) derived using MGC and GAMA samples agrees within 90% confidence intervals, but does not agree with predictions using standard CSFH and IMF models. Possible improvements to the data and alterations to the theory are suggested.

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