The focus of our project was an investigation into fluctuations and oscillations in the brightness of images of the solar corona, the outermost layer of the Sun’s atmosphere. Previous research has shown that power spectra computed from time series of light intensity values from the solar corona can be modelled by a general background power law, representing a combination of stochastic processes, with an added ‘tail’ at high frequencies, which captures a transition to white noise. Recently, work by Ireland et al. (2015) has proposed a more comprehensive spectral model that includes an additional superimposed Gaussian component to capture periodic spectral features. We use this comprehensive spectral model to perform the first global survey of power spectra of the extreme ultraviolet (EUV) solar corona. The solar region used is a massive (1000×1000-arcsecond) region, corresponding to 35% of the visible solar disk, and data from five wavelengths are considered: 171Å, 193Å, 211Å, 304Å, and 1600Å. The different wavelengths correspond to observations at different heights from the solar surface. We find that for these wavelengths, the best-fit model parameters distinctly reflect the regions’ visually observed features and allow for insight into the dynamical processes thought to exist in the solar corona. We classify spectra into three main categories: (1) power law-dominated; (2) tail-dominated; and (3) those with a significant Gaussian component, and associate these spectral categories with the physical processes thought to exist in those regions: (1) turbulence; (2) quiescence, and (3) those periodic in nature, respectively. Through comparison between wavelengths of the dependence of the model parameters on spatial location, we provide an explanation for how the physical processes that determine the conditions in each layer are connected to neighboring layers. Our research yields several promising possibilities for future study, including automated feature detection, as well as the detection of the precursor conditions that may be used to predict the onset of significant solar events such as sunspot emergences and solar flares.