Pulsars are known to emit radiation which is observed to vary in a vast range of frequencies, from very low radio frequencies (e.g. Pilia et al., 2016) even up to gamma rays (e.g Thompson, 2004), mainly due to the randomly disturbed around the universe ionised matter. However, lately it has been noted, particularly in the work of Bilous et al. (2016), that, when observed in very low radio frequencies, a few pulsars show fluctuations in their flux densities and spectra in magnitudes that require further explanation than just scintillation effects. Driven by their results, a supplementary monitoring campaign was conducted with the LOFAR telescope. For a total of four months, a set of thirteen pulsars were observed with a Ã¢ÂÂ¼2-weeks interval for a maximum of 30-minutes for each observation during the transit of each source. With the intention of getting a more thorough understanding of the large variability in their flux densities and spectra on timescales of both minutes and weeks, imaging data were acquired simultaneously to beam-formed. In this thesis, two pulsars, PSR B2016+28 and PSR B2020+20, were chosen from the observed set, due to their brightness and close proximity. The beam-formed and imaging data were processed to obtain flux density measurements and spectra, while additional analysis was done for the RFI mitigation process, the dependence of the results from the weighting scheme as well as the influence of the beam model on the measurements. Observational and intrinsic effects are being taken into account, as well as calibration errors, and discussed in an effort to explain the phenomenon. Our major concern, however, revolves around a large variability appearing simultaneously in beam-formed and imaging measurements for both sources, leading us to conclude that a better calibration scheme, which takes into consideration ionospheric effects and large contaminating sources in the field of the target, needs to be included in the standard analysis of the imaging LOFAR data. Furthermore, the results from image processing are deemed essential, as it can account for any misconceptions beam-formed data analysis may lead to.