campaign that supports the project [@2011arXiv1106.1706S; @2016arXiv161100036D; @2016arXiv161100037D].

Most of what is known about as a population is based on observations of the Coma cluster [@2015ApJ...798L..45V; @2016ApJS..225...11Y]. In this initial stage of the project, the detection algorithm has been constrained to search similar to those found in Coma, and thus is focused on systems with angular sizes $R_e \gtrsim 5$ arcsec, which are easier to classify than smaller objects in the absence of redshift information. The methodology used to identify is described in detail in @2019ApJS..240....1Z and Zaritsky et al. (in prep.), and here we summarize the main steps of the process. First, bright, saturated sources are detected, modeled and replaced in the images by background noise, whereas fainter background and foreground sources are carefully modeled and subtracted. Then, wavelet filtering is used to detect sources according to size and surface brightness criteria, defined to have $\mu_{0,g} \ge 24$ mag arcsec$^{-2}$ and $R_e > 5.3$. Finally, all UDG candidates are modeled with a single Sérsic component using <span style="font-variant:small-caps;">GALFIT</span> [@2002AJ....124..266P; @2010AJ....139.2097P].

In this work, we use a sample of 172 UDG candidates in the Stripe 82 area. From SMUDGes we adopt the values of $m_g, m_r, m_z,$ Sérsic index $n$, 