  We present a new cluster-finding algorithm based on a combination of the
Voronoi Tessellation and Friends-Of-Friends methods. The algorithm utilises
probability distribution functions derived from a photometric redshift analysis
and is tested on simulated cluster-catalogues. We use a 9 band photometric
catalogue over 0.5 square degrees in the Subaru XMM-Newton Deep Field. The
photometry is comprised of UKIDSS Ultra Deep Survey infrared J and K data
combined with 3.6 micro-m and 4.5 micro-m Spitzer bands and optical BVRi'z'
imaging from the Subaru Telescope. The cluster catalogue contains 13 clusters
at redshifts 0.61 <= z <= 1.39 with luminosities 10L* < L_tot < 50 L*.
