  We measure the redshift evolution of galaxy bias for a magnitude-limited
galaxy sample by combining the galaxy density maps and weak lensing shear maps
for a $\sim$116 deg$^{2}$ area of the Dark Energy Survey (DES) Science
Verification data. This method was first developed in Amara et al. (2012) and
later re-examined in a companion paper (Pujol et al. 2016) with rigorous
simulation tests and analytical treatment of tomographic measurements. In this
work we apply this method to the DES SV data and measure the galaxy bias for a
i$<$22.5 galaxy sample. We find the galaxy bias and 1$\sigma$ error bars in 4
photometric redshift bins to be 1.12$\pm$0.19 (z=0.2-0.4), 0.97$\pm$0.15
(z=0.4-0.6), 1.38$\pm$0.39 (z=0.6-0.8)), and 1.45$\pm$0.56 (z=0.8-1.0). These
measurements are consistent at the 2$\sigma$ level with measurements on the
same dataset using galaxy clustering and cross-correlation of galaxies with CMB
lensing, with most of the redshift bins consistent within the 1{\sigma} error
bars. In addition, our method provides the only $\sigma_8$-independent
constraint among the three. We forward-model the main observational effects
using mock galaxy catalogs by including shape noise, photo-z errors and masking
effects. We show that our bias measurement from the data is consistent with
that expected from simulations. With the forthcoming full DES data set, we
expect this method to provide additional constraints on the galaxy bias
measurement from more traditional methods. Furthermore, in the process of our
measurement, we build up a 3D mass map that allows further exploration of the
dark matter distribution and its relation to galaxy evolution.
