  We study the applicability of several galaxy environment measures
(n^th-nearest-neighbor distance, counts in an aperture, and Voronoi volume)
within deep redshift surveys. Mock galaxy catalogs are employed to mimic
representative photometric and spectroscopic surveys at high redshift (z ~ 1).
We investigate the effects of survey edges, redshift precision, redshift-space
distortions, and target selection upon each environment measure. We find that
even optimistic photometric redshift errors (\sigma_z = 0.02) smear out the
line-of-sight galaxy distribution irretrievably on small scales; this
significantly limits the application of photometric redshift surveys to
environment studies. Edges and holes in a survey field dramatically affect the
estimation of environment, with the impact of edge effects depending upon the
adopted environment measure. These edge effects considerably limit the
usefulness of smaller survey fields (e.g. the GOODS fields) for studies of
galaxy environment. In even the poorest groups and clusters, redshift-space
distortions limit the effectiveness of each environment statistic; measuring
density in projection (e.g. using counts in a cylindrical aperture or a
projected n^th-nearest-neighbor distance measure) significantly improves the
accuracy of measures in such over-dense environments. For the DEEP2 Galaxy
Redshift Survey, we conclude that among the environment estimators tested the
projected n^th-nearest-neighbor distance measure provides the most accurate
estimate of local galaxy density over a continuous and broad range of scales.
