The location accuracy of Global Positioning System (GPS) units depends on l
ocation type (3-dimensional, 3-D>2-dimensional, 2-D) and satellite geometry
(indexed by horizontal dilution of precision, HDOP). To determine the best
computation method for positions collected by CPS telemetry collars in hil
ly terrain, we used a stationary GPS collar that attempted to calculate a p
osition every 10 minutes for 5 days, and we evaluated the relationship betw
een horizontal and vertical location accuracy and HDOP (range of HDOP, 3-D=
1.4 to 489.1, 2-D=1.4 to 4,891). The 50th and 95th percentiles of horizonta
l and vertical location error were related linearly to HDOP. Location error
depended mainly on accuracy of the collar altitude estimate used to comput
e the position in 2-D. Most forced 2-D locations not differentially correct
ed were more accurate than 3-D locations when collar altitude error was les
s than or equal to 50 m. It was better to force the computation of 2-D posi
tions from differentially corrected 3-D locations with HDOP>15 when the col
lar altitude error was less than or equal to 10 m. We also used data collec
ted on 10 free-ranging moose (Alces alces) for 12 months to examine whether
moose altitude could be estimated accurately using prior 3-D locations. Ac
curacy of moose altitude estimation was related inversely to the time elaps
ed since the first 3-D location used to make the estimate. When animal alti
tude is likely to vary greatly within small time periods, we suggest runnin
g the differential correction program twice for a single time period, using
an HDOP cutoff of 20-25 in the first run and 10-12 in the second. All 3-D
positions computed during the first processing of the data should be kept b
ur only the 2-D locations calculated in the second pass should be used beca
use they were calculated using more accurate estimates of animal altitude.
When applying this method to our data, only 9% of successful locations are
discarded and we estimate that horizontal location error is <35 m 95% of th
e time.