Geoscience Reference
In-Depth Information
sufficient distance so that results on neighboring points can be considered
independent or to choose a number of randomly located points, and it is
relatively easy in the field to find and measure the distance to the closest
item, then find and measure the distance to the nearest (or second-nearest,
third-nearest, etc.) neighbor of the item.
Numerous procedures have been devised to estimate the density (num-
ber per unit area) of distinct items in a study area using plotless sampling.
These include the point-centered quarter method (Cottam, 1947) by which
the distances from a random point to the closest individual in each 90°
quadrant are measured. However, the density estimates from the point-
centered quarter method and most variations of distance methods are
biased if the spatial pattern is not random. In this chapter, only two plotless
sampling procedures are considered:
T
T-square sampling and wandering-
quarter sampling.
6.2
T
-Square Sampling
With the
T
T-square method a random (or systematic) sample of points is
located in the study area with the distances between points large enough
for them to be considered independent. At each point, two distances are
measured, as shown in Figure 6.1. The first distance
x
i
is from the point
P
to
the nearest item
I
, and the second distance
z
i
is from the item
I
to its nearest
neighbor.
+
+
+
+
+
+
+
+
Q
P
+
+
+
x
1
I
z
2
+
Q
x
2
+
+
z
1
I
+
P
+
+
+
+
+
FIGURE 6.1
T
T-square sampling. Two random points
P
are located in the study area, and the distances
x
i
to
the closest item
I
are measured. The distance
z
i
from the item
I
to its nearest neighbor
Q
is then
measured subject to the condition that the angle from
P
to
I
to
Q
is more than 90°.
