| dc.description.abstract | Stem analysis is a common forest mensurational
technique used to gain individual tree information for
various growth attributes. Interest in stem analysis has
been renewed with the availability of computer technology,
and an increased emphasis on forest growth and yield
research.
This thesis deals with two main areas of concern. The
first is the need for a new computer algorithm capable of
processing stem analysis data produced by annual ring
measurement equipment. The development and application of
two new algorithms, DUFFNO and STEM, are discussed.
DUFFNO's main functions are; to aid in data
verification, and to produce the Duff-Nolan sequences for
the ring width data. STEM'S main function is to calculate
and produce tabular and graphical output of the growth
attributes. able The second area of concern involves stem
analysis sampling techniques. Nine trees were sectioned
intensively to obtain true volume estimates, which were used
as control values. These were compared statistically
against volume estimates derived from sub-samples of the
disc data. Reliable volume estimates, within 10 percent of
control values at a confidence level of 95 percent, were
obtained from three basic sampling methods. These were
referred to as the "uniform section length" method, the
"form class" method, and Romberg's method.
Recommendations for further research are offered. | |
