TITLE:
Modifications on the Strand’s Sampling Method Applied to Stands of Pinus elliottii Engelm
AUTHORS:
Sylvio Péllico Netto, Doádi Antônio Brena, Ângelo Augusto Ebling, Aurélio Lourenço Rodrigues
KEYWORDS:
Cluster Sampling, PPS Sampling, Forest Inventory
JOURNAL NAME:
Journal of Applied Mathematics and Physics,
Vol.2 No.7,
June
17,
2014
ABSTRACT:
This work was carried out with the objective of proposing some changes in
the Strand’s sampling method, in which the trees are selected in sampling units
with probability proportional to its diameter for the calculation of the stand density
and basal area, and proportional to its height for the calculation of volume per
hectare. Data used to evaluate the efficiency of the sampling of Strand in clusters
were collected in stands of Pinus elliottii Engelm, located in a National Forest, Rio Grande do Sul State, Brazil. In the course
of this research work it was proposed to convert the sampling unit into a cluster,
structurally more efficient to obtain consistent estimates of volume and of dominant
heights, using volumetric equivalence, which results in a form factor equal to one
for the final calculation of volume per hectare and an indirect method to obtain
the average height of Lorey. The objectives of this study were achieved, because
with this methodology it is not necessary to measure heights of trees in the sampling
unit, except a dominant height by cluster to evaluate sites. The development of
independent estimators for basal area and volume gave rise to the proposition of
an estimator for average height of Lorey, but without measuring any tree height
in the sampling. The proposed methodology is an attractive solution to reduce costs
in forest inventories, with the ability to have greater accuracy and scope for information
at the level of compartments, without increasing the cost of sampling in comparison
to that performed with units of fixed area. The use of smaller permanent sampling
units with higher intensity in the compartments before the final cut will substantially
increase the precision of the estimators in these management units, which will enable them to eliminate the pre-cut inventory in forest enterprises.