The log volume calculation formula listed for various species in New Zealand
This is useful in manipulating forest stand density to silvicultural prescriptions in basal area. Reference equations and graphs are presented in English and metric units. Some examples of application are shown along with examples of other uses.
This publication explains estimating methods that can help harvesting and marketing decisions. However, the methods explained here apply only to sawn timber and pulpwood, and not to other products, such as poles and pilings.
USDA Technical Bulletin 1104, "Composite Volume Tables for Timber and Their Application in the Lake States" by Gevorkiantz and Olsen (1955) is used extensively for prediction of individual tree stem volumes in the Lake States region of the United States. Much of the work in the bulletin was done without the aid of contemporary statistical techniques, making it difficult to accurately extend the tables contained therein. Application of cubic spine interpolation and numerical integration provides a means of efficiently utilizing the bulletin�s information in modern computer systems while simultaneously extending the tables to a range of utilization standards. Close inspection of this analysis revealed some anomalies and inconsistencies in the original bulletin tables. The inspection also uncovered the implicit use of techniques attributed to more modern biometrics research. Several timber sampling aids requested by field foresters were derived using the system developed (Abstract)
This paper cover the foliage and branch biomass estimation for 6 Norway spruces (Picea abies) and 6 beeches (Fagus sylvatica) harvested in a 56-year-old mixed stand in southern Germany are presented. Different allometric models are investigated to derive branch biomass from branch dimension for both species. The equations that are based on branch length, foliated branch fraction, and branch diameter are used for tree and stand level estimates.
The authors have compiled all available diameter-based allometric regression equations for estimating total aboveground and component biomass, defined in dry weight terms, for trees in the United States.
The aim of this study was to construct dry weight equations for Norway spruce growing on farmland. Dry weight equations for fractions of Norway spruce trees were made. Biomass production was estimated in 32 stands of Norway spruce growing on abandoned farmland. A modified �mean tree technique� was used to estimate biomass production; i.e. the tallest tree was chosen for sampling.
The growth prediction system is a distance-independent individual-tree simulator containing equations that predict basal-area growth, survival, total and merchantable heights, and total and merchantable volumes for shortleaf pine trees. These equations were combined into a computer simulation program that predicts future states of shortleaf pine stands from initial stand descriptions. Comparisons of observed and predicted ending stand conditions in shortleaf pine research plots indicate the simulator makes acceptable forecasts of final stand attributes
It deals with measurement of DBH and Height and equipment used to measure the tree attributes. The estimation of the tree volume using volume table and stand volume is described
The study is based on disks taken at different heights on 17 pines and 22 spruces in seven experimental plots. Contours of the cross-sections outside and inside bark were drawn with high accuracy. A great number of measurements were made on each contour. Various characteristics of the shape of the section were computed. Different methods of estimating the cross-sectional area-with caliper, tape, and different kinds of sector forks-were simulated. The results were in agreement with what could be expected from geometrical theory. They did however in several cases disagree with results from field observations reported in the literature, for instance in the case caliper vs. tape. This can be explained by the fact that field measurements are often heavily influenced by errors in handling the instruments and making the observations (from abstract)
This paper reviews quantitative principles and gives specific examples for prediction of tree biomass. The examples should prove useful for understanding the principles involved and for instructional purposes.
Two procedures that guarantee the property of additivity among the components of tree biomass and total tree biomass utilizing nonlinear functions are developed. Procedure 1 is a simple combination approach, and procedure 2 is based on nonlinear joint-generalized regression (nonlinear seemingly unrelated regressions) with parameter restrictions. Specific examples using slash pine (Pinus elliottii Eng elm. var. elliottii) biomass data are presented to demonstrate and clarify the methods behind nonlinear estimation, additivity, error modeling, and the formation of confidence and prediction intervals.