G. B. Wood

Centroid sampling: a variant of importance sampling for estimating the volume of sample trees of radiata pine.

Simulation of importance sampling using a database comprising detailed measurements along the bole of 114 trees of radiata pine (Pinus radiata D. Don) revealed a point on the bole at a relative height of approximately 0.3 which, if selected as the point of importance sampling, gave minimum bias in the estimate of tree volume. A theoretical examination of solids of revolution identified this point as the centroid of the tree. A variant of importance sampling, called centroid sampling, in which the point of sampling is fixed at the height of the centroid rather than being determined at random, was then applied in conjunction with 3P sampling to estimate the volume of a forest plot of 55 trees of 36-year-old radiata pine in Stromlo Forest, Australian Capital Territory. The resulting estimate of stand volume was both precise and accurate.

Simple linear model reliably predicts bark thickness of radiata pine in the Australian capital territory

Abstract A series of linear and nonlinear models was tested for predicting bark thickness of radiata pine ( Pinus radiata D. Don) growing in the Australian Capital Territory. A simple linear model proved superior to all other models. This model predicts bark thickness at any point along the bole, relative to bark thickness at breast height, from the fourth power of relative diameter. Relative diameter is defined as the ratio of diameter overbark at a point on the bole to the diameter overbark at breast height. The model is independent of site and age and appears to be unaffected by forest location. Using the model, the underbark volume of 109 trees was estimated to be 54.6 m 3 compared with the actual volume of 54.9 m 3 . This represents an error of −0.5%.

Comparison of three modern methods for estimating volume of sample trees using one or two diameter measurements

Abstract Seven variations of the centroid, importance and control-variate methods for estimating bole volume were compared using four sample tree data sets, viz. Pinus ponderosa (186 trees), P. radiata (114 trees), P. taeda (4578 trees), and American mixed hardwoods (538 trees). The centroid method was the easiest to apply. Generally, it gave the most precise but also the most biased results (the biases were not severe, ranging from −0.2 to −4.1%). In contrast, methods involving importance sampling using either one or two random points, or a random point and an antithetic point, were unbiased (except for P. taeda) but generally much less precise. Invariably, the precision of the estimate was improved using two random points. Replacing one random point by an antithetic point generally improved the precision further but replacement by the centroid point generally introduced bias. The control-variate methods using one or two random points gave unbiased but imprecise estimates, the precision being better for two random points than one, as for importance sampling.

Practical guide for estimating the volume of a standing sample tree using either importance or centroid sampling

Abstract The importance and centroid sampling methods enable the volume of the bole of a standing tree or any portion of it (log) to be estimated based on a single diameter measurement. The methods eliminate the need for volume tables or equations and the bias which these might incur. They can be used anywhere for any species of tree of excurrent or deliquescent habit which has a well-defined main bole and would seem to be particularly appropriate for inventory of tropical mixed-moist forests. Programs written in BASIC and examples are provided to facilitate application of the methods in the field.

Estimating the volume of Australian hardwoods using centroid sampling.

Summary Centroid sampling was tested on 18 sample trees of Flindersia brayleyana and 124 sample trees of five species of Eucalyptus all of which were measured in detail. Volumes of the main bole of each tree and of logs (length approx. 6 m) derived from each bole were estimated using both Hubers formula and centroid sampling. These estimates were compared with ‘true’ volume obtained by summing the volumes derived using Smalians formula of all the measured short sections comprising the main bole and each log respectively. The mean error of the centroid estimate of volume of the main bole was not significant for Eucalyptus sieberi and E. diversicolor and was less than that derived from Hubers formula for all species except E. regnans. When all species were combined, the centroid estimate was clearly more accurate, its mean error (-2%) being just significant (p=0.046). Centroid sampling also gave more accurate estimates of the volume of the component logs. Results of this study and earlier work suggest th...

Test of application of centroid and importance sampling in a point-3P forest inventory

Abstract The volume of 66.8 ha of mature native eucalypt forest in southeast New South Wales was estimated by point-3P sampling using three methods: detailed dendrometry, centroid sampling and importance sampling. The derived resource estimates were 11 790 ± 1026, 11 150 ± 959 and 11 520 ± 1014 m3, respectively. The dendrometry required for centroid and importance sampling was 82% and 84% less respectively than that required for detailed measurement. Compared with detailed dendrometry, the centroid method underestimated the mean bole volume of second-stage sample trees by 6.9%, whereas importance sampling underestimated by only 2.4%. However, the bole volumes derived from centroid sampling were more closely related to those derived from detailed dendrometry (r2 = 0.976) than those derived from importance sampling (r2 = 0.935), and the two regressions were significantly different. More importantly, the centroid method proved superior to importance sampling in terms of both the mean-square error and tolerance interval. The reason for this apparent anomaly is discussed. All three methods were equally satisfactory for predicting the assortment of log products (saw-log, pulp, cull). The advantages and disadvantages of applying centroid and importance sampling to standing sample trees are listed.

Remotely sensed digital data in forestry: a review

Summary Landsat and other remotely sensed digital data offer many advantages for forest managers. Researchers and land managers have used Landsat to inventory forests, detect and monitor fire boundaries and clearing of forests, and monitor the spread of major forest pests. In North America, and to some extent in Australia, Landsat data are used operationally for some of these functions. The use of Landsat and other types of remotely sensed imagery by forest managers in Australia should become more widespread with improvements in sensors and computer algorithms and the increasing availability of cheaper computing facilities, including microcomputers, to analyse data.

Simulating the forest and the point-sampling process as an aid in designing forest inventories.

Abstract This paper describes a computer package, FPS-SIM, which is capable of simulating point sampling in a simulated 1000-ha tract of forest. The user is required to specify parameters for the forest and sub-sections of it including stocking rate (trees/ha), the pattern governing tree position, allowable range of values of diameter at breast height over back (Dbhob), and basal area (m2/ha). Point sampling may be executed at any specified location in the forest using one or more basal area factors ( bafs ). A set of experiments using the package is described in which the initial reconnaissance phase of a point-3P forest inventory is simulated. These experiments show the effects of varying the number of sample points, baf values and forest specifications on estimates of the population parameters. The results of the simulation are in accord with field experience and demonstrate the value of the model for comparing the results of various point-sampling strategies.

Ground-sampling methods used to inventory tropical mixed moist forests☆

Abstract Sixty tropical countries were surveyed for information relating to the ground-sampling methods used to inventory their forest resources. Thirty-six countries (60%) responded, ten African, twelve Asian/Pacific, and fourteen Latin American. Systematic sampling with either fixed-area plots or striplines is most widely favoured in Africa (relative use, 66%) and the Asian/Pacific region (49%). In Latin America, systematic, simple random and restricted random sampling are used about equally (22–32%). Only a small proportion of countries use clustered plots (relative use, 7%). (‘Relative use’ relates to data from those sections of the survey for which multiple answers were given (e.g. listing the various types of sampling methods used for forest inventory together with an estimate of the relative importance of each on a percentage scale). The relative-use data were derived by averaging the percentage figures across countries and geographical regions.) Angle-count sampling (ACS) is one of the methods used for forest inventory in 28% of the countries surveyed. The main objections to ACS by countries not using it are restricted visibility (53% of respondents), high cost of Relaskop (25%), too complicated (25%), and unfamiliarity with the technique (19%). A majority of countries (78%) use tables based on Dbhob (or Dbhab) and hole length as a method of assessing bole volume. Optical dendrometry (Relaskop) is used as one method to derive bole volume in 30% of African countries, but is used little or not at all in the outer two regions. The survey highlights a need for research and development of more sophisticated but practical forest-sampling systems for tropical countries, and training programmes broadening the experience and skills of foresters engaged in tropical forest inventory.

Choosing a portable data recorder.

Summary Choosing a portable data recorder from the array of machines now becoming available is a challenging and daunting task unless certain procedures are followed. These procedures are discussed in detail and recommendations are made on how to use the recorder most efficiently.