scholarly journals Differences in Computed Individual-Tree Volumes Caused by Differences in Field Measurements

2008 ◽  
Vol 25 (4) ◽  
pp. 195-201 ◽  
Author(s):  
James A. Westfall
Keyword(s):  
Field Measurements ◽  
Accurate Estimation ◽  
Statistical Bias ◽  
Full Data ◽  
Data Set ◽  
Individual Tree ◽  
Forest Inventory And Analysis ◽  
Species Groups ◽  
Input Variables ◽  
Volume Equations

Abstract Individual-tree volumes are primarily predicted using volume equations that rely on measured tree attributes. In the northeastern United States, the Forest Inventory and Analysis program determines tree volume using dbh, bole height, proportion of cull, and species information. These measurements are subject to variability due to a host of factors. The sensitivity of the volume equations were assessed in relation to changes in each of the input variables. Additionally, data from 3,345 trees that were independently remeasured were used to assess differences in gross and net volumes between operational and audit measurements. Evaluations were conducted for dbh, bole height, and proportion of cull classes, across 18 different species groups. Differences in bole height and proportion cull measurements were found to contribute the most to volume differences. Surprisingly, trees with relatively short bole heights were affected more than trees having taller bole heights. Differences in dbh and species identification contributed little to the volume differences. An analysis of the full data set across all realized volume differences showed no statistical bias in either gross or net volume. These results show the influence that specific field measurements have on accurate estimation of volume, which may be useful for targeting specific attributes where additional training or refined measurement protocols could improve consistency.

scholarly journals Individual Tree Volume Equations for Red Pine in Michigan

1997 ◽  
Vol 14 (2) ◽  
pp. 53-58 ◽  
Author(s):  
Gary W. Fowler
Keyword(s):  
Red Pine ◽  
Data Sets ◽  
Regression Equations ◽  
Independent Data ◽  
Data Set ◽  
Individual Tree ◽  
Standing Trees ◽  
Pine Stands ◽  
Volume Estimates ◽  
Volume Equations

Abstract New total, pulpwood, sawtimber, and residual pulpwood cubic foot individual tree volume equations were developed for red pine in Michigan using nonlinear and multiple linear regression. Equations were also developed for Doyle, International 1/4 in., and Scribner bd ft volume, and a procedure for estimating pulpwood and residual pulpwood rough cord volumes from the appropriate cubic foot equations was described. Average ratios of residual pulpwood (i.e., topwood, cubic foot or cords) to mbf were developed for 7.6 and 9.6 in. sawtimber. Data used to develop these equations were collected during May-August 1983-1985 from 3,507 felled and/or standing trees from 27 stands in Michigan. Sixteen and 11 stands were located in the Upper and Lower Peninsulas, respectively. All equations were validated on an independent data set. Rough cord volume estimates based on the new pulpwood equation were compared with contemporary tables for 2 small cruise data sets. The new equations can be used to more accurately estimate total volume and volume per acre when cruising red pine stands. North. J. Appl. For. 14(2):53-58.

Cubic and Board Foot Volume Models for the Central States

1991 ◽  
Vol 8 (2) ◽  
pp. 47-57 ◽  
Author(s):  
Jerold T. Hahn ◽  
Mark H. Hansen
Keyword(s):  
Forest Inventory ◽  
Site Index ◽  
Forest Service ◽  
Timber Species ◽  
Usda Forest Service ◽  
Data Set ◽  
Forest Inventory And Analysis ◽  
Regression Techniques ◽  
Species Groups ◽  
Volume Models

Abstract This paper presents tree volume models developed for major timber species in the Central States (Indiana, Illinois, Missouri, and Iowa). Models for estimating gross tree volume (either cubic foot or board foot International ¼-in. log rule) and percent cull were developed for 23 species or species groups. These models estimate volume based on observed dbh and tree site index. Nonlinear regression techniques were used to fit a Weibull-type function to estimate gross volume with a data set containing observations from more than 50,000 trees measured throughout the region. A simple linear model was used to estimate percent cull in a tree for each of several tree classes. These models are being used in the statewide inventories now underway in Missouri and Iowa and may be used by anyone desiring volume-per-tree estimates that are comparable to USDA Forest Service Forest Inventory and Analysis estimates in these areas. North. J. Appl. For. 8(2):47-57

Individual Tree Volume Equations for the Northeastern United States: Evaluation and New Form Quotient Board Foot Equations1

1989 ◽  
Vol 6 (1) ◽  
pp. 27-31 ◽  
Author(s):  
Thomas E. Burk ◽  
Richard P. Hans ◽  
Eric H. Wharton
Keyword(s):  
United States ◽  
Northeastern United States ◽  
Individual Tree ◽  
Tree Form ◽  
Forest Survey ◽  
Species Groups ◽  
New Form ◽  
Using Data ◽  
Volume Equations

Abstract Volume equations used in forest survey in the northeastern United States were evaluated using data collected as part of utilization studies. Results are presented for both cubic foot and board foot equations for 16 species groups. Existing cubic foot equations were found to be satisfactory while the board foot equations generally produced significantly large underestimates. New board foot equations that include a measure of tree form were derived. North. J. Appl. For. 6(1):27-31, March 1989.

PD26 Principal Component Approximation: Canadian Health Measures Survey

2018 ◽  
Vol 34 (S1) ◽  
pp. 138-139
Author(s):  
Yi-Sheng Chao ◽  
Chao-Jung Wu
Keyword(s):  
Principal Component ◽  
Physical Development ◽  
Forced Expiratory Volume ◽  
Data Sets ◽  
Full Data ◽  
Data Set ◽  
Health Measures ◽  
Canadian Health ◽  
Input Variables ◽  
Canadian Health Measures Survey

Introduction:Principal component analysis (PCA) is used for dimension reduction and data summary. However, principal components (PCs) cannot be easily interpreted. To interpret PCs, this study compares two methods to approximate PCs. One uses the PCA loadings to understand how input variables are projected to PCs. The other uses forward-stepwise regression to determine the proportions of PC variances explained by input variables.Methods:Two data sets derived from the Canadian Health Measures Survey (CHMS) were used to test the concept of PC approximation: a spirometry subset with the measures from the first trial of spirometry; and, full data set that contained representative variables. Variables were centered and scaled. PCA were conducted with 282 and twenty-three variables respectively. PCs were approximated with two methods.Results:The first PC (PC1) could explain 12.1 percent and 50.3 percent of total variances in respective data sets. The leading variables explained 89.6 percent and 79.0 percent of the variances of PC1 in respective data sets. It required one and two variables to explain more than 80 percent of the variances of PC1, respectively. Measures related to physical development were the leading variables to approximate PC1 and lung function variables were leading to approximate PC2 in the full data set. The leading variable to approximate PC1 of the spirometry subset were forced expiratory volume (FEV) 0.5/forced vital capacity (FVC) (percent) and FEV1/FVC (percent).Conclusions:Approximating PCs with input variables were highly feasible and helpful for the interpretation of PCs, especially for the first PCs. This method is also useful to identify major or unique sources of variances in data sets. The variables related to physical development are the variables related to the most variations in the full data set. The leading variable in the spirometry subset, FEV0.5/FVC (percent), is not well studied for its application in clinical use.

The Relationship of Diameter at Breast Height and Crown Diameter for Four Species Groups in Hardin County, Tennessee

1995 ◽  
Vol 19 (4) ◽  
pp. 177-181 ◽  
Author(s):  
Lawrence R. Gering ◽  
Dennis M. May
Keyword(s):  
Field Measurements ◽  
Aerial Photographs ◽  
Linear Regression Models ◽  
Individual Tree ◽  
Diameter At Breast Height ◽  
Crown Diameter ◽  
Breast Height ◽  
Forest Experiment Station ◽  
Species Groups ◽  
Time Required

Abstract A set of simple linear regression models for predicting diameter at breast height (dbh) from crown diameter and a set of similar models for predicting crown diameter from dbh were developed for four species groups in Hardin County, TN. Data were obtained from 557 trees measured during the 1989 USDA Southern Forest Experiment Station survey of the forests of Tennessee, with supplemental aerial photographic observations. Estimates of individual tree crown diameter were obtained from ground measurements and from measurements made on 9 X 9 in. color aerial photographs (with nominal scale of 1:4,800) taken during the fall color season. In practice, users of aerial photographs can estimate dbh by measuring crown diameter, converting it to feet using the photo scale, and applying the appropriate equation. Similarly, crown diameter can be estimated from a ground measurement of dbh. This procedure may be useful in reducing the time required for field measurements. It may also be used to calculate crown diameters for datasets that include dbh but no direct measurement of crown attributes. South. J. Appl. For. 19(4):177-181.

scholarly journals STRATEGIES FOR STEM MEASUREMENT SAMPLING: A STATISTICAL APPROACH OF MODELLING INDIVIDUAL TREE VOLUME

CERNE ◽  
2016 ◽  
Vol 22 (3) ◽  
pp. 249-260 ◽  
Author(s):  
Hassan Camil David ◽  
Rodrigo Otávio Veiga Miranda ◽  
John Welker ◽  
Luan Demarco Fiorentin ◽  
Ângelo Augusto Ebling ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Statistical Tests ◽  
Fixed Number ◽  
Stem Volume ◽  
Diameter Class ◽  
Clear Trend ◽  
Data Set ◽  
Individual Tree ◽  
Volume Estimates ◽  
Volume Equations

ABSTRACT The aim of this paper was to evaluate different criteria for stem measurement sampling and to identify the criterion with best performance for developing individual tree volume equations. Data were collected in eucalyptus stands 58 to 65 months old. Schumacher-Hall model was applied using five sampling criteria with nine variations (45 in total): 1) number of trees per diameter class, being (a) fixed number, (b) proportional to the diameter class of the sample, or (c) proportional to the standard deviation of the sample; and 2) the width of the diameter class, which ranged from 1.0 up to 5.0 cm. We used the equations generated from each of the five sampling criteria to estimate stem volume of trees reserved for validation. This allowed us to obtain standard errors of estimates from this data-set. In addition, residuals of volume estimates were examined by means of statistical tests of bias, autocorrelation and heteroscedasticity. Better performances of volume equations occurred when smaller diameter class widths were used, i.e., when the sample size increased. There was no clear trend in increasing/decreasing residual autocorrelation and/or heteroscedasticity. Both methods of sampling proportional to the frequency of diameter class had the best performances, inclusive using only 36 trees. The ones where choice of trees was proportional to the standard deviation had the worst. In conclusion, the selection proportional to the frequency of the diameter class, under the condition that at least two trees per class are sampled, provides models statistically better than all the other criteria.

scholarly journals Back in Time for Breakfast: An Analysis of the Changing Breakfast Cereal Aisle

Nutrients ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 489
Author(s):  
Emilie Croisier ◽  
Jaimee Hughes ◽  
Stephanie Duncombe ◽  
Sara Grafenauer
Keyword(s):  
Dietary Fibre ◽  
Saturated Fat ◽  
Health Claims ◽  
Whole Grain ◽  
Breakfast Cereal ◽  
Full Data ◽  
Data Set ◽  
Time Points ◽  
Total Fat ◽  
Over Time

Breakfast cereal improves overall diet quality yet is under constant scrutiny with assertions that the category has not improved over time. This study aimed to comprehensively analyse the category of breakfast cereals, the nutritional values, and health claims across eight distinct sub-categories at four time points (2013, 2015, 2018, and 2020). An audit of products from four major supermarkets in metropolitan Sydney (Aldi, Coles, IGA, and Woolworths) collected ingredient lists, nutrition information, claims and Health Star Rating (HSR) for biscuits and bites; brans; bubbles, puffs, and flakes; granola and clusters; hot cereal flavoured; hot cereal plain; muesli; breakfast biscuits. The median (IQR) were calculated for energy, protein, fat, saturated fat, carbohydrate, sugars, dietary fibre, and sodium for comparisons over time points by nutrient. Data from 2013 was compared with 2020 (by sub-category and then for a sub-section of common products available at each time point). Product numbers between 2013 (n = 283) and 2020 (n = 543) almost doubled, led by granola and clusters. Whole grain cereals ≥ 8 g/serve made up 67% of products (↑114%). While there were positive changes in nutrient composition over time within the full data set, the most notable changes were in the nutrition composition of cereals marketed as the same product in both years (n = 134); with decreases in mean carbohydrate (2%), sugar (10%) and sodium (16%) (p < 0.000), while protein and total fat increased significantly (p = 0.036; p = 0.021). Claims regarding Dietary Fibre and Whole Grain doubled since 2013. Analysis of sub-categories of breakfast cereal assisted in identifying some changes over time, but products common to both timeframes provided a clearer analysis of change within the breakfast category, following introduction of HSR. Whole grain products were lower in the two target nutrients, sodium and sugars, and well-chosen products represent a better choice within this category.

Ultrasonic Imaging of a Crack Using Modified Time Reversal

2016 ◽  
Vol 846 ◽  
pp. 553-558
Author(s):  
Jed Guinto ◽  
Philippe Blanloeuil ◽  
Chun H. Wang ◽  
Francis Rose ◽  
Martin Veidt
Keyword(s):  
Time Reversal ◽  
Computational Simulation ◽  
Field Measurements ◽  
Tone Burst ◽  
Data Matrix ◽  
Accurate Estimation ◽  
Diffraction Tomography ◽  
Static Data ◽  
Reconstruction Quality ◽  
Scatter Field

A majority of the research in Structural Health Monitoring focuses on detection of damage. This paper presents a method of imaging crack damage in an isotropic material using the Time Reversal imaging algorithm. Inputs for the algorithm are obtained via computational simulation of the propagation field of a crack in a medium under tone-burst excitation. The approach is similar to existing techniques such as Diffraction Tomography which makes use of the multi-static data matrix constructed using scatter field measurements from the computational simulation. Results indicate excellent reconstruction quality and accurate estimation of damage size.

Estimating Heterogeneous Treatment Effects and the Effects of Heterogeneous Treatments with Ensemble Methods

2017 ◽  
Vol 25 (4) ◽  
pp. 413-434 ◽  
Author(s):  
Justin Grimmer ◽  
Solomon Messing ◽  
Sean J. Westwood
Keyword(s):  
Treatment Effects ◽  
Ensemble Methods ◽  
Ensemble Method ◽  
Superior Performance ◽  
Accurate Estimation ◽  
Randomized Experiments ◽  
Heterogeneous Treatment Effects ◽  
Data Set ◽  
Heterogeneous Effects ◽  
The Ensemble Method

Randomized experiments are increasingly used to study political phenomena because they can credibly estimate the average effect of a treatment on a population of interest. But political scientists are often interested in how effects vary across subpopulations—heterogeneous treatment effects—and how differences in the content of the treatment affects responses—the response to heterogeneous treatments. Several new methods have been introduced to estimate heterogeneous effects, but it is difficult to know if a method will perform well for a particular data set. Rather than using only one method, we show how an ensemble of methods—weighted averages of estimates from individual models increasingly used in machine learning—accurately measure heterogeneous effects. Building on a large literature on ensemble methods, we show how the weighting of methods can contribute to accurate estimation of heterogeneous treatment effects and demonstrate how pooling models lead to superior performance to individual methods across diverse problems. We apply the ensemble method to two experiments, illuminating how the ensemble method for heterogeneous treatment effects facilitates exploratory analysis of treatment effects.

scholarly journals Serum sodium changes in marathon participants who use NSAIDs

2018 ◽  
Vol 4 (1) ◽  
pp. e000364 ◽  
Author(s):  
Steven Whatmough ◽  
Stephen Mears ◽  
Courtney Kipps
Keyword(s):  
Serum Sodium ◽  
Fluid Intake ◽  
Large City ◽  
Control Group ◽  
Full Data ◽  
Data Set ◽  
Nsaid Group ◽  
Total Body ◽  
Average Serum ◽  
Internal And External Factors

IntroductionThe primary mechanism through which the development of exercise-associated hyponatraemia (EAH) occurs is excessive fluid intake. However, many internal and external factors have a role in the maintenance of total body water and non-steroidal anti-inflammatory medications (NSAIDs) have been implicated as a risk factor for the development of EAH. This study aimed to compare serum sodium concentrations ([Na]) in participants taking an NSAID before or during a marathon (NSAID group) and those not taking an NSAID (control group).MethodsParticipants in a large city marathon were recruited during race registration to participate in this study. Blood samples and body mass measurements took place on the morning of the marathon and immediately post marathon. Blood was analysed for [Na]. Data collected via questionnaires included athlete demographics, NSAID use and estimated fluid intake.ResultsWe obtained a full data set for 28 participants. Of these 28 participants, 16 took an NSAID on the day of the marathon. The average serum [Na] decreased by 2.1 mmol/L in the NSAID group, while it increased by 2.3 mmol/L in the control group NSAID group (p=0.0039). Estimated fluid intake was inversely correlated with both post-marathon serum [Na] and ∆ serum [Na] (r=−0.532, p=0.004 and r=−0.405 p=0.032, respectively).ConclusionSerum [Na] levels in participants who used an NSAID decreased over the course of the marathon while it increased in those who did not use an NSAID. Excessive fluid intake during a marathon was associated with a lower post-marathon serum [Na].

Sign in / Sign up

Export Citation Format

Share Document