A comparison between derivative and numerical optimization methods used for diameter distribution estimation

Gorgoso-Varela, José Javier; Ogana, Friday Nwabueze; Ige, P. O.

doi:10.1080/02827581.2020.1760343

Cited by 13 publications

(26 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Gorgoso et al (2007) reported similar result for beech stand in northwest Spain. Recently, Gorgoso-Varela et al (2020) observed smallest KS value for MLE in three species -E. globulus Labill, Pinus radiata D. Don. (temperate forest) and G. arborea (tropical forest).…”

Section: Discussionmentioning

confidence: 99%

An evaluation of ten estimators for fitting two-parameter weibull function to Nigerian forest stands

Ogana

2020

Eurasian Journal of Forest Science

Self Cite

View full text Add to dashboard Cite

The quality fit produce by distribution function such as the Weibull depends to an extent the type of estimator used to derive its parameters. Inappropriate choice of estimator could affect management decision. Though several estimators have been developed for the Weibull function, their application to forestry have been relatively few. Therefore, this study evaluated ten estimators of the Weibull parameters using tree diameter data from five production forest plantations in Nigeria. The estimators were generalized least type I and type II, L-moment, moments, maximum likelihood, percentiles, rank correlation, least squares, U-statistics and weighted least squares. The quality of fits of the Weibull function were evaluated with Kolmogorov-Smirnov, Anderson-Darling, Cramervon Mises, Akaike information criterion and Bayesian information criterion. Relative rank sum from the evaluation statistics of the methods was analysed using One-way analysis of variance. The results showed that weighted least square had the smallest statistics and relative rank, but not significantly different from L-moment, moments and maximum likelihood (p > 0.05). The performances of least squares, generalized least type I and type II, percentiles and U-statistics were relatively poor. Thus, either the weighted least squares, moments-based or MLE could be used for the Weibull function in the diameter distribution of forest stands in Nigeria.

show abstract

Section: Discussionmentioning

confidence: 99%

An evaluation of ten estimators for fitting two-parameter weibull function to Nigerian forest stands

Ogana

2020

Eurasian Journal of Forest Science

Self Cite

View full text Add to dashboard Cite

show abstract

“…For the Weibull-2P and gamma-2P functions, the value of the location parameters was zero. Scale parameters and the upper limit of the four-parameter functions (Johnson's SB, beta and generalized beta) were established as the maximum diameter of the distributions (d max ) and the upper limit of the largest diameter class for the beta function [27,28] to improve parameters' convergence. The size of the diameter classes was assumed to equal 1 cm.…”

Section: The Gamma Functionmentioning

confidence: 99%

Modeling Diameter Distributions with Six Probability Density Functions in Pinus halepensis Mill. Plantations Using Low-Density Airborne Laser Scanning Data in Aragón (Northeast Spain)

Gorgoso-Varela

Ponce²,

Rodríguez-Puerta

2021

Remote Sensing

View full text Add to dashboard Cite

The diameter distributions of trees in 50 temporary sample plots (TSPs) established in Pinus halepensis Mill. stands were recovered from LiDAR metrics by using six probability density functions (PDFs): the Weibull (2P and 3P), Johnson’s SB, beta, generalized beta and gamma-2P functions. The parameters were recovered from the first and the second moments of the distributions (mean and variance, respectively) by using parameter recovery models (PRM). Linear models were used to predict both moments from LiDAR data. In recovering the functions, the location parameters of the distributions were predetermined as the minimum diameter inventoried, and scale parameters were established as the maximum diameters predicted from LiDAR metrics. The Kolmogorov–Smirnov (KS) statistic (Dn), number of acceptances by the KS test, the Cramér von Misses (W2) statistic, bias and mean square error (MSE) were used to evaluate the goodness of fits. The fits for the six recovered functions were compared with the fits to all measured data from 58 TSPs (LiDAR metrics could only be extracted from 50 of the plots). In the fitting phase, the location parameters were fixed at a suitable value determined according to the forestry literature (0.75·dmin). The linear models used to recover the two moments of the distributions and the maximum diameters determined from LiDAR data were accurate, with R2 values of 0.750, 0.724 and 0.873 for dg, dmed and dmax. Reasonable results were obtained with all six recovered functions. The goodness-of-fit statistics indicated that the beta function was the most accurate, followed by the generalized beta function. The Weibull-3P function provided the poorest fits and the Weibull-2P and Johnson’s SB also yielded poor fits to the data.

show abstract

“…This method is based on the relationship between the parameters of 3P-Weibull and the first and second diameter moment i.e., arithmetic mean and variance, respectively; expressed as equation ( 5) and ( 6). This method was recently used by other researchers (Gorgoso-Varela et al, 2020;Pogoda et al, 2020;Sun et al, 2019):…”

Section: Momentsmentioning

confidence: 99%

Application of the BDq method to complex tropical mixed forest ecosystems in Nigeria

2021

Self Cite

View full text Add to dashboard Cite

The absence of management practice/silvicultural treatments in the complex tropical mixed forests of Nigeria has led to uncontrolled logging in natural forest stands and loss of biodiversity. To sustain production, protection and conservation in these complex tropical mixed stands, this study proposes the application of a selection method – the BDq method (B: basal area, D: maximum diameter, q-ratio) to manage these stands. Two strata were used as a pilot test: stratum 1 consisted of 15 plots and stratum 2 of 7 plots, each with an area of 0.25 ha. Only trees with a diameter at breast height (d) ≥ 10.0 cm were considered in this study. Harvesting with the BDq method was quantified, by setting B at 20 m2, 25 m2 and 30 m2/ha corresponding respectively to intensive, medium and light harvesting regimes. D was set at 65 cm and the q-ratio was computed for each plot. The results showed that the three BDq regimes prescribed (intensive, medium and light) yielded reasonable felling intensities (FI), derived as the percentage of extracted volume (Vext) and biomass (Wext). The Vext and FI for stratum 1 ranged from 39.94-62.30 m3/ha and 11.22-18.18%; the results for stratum 2 were 30.44-51.33 m3/ha and 10.02-17.57%. For biomass, the Wext and FI ranged from 18.46-29.82 t/ha and 9.40-15.95% for stratum 1 and 14.16-24.82 t/ha and 9.73-17.50% for stratum 2. These findings show that applying the BDq method to the complex tropical mixed forests of Nigeria would yield attractive stands.

show abstract

A comparison between derivative and numerical optimization methods used for diameter distribution estimation

Cited by 13 publications

References 31 publications

An evaluation of ten estimators for fitting two-parameter weibull function to Nigerian forest stands

An evaluation of ten estimators for fitting two-parameter weibull function to Nigerian forest stands

Modeling Diameter Distributions with Six Probability Density Functions in Pinus halepensis Mill. Plantations Using Low-Density Airborne Laser Scanning Data in Aragón (Northeast Spain)

Application of the BDq method to complex tropical mixed forest ecosystems in Nigeria

Contact Info

Product

Resources

About