Performance of Weibull function as a diameter distribution model for Pinus thunbergii stands in the eastern coast of South Korea

Abino, Azyleah C.; Kim, Sung Yong; Lumbres, Roscinto Ian C.; Jang, Min; Youn, Ho Joong; Park, Ki Hyung; Lee, Young Jin

doi:10.1007/s11629-014-3243-5

Cited by 6 publications

(3 citation statements)

References 34 publications

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“…The Weibull function has been used widely in predicting diameter distribution for various types of forests and obtained satisfactory results [18,[22][23][24][25][26][44][45][46]. Because it possesses many advantages, including the flexibility of its curve for characterizing different forest types, its parameters could be helpful to explain the stand structure through DBH distribution, and the interval of DBH classes could be easy to calculate [18,22,23].…”

Section: Discussionmentioning

confidence: 99%

Application of Models to Predict Stand Volume, Aboveground Biomass Accumulation, and Carbon Storage Capacity for a Konishii Fir (Cunninghamia konishii Hayata) Plantation in Central Taiwan

Hussain

Lin

Yen

et al. 2021

Forests

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Konishii fir (Cunninghamia konishii Hayata) is n important conifer in Taiwan. The purpose of this study was to predict stand volume (V), aboveground biomass accumulation (AGB), and aboveground carbon storage (AGCST) for a Konishii fir plantation. This study was located at the Huisun Experimental Forest Station of Nantou County located in central Taiwan. Four sample plots, each with an area of 0.05 ha, were installed and surveyed from 29 June to 2 July 2020. Two models, the diameter distribution model (DDM) and allometric model (AM), were used to predict V, AGB, and AGCST. Each item predicted by these two models was compared by the paired sample t-test. We employed the Weibull function to quantify stand diameter distribution and this function can effectively quantify diameter distribution, because all plots passed the examination by the Kolmogorov–Smirnov test (non-significant). Therefore, the Weibull function was suitable for developing the DDM. The predicted V, AGB, and AGCST were 538.43 ± 140.52 m3 ha−1, 203.25 ± 52.79 Mg ha−1, and 100.85 ± 26.30 Mg ha−1 by DDM; and 555.90 ± 145.42 m3 ha−1, 209.10 ± 51.25 Mg ha−1, and 103.78 ± 25.51 Mg ha−1 by AM, respectively. Each item was insignificantly different between DDM and AM, indicating similarity in results for both predictions. Meanwhile, using DDM is advantageous, as it can provide more yield information in diameter classes; therefore, this approach was recommended for yield prediction of the Konishii fir plantation.

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Section: Discussionmentioning

confidence: 99%

Application of Models to Predict Stand Volume, Aboveground Biomass Accumulation, and Carbon Storage Capacity for a Konishii Fir (Cunninghamia konishii Hayata) Plantation in Central Taiwan

Hussain

Lin

Yen

et al. 2021

Forests

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“…Weibull distribution parameters have been predicted using parameter prediction methods (PPM) (Abino et al 2016;Özçelik et al 2016) and various parameter recovery methods (PRM) (Leduc et al 2001;Liu et al 2004;Burkhart and Tomé 2012). Ordinary least squares (OLS) and seemingly unrelated regression (SUR) analysis have been used to estimate the coefficients of the parameter prediction models (Zellner 1962;Siipilehto et al 2007;Poudel and Cao 2013).…”

Section: Introductionmentioning

confidence: 99%

Developing Weibull-based diameter distributions for the major coniferous species in Heilongjiang Province, China

Jin

Pukkala

et al. 2023

J. For. Res.

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Diameter distribution models play an important role in forest inventories, growth prediction, and management. The Weibull probability density function is widely used in forestry. Although a number of methods have been proposed to predict or recover the Weibull distribution, their applicability and predictive performance for the major tree species of China remain to be determined. Trees in sample plots of three even-aged coniferous species (Larix olgensis, Pinus sylvestris and Pinus koraiensis) were measured both in un-thinned and thinned stands to develop parameter prediction models for the Weibull probability density function. Ordinary least squares (OLS) and maximum likelihood regression (MLER), as well as cumulative distribution function regression (CDFR) were used, and their performance compared. The results show that MLER and CDFR were better than OLS in predicting diameter distributions of tree plantations. CDFR produced the best results in terms of fitting statistics. Based on the error statistics calculated for different age groups, CDFR was considered the most suitable method for developing prediction models for Weibull parameters in coniferous plantations.

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“…  = Crown length (m) of  th individual trees,   = Tree expansion factor corrected to a per ha basis for the  th trees.같이 적합도지수, 변동계수 등으로 검토하였다. 시업지 임분 의 D q , D 0 , D 25 , D 50 , D 95 의 적합도지수는 0.58 (D 0 )∼0.96 (D 50 )으로 나타났으며, 비시업지 임분은 0.58 (D 0 )∼0.96 (D 50 )로 기존 연구에서 제시한 모델의 모수 적합도지수와 유사하게 나타났다(Lumbres and Lee, 2014;Abino et al, 2016;Lee et al, 2018).고사율에 영향을 미치는 인자들의 조합을 고려하여 총…”

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A Dynamic Growth Model for Predicting Forest Fire Fuel Loads for Pinus Koraiensis Stands in South Korea

Lee¹,

Kim²,

Lee³

et al. 2019

J. Korean Soc. Hazard Mitig

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The objective of this study is to predict the effects of forest management activities on canopy fuel characteristics for Pinus koraiensis stands. We used data from 136 managed stands and 23 unmanaged stands of the National Forest Inventory for this study. Weibull function and mortality models were developed. A dynamic growth model in which models were interactively linked was prepared to predict stand growth and forest fuel loads after considering the mortality rate. As a result, after 20 years of managed stand data, the increase in available canopy fuel load was predicted to be about 12.8 ton/ha and increase in available canopy bulk density was predicted to be about 0.2kg/㎥. However, the increase in available canopy fuel load for unmanaged stands was about 15.2 ton/ha and the increase in available canopy bulk density was about 0.3 kg/㎥. These results showed that there were higher forest fuel loads in unmanaged stands than in managed stands. The risk of crown fire hazard is higher, and the forest fire hazard of unmanaged stands is judged to be higher than that of managed stands of Pinus koraiensis species in South Korea. 요 지 본 연구는 산불에 취약한 대표 침엽수종인 잣나무 임분을 대상으로 산림시업이 수관연료특성 변화에 미치는 영향을 예측하고자 하였다. 이를 위해 국가산림자원조사 자료 중 산림시업지 잣나무림 136 plots, 비시업지 잣나무림 23 plots를 분석자료로 활용하였다. 시간이 경과됨에 따라 고사되는 임목의 특성을 고려하기 위해 Weibull 함수에 고사모델을 적용하여 임분특성별 산불연료량을 추정할 수 있는 동적생장 모델을 구축하였다. 그 결과, 시업지 임분의 20년 후 연소가능한 수관연료량 증가량은 약 12.8 ton/ha, 연소가능한 수관연료밀도는 약 0.2 kg/㎥로 예측된 반면, 비시업지 임분의 20년 후 연소가능한 수관연료량 증가량은 15.2 ton/ha, 연소가능한 수관연료밀도는 약 0.3 kg/㎥로 시업지 임분에 비해 비시업지 임분의 산불연료의 증가량이 높게 예측되었다. 따라서 비시업지 임분에서 산불확산 요소로 작용할 수 있는 산불 연료량 축적량이 더 높게 예측됨에 따라 수관화 확산 위험성이 더 높을 것으로 판단된다.

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Performance of Weibull function as a diameter distribution model for Pinus thunbergii stands in the eastern coast of South Korea

Cited by 6 publications

References 34 publications

Application of Models to Predict Stand Volume, Aboveground Biomass Accumulation, and Carbon Storage Capacity for a Konishii Fir (Cunninghamia konishii Hayata) Plantation in Central Taiwan

Application of Models to Predict Stand Volume, Aboveground Biomass Accumulation, and Carbon Storage Capacity for a Konishii Fir (Cunninghamia konishii Hayata) Plantation in Central Taiwan

Developing Weibull-based diameter distributions for the major coniferous species in Heilongjiang Province, China

A Dynamic Growth Model for Predicting Forest Fire Fuel Loads for Pinus Koraiensis Stands in South Korea

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