Accurate and efficient estimation of forest growth and live biomass is a critical element in assessing potential responses to forest management and environmental change. The objective of this study was to develop mode...Accurate and efficient estimation of forest growth and live biomass is a critical element in assessing potential responses to forest management and environmental change. The objective of this study was to develop models to predict longleaf pine tree diameter at breast height （dbh） and merchantable stem volume （V） using data obtained from field measurements. We used longleaf pine tree data from 3,376 planted trees on 127 permanent plots located in the U.S. Gulf Coastal Plain region to fit equations to predict dbh and V as functions of tree height （H） and crown area （CA）. Prediction of dbh as a function of H improved when CA was added as an additional independent variable. Similarly, predic- tions of V based on H improved when CA was included. Incorporation of additional stand variables such as age, site index, dominant height, and stand density were also evaluated but resulted in only small improvements in model performance. For model testing we used data from planted and naturally-regenerated trees located inside and outside the geographic area used for model fitting. Our results suggest that the models are a robust alternative for dbh and V estimations when H and CA are known on planted stands with potential for naturally-regenerated stands, across a wide range of ages. We discuss the importance of these models for use with metrics derived from remote sensing data.展开更多
Advancements in airborne LiDAR analysis technology have made it possible to quantify forest resource volumes based on individual trees, and such technology may soon replace field surveys. Unlike individual tree detect...Advancements in airborne LiDAR analysis technology have made it possible to quantify forest resource volumes based on individual trees, and such technology may soon replace field surveys. Unlike individual tree detection or tree height measurements, diameter at breast height (DBH) is difficult to determine directly from measured data and is instead estimated indirectly using the correlation between crown size and DBH. Indicators that represent crown size include crown area, surface area, length, and length ratio, and were utilized with tree height as explanatory variables in ten combinations to determine a regression formula. DBH and tree height calculated from the regression formula were applied to an equation to calculate stem volumes of individual trees. Airborne LiDAR measurements were taken using ALS50-II and ALS60 (Leica) at a density of 4 points/m2. An evaluation of the relationship between the regression formulae and DBH estimates indicated that a combination of crown area, tree height, and crown ratio for Japanese cedar, and a combination of crown area and tree height for Japanese cypress, yielded the highest coefficients of determination. The average error and RMSE were 6.9% and 2.38 cm respectively for Japanese cedar, while the corresponding values for Japanese cypress were 8.35% and 2.51 cm. Once the relationship was extended to the stem volumes of individual trees, the average error was 14.4% and RMSE was 0.10 m3 for Japanese cedar. The corresponding values for Japanese cypress were 18.9% and 0.10 m3. These results demonstrate the potential use of airborne LiDAR as a substitute for field surveys.展开更多
The number and composition of species in a community can be quantified withα-diversity indices,including species richness(R),Simpson’s index(D),and the Shannon-Wiener index(H΄).In forest communities,there are large ...The number and composition of species in a community can be quantified withα-diversity indices,including species richness(R),Simpson’s index(D),and the Shannon-Wiener index(H΄).In forest communities,there are large variations in tree size among species and individu-als of the same species,which result in differences in eco-logical processes and ecosystem functions.However,tree size inequality(TSI)has been largely neglected in studies using the available diversity indices.The TSI in the diameter at breast height(DBH)data for each of 99920 m×20 m forest census quadrats was quantified using the Gini index(GI),a measure of the inequality of size distribution.The generalized performance equation was used to describe the rotated and right-shifted Lorenz curve of the cumulative proportion of DBH and the cumulative proportion of number of trees per quadrat.We also examined the relationships ofα-diversity indices with the GI using correlation tests.The generalized performance equation effectively described the rotated and right-shifted Lorenz curve of DBH distributions,with most root-mean-square errors(990 out of 999 quadrats)being<0.0030.There were significant positive correlations between each of threeα-diversity indices(i.e.,R,D,and H’)and the GI.Nevertheless,the total abundance of trees in each quadrat did not significantly influence the GI.This means that the TSI increased with increasing spe-cies diversity.Thus,two new indices are proposed that can balanceα-diversity against the extent of TSI in the com-munity:(1−GI)×D,and(1−GI)×H’.These new indices were significantly correlated with the original D and H΄,and did not increase the extent of variation within each group of indices.This study presents a useful tool for quantifying both species diversity and the variation in tree sizes in forest communities,especially in the face of cumulative species loss under global climate change.展开更多
[Objectives]This study was conducted to provide good basic research data for Cunninghamia lanceolata plantations in southern Anhui,so as to improve local ecological,economic and social benefits.[Methods]A 22-year-old ...[Objectives]This study was conducted to provide good basic research data for Cunninghamia lanceolata plantations in southern Anhui,so as to improve local ecological,economic and social benefits.[Methods]A 22-year-old near-mature C.lanceolata plantation in Lingnan Forest Farm,Xiuning County,Huangshan City,Anhui Province was investigated and analyzed by sample plot survey.[Results]The average DBH value of the C.lanceolata plantation at the lower slope was the largest,24.7%and 19.2%higher than those at the upper and middle slopes,respectively.The average single plant wood volume at the lower slope was 47.6%and 49.1%higher than those in the upper and middle slopes,respectively.However,the average tree heights at various slope positions showed little difference.Meanwhile,all the indexes showed the phenomenon of semi-shady slope>sunny slope>shady slope under different slope directions.Among them,the effect of slope position on DBH was extremely significant,but the effect of slope direction on DBH was not significant,and slope position,slope direction and the interaction of slope direction and slope position had no significant effects on the tree height of the C.lanceolata plantation.In addition,slope direction and slope position had extremely significant effects on single plant wood volume.From the overall growth situation of the C.lanceolata plantation in Lingnan Forest Farm,the slope position factor had greater effects on various indexes of forest growth than the slope direction factor,mainly manifested in that the lower slope was better than the middle slope,and the middle slope position was better than the upper slope,while although slope direction had some effect on the growth of the C.lanceolata plantation,the influence degree was not as significant as that of slope position.[Conclusions]This study provides some reference for the adjustment and optimization,development and renewal of C.lanceolata plantation structure in the later period in this area,as well as some data support for other theoretical research on economic forests.展开更多
The development of equations to predict tree height, crown diameter, crown depth from stem diameter of a tree species enables arborists, researchers, and urban forest managers to model costs and benefits, analyze alte...The development of equations to predict tree height, crown diameter, crown depth from stem diameter of a tree species enables arborists, researchers, and urban forest managers to model costs and benefits, analyze alternative management scenarios, and determine the best management practices for sustainable forests. The objective of this study was to develop regression prediction models for tree age, tree height, crown diameter, crown ratio and crown depth for A. senegal growing in Ferlo, in the northern Senegal. Four plantations of different years old (ISRA, 10 years old plantations, Ndodj, 8 years old plantations, Boulal, 5 years old plantations and Déali, 4 years old plantations) were selected. The following dendometric variables: crown height, crown diameter, stem diameter at the breast height, stem basal diameter (at 0.30 m) and the height from the tree base to first branch were measured on a total of 489 trees. The results suggested that the ecological structure of the different year old A. Senegal plantation revealed a bell-shaped form with left dissymmetric distribution indicating a predominance of individuals with small diameter at breast height. Allometry study of A. Senegal showed highly significant positive correlations (p = 0.00) between stem diameter at breast height, stem basal diameter, tree height, crown diameter and crown depth. Positive correlations were also found between crown diameter, tree height and crown height. Prediction models derived from these relationships can be used to estimate the tree height, stem diameter at breast height and crown depth from crown diameter with greater precision. As for A. Senegal age estimation, the established model is not strong as it can explain only 49.1% of the age variation.展开更多
The role of cocoa systems for climate change mitigation and adaptation has increased substantially because of their capability to trap carbon dioxide from the atmosphere and deposited in the cocoa trees as carbon. Dev...The role of cocoa systems for climate change mitigation and adaptation has increased substantially because of their capability to trap carbon dioxide from the atmosphere and deposited in the cocoa trees as carbon. Development of aboveground biomass (AGB) models for cocoa plantations is crucial for accurate estimation of carbon stocks in the cocoa systems, however, allometric models for estimating AGB for cocoa plantations remain a challenge for cocoa producing countries in Sub-Saharan Africa especially Ghana. The aim of this study is to develop allometric model that can be used for the estimation of AGB for cocoa plantations in Ghana, as well as West Africa. Destructive sampling was carried out on 110 cocoa trees obtained from the cocoa rehabilitation exercise for the development of the allometric models. Diameter at breast height (D), total tree height (H) and wood density (ρ) were used as predictors to develop seven models. The best model was selected based on coefficient of determination (R<sup>2</sup>), index of agreement (I<sub>A</sub>), root mean squared error (RMSE), bias (E%), mean absolute error (MAE) and corrected akaike information criterion (AIC<sub>C</sub>) and percentage relative standard error (PRSE) of the estimated parameters. The selected model, which was the one with the predictors D and ρ, was given as;AGB = 0.7217ρ(D<sup>2</sup>)<sup>0.921</sup>. It was compared with the Yuliasmara et al. (2009) cocoa model using equivalence test and paired sample t-test. The two models were found to be equivalent within ±10% of their mean predictions (p < 0.0001) for one-tailed tests for both lower and upper limits, while the paired sample t-test rejected the null hypothesis with mean difference of 14.16 kg between the two models. This study is significant because it has provided a model to estimate AGB for the cocoa plantations in Ghana which is very important for the Ghana Cocoa-Forest REDD+ Programme and also can be used by other West African cocoa producing countries.展开更多
Background: Modelling aboveground biomass(AGB) in forest and woodland ecosystems is critical for accurate estimation of carbon stocks. However, scarcity of allometric models for predicting AGB remains an issue that ha...Background: Modelling aboveground biomass(AGB) in forest and woodland ecosystems is critical for accurate estimation of carbon stocks. However, scarcity of allometric models for predicting AGB remains an issue that has not been adequately addressed in Africa. In particular, locally developed models for estimating AGB in the tropical woodlands of Ghana have received little attention. In the absence of locally developed allometric models, Ghana will continue to use Tier 1 biomass data through the application of pantropic models. Without local allometric models it is not certain how Ghana would achieve Tier 2 and 3 levels under the United Nations programme for reducing emissions from deforestation and forest degradation. The objective of this study is to develop a mixedspecies allometric model for use in estimating AGB for the tropical woodlands in Ghana. Destructive sampling was carried out on 745 trees(as part of charcoal production) for the development of allometric equations. Diameter at breast height(dbh, i.e. 1.3 m above ground level), total tree height(H) and wood density(ρ) were used as predictors for the models. Seven models were compared and the best model selected based on model efficiency,bias(%) and corrected Akaike Information Criterion. The best model was validated by comparing its results with those of the pantropic model developed by Chave et al.(Glob Chang Biol 20:3177–3190, 2014) using equivalence test and conventional paired t-test.Results: The results revealed that the best model for estimating AGB in the tropical woodlands is AGB =0.0580ρ((dbh)2 H)0.999. The equivalence test showed that this model and the pantropic model developed by Chave et al.(Glob Chang Biol 20:3177–3190, 2014) were equivalent within ±10% of their mean predictions(p-values <0.0001 for one-tailed t-tests for both lower and upper bounds at 5% significant level), while the paired t-test revealed that the mean(181.44 ± 18.25 kg) of the model predictions of the best model of this study was significantly(n = 745, mean diff. = 16.50 ± 2.45 kg;S.E. = 1.25 kg;p < 0.001) greater than that(164.94 ± 15.82 kg) of the pantropic model of Chave et al.(Glob Chang Biol 20:3177–3190, 2014).Conclusion: The model developed in this study fills a critical gap in estimating AGB in tropical woodlands in Ghana and other West African countries with similar ecological conditions. Despite the equivalence with the pantropic model it remains superior to the model of Chave et al.(Glob Chang Biol 20:3177–3190, 2014) for the estimation of AGB in local tropical woodlands. It is a relevant tool for the attainment of Tier 2 and 3 levels for REDD+. The model is recommended for use in the tropical woodlands in Ghana and other West African countries in place of the use of pantropic models.展开更多
【目的】以人工落叶松为例,探索基于无人机激光雷达(Unmanned aerial vehicle LiDAR,UAVLiDAR)点云的单木探测提取树高的误差对胸径反演的影响并校准,实现单木参数(胸径、树高)的准确度量,为大尺度高效便捷估测单木参数提供新的思路。...【目的】以人工落叶松为例,探索基于无人机激光雷达(Unmanned aerial vehicle LiDAR,UAVLiDAR)点云的单木探测提取树高的误差对胸径反演的影响并校准,实现单木参数(胸径、树高)的准确度量,为大尺度高效便捷估测单木参数提供新的思路。【方法】以东北林业大学帽儿山实验林场13块4个龄组(幼龄林、中龄林、近熟林和成熟林)的落叶松人工林样地UAV-LiDAR数据及野外调查数据为数据源,基于UAVLiDAR点云的单木探测提取的树高,分别以普通最小二乘法(Ordinary least squares,OLS)和3种误差变量回归(标准主轴(Standard major axis,SMA)、远程主轴(Ranged major axis,RMA)和极大似然估计(Maximum likelihood estimate,MLE))构建胸径-树高模型,研究探测误差对各龄组人工落叶松胸径反演的影响并校准。【结果】利用UAV-LiDAR点云的单木探测提取4个龄组树高的相对均方根误差(rRMSE),误差范围为3.41%~5.14%;在胸径-树高模型预测方面,3种误差变量回归均优于OLS,RMA预测效果最好,4个龄组反演单木胸径的rRMSE降低了2.21%~3.58%。【结论】当满足模型假设时,误差变量回归比OLS在预测响应变量方面表现更好,是估计无偏的模型系数的理想方法,本研究中RMA方法表现最好;本研究所构建的人工落叶松胸径反演模型具有较高的预估精度,各项误差均保持在合理范围内,可实现应用UAV-LiDAR高效便捷地估测大尺度森林单木参数的目的,可在实践中推广。展开更多
基金supported by the U.S.Department of Defense,through the Strategic Environmental Research and Development Program(SERDP)
文摘Accurate and efficient estimation of forest growth and live biomass is a critical element in assessing potential responses to forest management and environmental change. The objective of this study was to develop models to predict longleaf pine tree diameter at breast height （dbh） and merchantable stem volume （V） using data obtained from field measurements. We used longleaf pine tree data from 3,376 planted trees on 127 permanent plots located in the U.S. Gulf Coastal Plain region to fit equations to predict dbh and V as functions of tree height （H） and crown area （CA）. Prediction of dbh as a function of H improved when CA was added as an additional independent variable. Similarly, predic- tions of V based on H improved when CA was included. Incorporation of additional stand variables such as age, site index, dominant height, and stand density were also evaluated but resulted in only small improvements in model performance. For model testing we used data from planted and naturally-regenerated trees located inside and outside the geographic area used for model fitting. Our results suggest that the models are a robust alternative for dbh and V estimations when H and CA are known on planted stands with potential for naturally-regenerated stands, across a wide range of ages. We discuss the importance of these models for use with metrics derived from remote sensing data.
文摘Advancements in airborne LiDAR analysis technology have made it possible to quantify forest resource volumes based on individual trees, and such technology may soon replace field surveys. Unlike individual tree detection or tree height measurements, diameter at breast height (DBH) is difficult to determine directly from measured data and is instead estimated indirectly using the correlation between crown size and DBH. Indicators that represent crown size include crown area, surface area, length, and length ratio, and were utilized with tree height as explanatory variables in ten combinations to determine a regression formula. DBH and tree height calculated from the regression formula were applied to an equation to calculate stem volumes of individual trees. Airborne LiDAR measurements were taken using ALS50-II and ALS60 (Leica) at a density of 4 points/m2. An evaluation of the relationship between the regression formulae and DBH estimates indicated that a combination of crown area, tree height, and crown ratio for Japanese cedar, and a combination of crown area and tree height for Japanese cypress, yielded the highest coefficients of determination. The average error and RMSE were 6.9% and 2.38 cm respectively for Japanese cedar, while the corresponding values for Japanese cypress were 8.35% and 2.51 cm. Once the relationship was extended to the stem volumes of individual trees, the average error was 14.4% and RMSE was 0.10 m3 for Japanese cedar. The corresponding values for Japanese cypress were 18.9% and 0.10 m3. These results demonstrate the potential use of airborne LiDAR as a substitute for field surveys.
基金supported by the National Natural Science Foundation of China(32101260).
文摘The number and composition of species in a community can be quantified withα-diversity indices,including species richness(R),Simpson’s index(D),and the Shannon-Wiener index(H΄).In forest communities,there are large variations in tree size among species and individu-als of the same species,which result in differences in eco-logical processes and ecosystem functions.However,tree size inequality(TSI)has been largely neglected in studies using the available diversity indices.The TSI in the diameter at breast height(DBH)data for each of 99920 m×20 m forest census quadrats was quantified using the Gini index(GI),a measure of the inequality of size distribution.The generalized performance equation was used to describe the rotated and right-shifted Lorenz curve of the cumulative proportion of DBH and the cumulative proportion of number of trees per quadrat.We also examined the relationships ofα-diversity indices with the GI using correlation tests.The generalized performance equation effectively described the rotated and right-shifted Lorenz curve of DBH distributions,with most root-mean-square errors(990 out of 999 quadrats)being<0.0030.There were significant positive correlations between each of threeα-diversity indices(i.e.,R,D,and H’)and the GI.Nevertheless,the total abundance of trees in each quadrat did not significantly influence the GI.This means that the TSI increased with increasing spe-cies diversity.Thus,two new indices are proposed that can balanceα-diversity against the extent of TSI in the com-munity:(1−GI)×D,and(1−GI)×H’.These new indices were significantly correlated with the original D and H΄,and did not increase the extent of variation within each group of indices.This study presents a useful tool for quantifying both species diversity and the variation in tree sizes in forest communities,especially in the face of cumulative species loss under global climate change.
基金Supported by General Project of Natural Science Research in Colleges and Universities in Anhui Province(KJHS2019B13)School-level Talents Start-up Project of Huangshan University(2019xkjq012)+1 种基金Horizontal Topic of Huangshan University(hxkt2020023)Undergraduate Innovation and Entrepreneurship Training Program of Anhui Province(S202110375082).
文摘[Objectives]This study was conducted to provide good basic research data for Cunninghamia lanceolata plantations in southern Anhui,so as to improve local ecological,economic and social benefits.[Methods]A 22-year-old near-mature C.lanceolata plantation in Lingnan Forest Farm,Xiuning County,Huangshan City,Anhui Province was investigated and analyzed by sample plot survey.[Results]The average DBH value of the C.lanceolata plantation at the lower slope was the largest,24.7%and 19.2%higher than those at the upper and middle slopes,respectively.The average single plant wood volume at the lower slope was 47.6%and 49.1%higher than those in the upper and middle slopes,respectively.However,the average tree heights at various slope positions showed little difference.Meanwhile,all the indexes showed the phenomenon of semi-shady slope>sunny slope>shady slope under different slope directions.Among them,the effect of slope position on DBH was extremely significant,but the effect of slope direction on DBH was not significant,and slope position,slope direction and the interaction of slope direction and slope position had no significant effects on the tree height of the C.lanceolata plantation.In addition,slope direction and slope position had extremely significant effects on single plant wood volume.From the overall growth situation of the C.lanceolata plantation in Lingnan Forest Farm,the slope position factor had greater effects on various indexes of forest growth than the slope direction factor,mainly manifested in that the lower slope was better than the middle slope,and the middle slope position was better than the upper slope,while although slope direction had some effect on the growth of the C.lanceolata plantation,the influence degree was not as significant as that of slope position.[Conclusions]This study provides some reference for the adjustment and optimization,development and renewal of C.lanceolata plantation structure in the later period in this area,as well as some data support for other theoretical research on economic forests.
文摘The development of equations to predict tree height, crown diameter, crown depth from stem diameter of a tree species enables arborists, researchers, and urban forest managers to model costs and benefits, analyze alternative management scenarios, and determine the best management practices for sustainable forests. The objective of this study was to develop regression prediction models for tree age, tree height, crown diameter, crown ratio and crown depth for A. senegal growing in Ferlo, in the northern Senegal. Four plantations of different years old (ISRA, 10 years old plantations, Ndodj, 8 years old plantations, Boulal, 5 years old plantations and Déali, 4 years old plantations) were selected. The following dendometric variables: crown height, crown diameter, stem diameter at the breast height, stem basal diameter (at 0.30 m) and the height from the tree base to first branch were measured on a total of 489 trees. The results suggested that the ecological structure of the different year old A. Senegal plantation revealed a bell-shaped form with left dissymmetric distribution indicating a predominance of individuals with small diameter at breast height. Allometry study of A. Senegal showed highly significant positive correlations (p = 0.00) between stem diameter at breast height, stem basal diameter, tree height, crown diameter and crown depth. Positive correlations were also found between crown diameter, tree height and crown height. Prediction models derived from these relationships can be used to estimate the tree height, stem diameter at breast height and crown depth from crown diameter with greater precision. As for A. Senegal age estimation, the established model is not strong as it can explain only 49.1% of the age variation.
文摘The role of cocoa systems for climate change mitigation and adaptation has increased substantially because of their capability to trap carbon dioxide from the atmosphere and deposited in the cocoa trees as carbon. Development of aboveground biomass (AGB) models for cocoa plantations is crucial for accurate estimation of carbon stocks in the cocoa systems, however, allometric models for estimating AGB for cocoa plantations remain a challenge for cocoa producing countries in Sub-Saharan Africa especially Ghana. The aim of this study is to develop allometric model that can be used for the estimation of AGB for cocoa plantations in Ghana, as well as West Africa. Destructive sampling was carried out on 110 cocoa trees obtained from the cocoa rehabilitation exercise for the development of the allometric models. Diameter at breast height (D), total tree height (H) and wood density (ρ) were used as predictors to develop seven models. The best model was selected based on coefficient of determination (R<sup>2</sup>), index of agreement (I<sub>A</sub>), root mean squared error (RMSE), bias (E%), mean absolute error (MAE) and corrected akaike information criterion (AIC<sub>C</sub>) and percentage relative standard error (PRSE) of the estimated parameters. The selected model, which was the one with the predictors D and ρ, was given as;AGB = 0.7217ρ(D<sup>2</sup>)<sup>0.921</sup>. It was compared with the Yuliasmara et al. (2009) cocoa model using equivalence test and paired sample t-test. The two models were found to be equivalent within ±10% of their mean predictions (p < 0.0001) for one-tailed tests for both lower and upper limits, while the paired sample t-test rejected the null hypothesis with mean difference of 14.16 kg between the two models. This study is significant because it has provided a model to estimate AGB for the cocoa plantations in Ghana which is very important for the Ghana Cocoa-Forest REDD+ Programme and also can be used by other West African cocoa producing countries.
基金Federal Ministry of Education and Research (BMBF) of Germany,funded the PhD programme of the lead author through the West African Science Service Centre for Climate Change and Adapted Land use (WASCAL)。
文摘Background: Modelling aboveground biomass(AGB) in forest and woodland ecosystems is critical for accurate estimation of carbon stocks. However, scarcity of allometric models for predicting AGB remains an issue that has not been adequately addressed in Africa. In particular, locally developed models for estimating AGB in the tropical woodlands of Ghana have received little attention. In the absence of locally developed allometric models, Ghana will continue to use Tier 1 biomass data through the application of pantropic models. Without local allometric models it is not certain how Ghana would achieve Tier 2 and 3 levels under the United Nations programme for reducing emissions from deforestation and forest degradation. The objective of this study is to develop a mixedspecies allometric model for use in estimating AGB for the tropical woodlands in Ghana. Destructive sampling was carried out on 745 trees(as part of charcoal production) for the development of allometric equations. Diameter at breast height(dbh, i.e. 1.3 m above ground level), total tree height(H) and wood density(ρ) were used as predictors for the models. Seven models were compared and the best model selected based on model efficiency,bias(%) and corrected Akaike Information Criterion. The best model was validated by comparing its results with those of the pantropic model developed by Chave et al.(Glob Chang Biol 20:3177–3190, 2014) using equivalence test and conventional paired t-test.Results: The results revealed that the best model for estimating AGB in the tropical woodlands is AGB =0.0580ρ((dbh)2 H)0.999. The equivalence test showed that this model and the pantropic model developed by Chave et al.(Glob Chang Biol 20:3177–3190, 2014) were equivalent within ±10% of their mean predictions(p-values <0.0001 for one-tailed t-tests for both lower and upper bounds at 5% significant level), while the paired t-test revealed that the mean(181.44 ± 18.25 kg) of the model predictions of the best model of this study was significantly(n = 745, mean diff. = 16.50 ± 2.45 kg;S.E. = 1.25 kg;p < 0.001) greater than that(164.94 ± 15.82 kg) of the pantropic model of Chave et al.(Glob Chang Biol 20:3177–3190, 2014).Conclusion: The model developed in this study fills a critical gap in estimating AGB in tropical woodlands in Ghana and other West African countries with similar ecological conditions. Despite the equivalence with the pantropic model it remains superior to the model of Chave et al.(Glob Chang Biol 20:3177–3190, 2014) for the estimation of AGB in local tropical woodlands. It is a relevant tool for the attainment of Tier 2 and 3 levels for REDD+. The model is recommended for use in the tropical woodlands in Ghana and other West African countries in place of the use of pantropic models.
文摘【目的】以人工落叶松为例,探索基于无人机激光雷达(Unmanned aerial vehicle LiDAR,UAVLiDAR)点云的单木探测提取树高的误差对胸径反演的影响并校准,实现单木参数(胸径、树高)的准确度量,为大尺度高效便捷估测单木参数提供新的思路。【方法】以东北林业大学帽儿山实验林场13块4个龄组(幼龄林、中龄林、近熟林和成熟林)的落叶松人工林样地UAV-LiDAR数据及野外调查数据为数据源,基于UAVLiDAR点云的单木探测提取的树高,分别以普通最小二乘法(Ordinary least squares,OLS)和3种误差变量回归(标准主轴(Standard major axis,SMA)、远程主轴(Ranged major axis,RMA)和极大似然估计(Maximum likelihood estimate,MLE))构建胸径-树高模型,研究探测误差对各龄组人工落叶松胸径反演的影响并校准。【结果】利用UAV-LiDAR点云的单木探测提取4个龄组树高的相对均方根误差(rRMSE),误差范围为3.41%~5.14%;在胸径-树高模型预测方面,3种误差变量回归均优于OLS,RMA预测效果最好,4个龄组反演单木胸径的rRMSE降低了2.21%~3.58%。【结论】当满足模型假设时,误差变量回归比OLS在预测响应变量方面表现更好,是估计无偏的模型系数的理想方法,本研究中RMA方法表现最好;本研究所构建的人工落叶松胸径反演模型具有较高的预估精度,各项误差均保持在合理范围内,可实现应用UAV-LiDAR高效便捷地估测大尺度森林单木参数的目的,可在实践中推广。
