533 research outputs found
A new approach to "Forsteinrichtung": Combining enterprise level inventories and airborne LiDAR data to develop compartment wise managment plans
No full textA new approach to "Forsteinrichtung": Combining enterprise level inventories and airborne LiDAR data to develop compartment wise managment plans
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General considerations about the use of allometric equations for biomass estimation on the example of Norway spruce in central Europe
No full textAllometric relations for tree growth modelling have been subject to research for decades, partly as empirical models, and partly as process models such as the pipe model, hydraulic architecture, mechanical approaches or the fractal-like nature of plant architecture. Unlike empirical studies, process models aim at explaining the scaling within tree architecture as a function of biological, physical or mechanical factors and at modelling their effect on functionality and growth of different parts of an individual tree. The goal of the underlying study is to link theoretical explanation to empirical approaches of tree biomass estimation by the example of Norway spruce (Picea abies [L.] Karst.). Decisively, this article tries to take allometry out of the purely curve-fitting exercise common in literature and derives implications for the use of allometric biomass functions. Our results demonstrate that the dbh as independent variable might be misleading for the comparison of universal scaling laws with empirical studies. We were able to show, that the use of a recalculated diameter in relative stem height by means of a taper form model confirms general biological implications better than the dbh measured at a fixed tree height. We used a compiled dataset of altogether 245 trees that were measured on different sites in central Europe to proof our consideration. As one result we estimated a scaling factor b of 2.65 for the allometric relation (agb = aAllometric relations for tree growth modelling have been subject to research for decades, partly as empirical models, and partly as process models such as the pipe model, hydraulic architecture, mechanical approaches or the fractal-like nature of plant architecture. Unlike empirical studies, process models aim at explaining the scaling within tree architecture as a function of biological, physical or mechanical factors and at modelling their effect on functionality and growth of different parts of an individual tree. The goal of the underlying study is to link theoretical explanation to empirical approaches of tree biomass estimation by the example of Norway spruce (Picea abies [L.] Karst.). Decisively, this article tries to take allometry out of the purely curve-fitting exercise common in literature and derives implications for the use of allometric biomass functions. Our results demonstrate that the dbh as independent variable might be misleading for the comparison of universal scaling laws with empirical studies. We were able to show, that the use of a recalculated diameter in relative stem height by means of a taper form model confirms general biological implications better than the dbh measured at a fixed tree height. We used a compiled dataset of altogether 245 trees that were measured on different sites in central Europe to proof our consideration. As one result we estimated a scaling factor b of 2.65 for the allometric relation (agb = aAllometric relations for tree growth modelling have been subject to research for decades, partly as empirical models, and partly as process models such as the pipe model, hydraulic architecture, mechanical approaches or the fractal-like nature of plant architecture. Unlike empirical studies, process models aim at explaining the scaling within tree architecture as a function of biological, physical or mechanical factors and at modelling their effect on functionality and growth of different parts of an individual tree. The goal of the underlying study is to link theoretical explanation to empirical approaches of tree biomass estimation by the example of Norway spruce (Picea abies [L.] Karst.). Decisively, this article tries to take allometry out of the purely curve-fitting exercise common in literature and derives implications for the use of allometric biomass functions. Our results demonstrate that the dbh as independent variable might be misleading for the comparison of universal scaling laws with empirical studies. We were able to show, that the use of a recalculated diameter in relative stem height by means of a taper form model confirms general biological implications better than the dbh measured at a fixed tree height. We used a compiled dataset of altogether 245 trees that were measured on different sites in central Europe to proof our consideration. As one result we estimated a scaling factor b of 2.65 for the allometric relation (agb = aAllometric relations for tree growth modelling have been subject to research for decades, partly as empirical models, and partly as process models such as the pipe model, hydraulic architecture, mechanical approaches or the fractal-like nature of plant architecture. Unlike empirical studies, process models aim at explaining the scaling within tree architecture as a function of biological, physical or mechanical factors and at modelling their effect on functionality and growth of different parts of an individual tree. The goal of the underlying study is to link theoretical explanation to empirical approaches of tree biomass estimation by the example of Norway spruce (Picea abies [L.] Karst.). Decisively, this article tries to take allometry out of the purely curve-fitting exercise common in literature and derives implications for the use of allometric biomass functions. Our results demonstrate that the dbh as independent variable might be misleading for the comparison of universal scaling laws with empirical studies. We were able to show, that the use of a recalculated diameter in relative stem height by means of a taper form model confirms general biological implications better than the dbh measured at a fixed tree height. We used a compiled dataset of altogether 245 trees that were measured on different sites in central Europe to proof our consideration. As one result we estimated a scaling factor b of 2.65 for the allometric relation (agb = aD) between a diameter in relative stem height (D0.1) and aboveground biomass (agb), which is close to scaling relations predicted by process models. The standard error of a linear regression model based on the log-transformed variables could be slightly reduced to 0.21 (R2 = 0.98) when we used the diameter in relative tree height.) between a diameter in relative stem height (D0.1) and aboveground biomass (agb), which is close to scaling relations predicted by process models. The standard error of a linear regression model based on the log-transformed variables could be slightly reduced to 0.21 (R2 = 0.98) when we used the diameter in relative tree height.) between a diameter in relative stem height (D0.1) and aboveground biomass (agb), which is close to scaling relations predicted by process models. The standard error of a linear regression model based on the log-transformed variables could be slightly reduced to 0.21 (R2 = 0.98) when we used the diameter in relative tree height.) between a diameter in relative stem height (D0.1) and aboveground biomass (agb), which is close to scaling relations predicted by process models. The standard error of a linear regression model based on the log-transformed variables could be slightly reduced to 0.21 (R2 = 0.98) when we used the diameter in relative tree height
Comparison of linear and mixed-effect regression models and a k-nearest neighbour approach for estimation of single-tree biomass
No full textAllometric biomass models for individual trees are typically specific to site conditions and species. They are often based on a low number of easily measured independent variables, such as diameter in breast height and tree height. A prevalence of small data sets and few study sites limit their application domain. One challenge in the context of the actual climate change discussion is to find more general approaches for reliable biomass estimation. Therefore, nonparametric approaches can be seen as an alternative to commonly used regression models. In this pilot study, we compare a nonparametric instance-based k-nearest neighbour (k-NN) approach to estimate single-tree biomass with predictions from linear mixed-effect regression models and subsidiary linear models using data sets of Norway spruce (Picea abies (L.) Karst.) and Scots pine (Pinus sylvestris L.) from the National Forest Inventory of Finland. For all trees, the predictor variables diameter at breast height and tree height are known. The data sets were split randomly into a modelling and a test subset for each species. The test subsets were not considered for the estimation of regression coefficients nor as training data for the k-NN imputation. The relative root mean square errors of linear mixed models and k-NN estimations are slightly lower than those of an ordinary least squares regression model. Relative prediction errors of the k-NN approach are 16.4% for spruce and 14.5% for pine. Errors of the linear mixed models are 17.4% for spruce and 15.0% for pine. Our results show that nonparametric methods are suitable in the context of single-tree biomass estimation
The potential of terrestrial laser scanning for the estimation of understory biomass in coppice-with-standard systems
No full textMethods for estimating the biomass potential of dense coppice in coppice-with-standard forests in a fast and objective way are currently rare. We adapted existing methodical approaches for biomass estimations from terrestrial laser scanning developed for mature stands in order to perform single scan measurements of diameter at breast height in extremely dense coppice with a stem density of 30,000 ha−1. Diameter was then used as input for allometric regression models for estimations of the dry weights. As a tribute to the dense stocking on the investigated stands study plots were smaller than in previous studies focusing on mature forests. Results were found to be sound with a mean absolute error of about 6.9 kg which is equal to a relative error of 11.1%. With respect to the strongly reduced amount of field work the method is therefore of high efficiency. With the new approach reliable assessments of the bioenergy potentials become possible for coppice stands, which might play an important role in future tasks of mitigating climate change
Projektantrag im Rahmen des Fortsetzungsantrags der DFG-Forschergruppe 742 “Grammatik und Verarbeitung verbaler Argumente”
No full textLandschaftspflegematerial im Land Niedersachsen: Potentiale für die energetische Nutzung
No full textPotentialanalyse zur Erfassung holziger Biomasse in Niedersachsen mittels Fernerkundungsmethodik
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