Site index(SI)is determined from the top height development and is a proxy for forest productivity,defined as the expected top height for a given species at a certain index age.In Norway,an index age of 40 years is us...Site index(SI)is determined from the top height development and is a proxy for forest productivity,defined as the expected top height for a given species at a certain index age.In Norway,an index age of 40 years is used.By using bi-temporal airborne laser scanning(ALS)data,SI can be determined using models estimated from SI observed on field plots(the direct approach)or from predicted top heights at two points in time(the height differential approach).Time series of ALS data may enhance SI determination compared to conventional methods used in operational forest inventory by providing more detailed information about the top height development.We used longitudinal data comprising spatially consistent field and ALS data collected from training plots in 1999,2010,and 2022 to determine SI using the direct and height differential approaches using all combinations of years and performed an external validation.We also evaluated the use of data assimilation.Values of root mean square error obtained from external validation were in the ranges of 16.3%–21.4%and 12.8%–20.6%of the mean fieldregistered SI for the direct approach and the height differential approach,respectively.There were no statistically significant effects of time series length or the number of points in time on the obtained accuracies.Data assimilation did not result in any substantial improvement in the obtained accuracies.Although a time series of ALS data did not yield greater accuracies compared to using only two points in time,a larger proportion of the study area could be used in ALS-based determination of SI when a time series was available.This was because areas that were unsuitable for SI determination between two points in time could be subject to SI determination based on data from another part of the time series.展开更多
Background： Forests are a key component of the global carbon cycle, and research is needed into the effects of human-driven and natural processes on their carbon pools. Airborne laser scanning （ALS） produces detail...Background： Forests are a key component of the global carbon cycle, and research is needed into the effects of human-driven and natural processes on their carbon pools. Airborne laser scanning （ALS） produces detailed 3D maps of forest canopy structure from which aboveground carbon density can be estimated. Working with a ALS dataset collected over the 8049-km2 Wellington Region of New Zealand we create maps of indigenous forest carbon and evaluate the influence of wind by examining how carbon storage varies with aspect. Storms flowing from the west are a common cause of disturbance in this region, and we hypothesised that west-facing forests exposed to these winds would be shorter than those in sheltered east-facing sites. Methods： The aboveground carbon density of 31 forest inventory plots located within the ALS survey region were used to develop estimation models relating carbon density to ALS information. Power-law models using rasters of top-of-the-canopy height were compared with models using tree-level information extracted from the ALS dataset. A forest carbon map with spatial resolution of 25 m was generated from ALS maps of forest height and the estimation models. The map was used to evaluate the influences of wind on forests. Results： Power-law models were slightly less accurate than tree-centric models （RMSE 35% vs 32%） but were selected for map generation for computational efficiency. The carbon map comprised 4.5 million natural forest pixels within which canopy height had been measured by ALS, providing an unprecedented dataset with which to examine drivers of carbon density. Forests facing in the direction of westerly storms stored less carbon, as hypothesised. They had much greater above-ground carbon density for a given height than any of 14 tropical forests previously analysed by the same approach, and had exceptionally high basal areas for their height. We speculate that strong winds have kept forests short without impeding basal area growth. Conclusion： Simple estimation models based on top-of-the canopy height are almost as accurate as state-of-the-art tree-centric approaches, which require more computing power. High-resolution carbon maps produced by ALS provide powerful datasets for evaluating the environmental drivers of forest structure, such as wind.展开更多
Background: The distribution of forest vegetation within urban environments is critically important as it influences urban environmental conditions and the energy exchange through the absorption of solar radiation and...Background: The distribution of forest vegetation within urban environments is critically important as it influences urban environmental conditions and the energy exchange through the absorption of solar radiation and modulation of evapotranspiration. It also plays an important role filtering urban water systems and reducing storm water runoff.Methods: We investigate the capacity of ALS data to individually detect, map and characterize large(taller than15 m) trees within the City of Vancouver. Large trees are critical for the function and character of Vancouver’s urban forest. We used an object-based approach for individual tree detection and segmentation to determine tree locations(position of the stem), to delineate the shape of the crowns and to categorize the latter either as coniferous or deciduous.Results: Results indicate a detection rate of 76.6% for trees > 15 m with a positioning error of 2.11 m(stem location). Extracted tree heights possessed a RMSE of 2.60 m and a bias of-1.87 m, whereas crown diameter was derived with a RMSE of 3.85 m and a bias of-2.06 m. Missed trees are principally a result of undetected treetops occurring in dense, overlapping canopies with more accurate detection and delineation of trees in open areas.Conclusion: By identifying key structural trees across Vancouver’s urban forests, we can better understand their role in providing ecosystem goods and services for city residents.展开更多
Airborne laser scanning(ALS)has been widely applied to estimate tree and forest attributes,but it can also drive the segmentation of forest areas.Clustering algorithms are the dominant technique in segmentation but sp...Airborne laser scanning(ALS)has been widely applied to estimate tree and forest attributes,but it can also drive the segmentation of forest areas.Clustering algorithms are the dominant technique in segmentation but spatial optimization using exact methods remains untested.This study presents a novel approach to segmentation based on mixed integer programming to create forest management units(FMUs).This investigation focuses on using raster information derived from ALS surveys.Two mainstream clustering algorithms were compared to the new MIP formula that simultaneously accounts for area and adjacency restrictions,FMUs size and homogeneity in terms of vegetation height.The optimal problem solution was found when using less than 150 cells,showing the problem formulation is solvable.The results for MIP were better than for the clustering algorithms;FMUs were more compact based on the intravariation of canopy height and the variability in size was lower.The MIP model allows the user to strictly control the size of FMUs,which is not possible in heuristic optimization and in the clustering algorithms tested.The definition of forest management units based on remote sensing data is an important operation and our study pioneers the use of MIP ALS-based optimal segmentation.展开更多
Background: Forest inventories have always been a primary information source concerning the forest ecosystem state. Various applied survey approaches arise from the numerous important factors during sampling scheme pl...Background: Forest inventories have always been a primary information source concerning the forest ecosystem state. Various applied survey approaches arise from the numerous important factors during sampling scheme planning. Paramount aspects include the survey goal and scale, target population inherent variation and patterns,and available resources. The last factor commonly inhibits the goal, and compromises have to be made. Airborne laser scanning(ALS) has been intensively tested as a cost-effective option for forest inventories. Despite existing foundations, research has provided disparate results. Environmental conditions are one of the factors greatly influencing inventory performance. Therefore, a need for site-related sampling optimization is well founded.Moreover, as stands are the basic operational unit of managed forest holdings, few related studies have presented stand-level results. As such, herein, we tested the sampling intensity influence on the performance of the ALSenhanced stand-level inventory.Results: Distributions of possible errors were plotted by comparing ALS model estimates, with reference values derived from field surveys of 3300 sample plots and more than 300 control stands located in 5 forest districts. No improvement in results was observed due to the scanning density. The variance in obtained errors stabilized in the interval of 200–300 sample plots, maintaining the bias within +/-5% and the precision above 80%. The sample plot area affected scores mostly when transitioning from 100 to 200 m2. Only a slight gain was observed when bigger plots were used.Conclusions: ALS-enhanced inventories effectively address the demand for comprehensive and detailed information on the structure of single stands over vast areas. Knowledge of the relation between the sampling intensity and accuracy of ALS estimates allows the determination of certain sampling intensity thresholds. This should be useful when matching the required sample size and accuracy with available resources. Site optimization may be necessary, as certain errors may occur due to the sampling scheme, estimator type or forest site, making these factors worth further consideration.展开更多
Identifying tree locations is a basic step in the derivation of other tree parameters using remote sensing techniques, particularly when using airborne laser scanning. There are several techniques for identifying tree...Identifying tree locations is a basic step in the derivation of other tree parameters using remote sensing techniques, particularly when using airborne laser scanning. There are several techniques for identifying tree positions. In this paper, we present a raster-based method for determining tree position and delineating crown coverage. We collected data from nine research plots that supported different mixes of species. We applied a raster-based method to raster layers with six different spatial resolutions and used terrestrial measurement data as reference data. Tree identification at a spatial resolution of 1.5 m was demonstrated to be the most accurate, with an average identification ratio (IR) of 95% and average detection ratio of 68% being observed. At a higher spatial resolution of 0.5 m, IR was overestimated by more than 600%. At a lower spatial resolution of 3 m, IR was underestimated at less than 44% of terrestrial measurements. The inventory process was timed to enable evaluation of the time efficiency of automatic methods.展开更多
Sustainable forest management heavily relies on the accurate estimation of tree parameters.Among others,the diameter at breast height(DBH) is important for extracting the volume and mass of an individual tree.For syst...Sustainable forest management heavily relies on the accurate estimation of tree parameters.Among others,the diameter at breast height(DBH) is important for extracting the volume and mass of an individual tree.For systematically estimating the volume of entire plots,airborne laser scanning(ALS) data are used.The estimation model is frequently calibrated using manual DBH measurements or static terrestrial laser scans(STLS) of sample plots.Although reliable,this method is time-consuming,which greatly hampers its use.Here,a handheld mobile terrestrial laser scanning(HMTLS) was demonstrated to be a useful alternative technique to precisely and efficiently calculate DBH.Different data acquisition techniques were applied at a sample plot,then the resulting parameters were comparatively analysed.The calculated DBH values were comparable to the manual measurements for HMTLS,STLS,and ALS data sets.Given the comparability of the extracted parameters,with a reduced point density of HTMLS compared to STLS data,and the reasonable increase of performance,with a reduction of acquisition time with a factor of5 compared to conventional STLS techniques and a factor of3 compared to manual measurements,HMTLS is considered a useful alternative technique.展开更多
Determining forest structural complexity,i.e.,a measure of the number of different attributes of a forest and the relative abundance of each attribute,is important for forest management and conservation.In this study,...Determining forest structural complexity,i.e.,a measure of the number of different attributes of a forest and the relative abundance of each attribute,is important for forest management and conservation.In this study,we examined the structural complexity of mixed conifer–broadleaf forests by integrating multiple forest structural attributes derived from airborne Li DAR data and aerial photography.We sampled 76 plots from an unmanaged mixed conifer–broadleaf forest reserve in northern Japan.Plot-level metrics were computed for all plots using both field and remote sensing data to assess their ability to capture the vertical and horizontal variations of forest structure.A multivariate set of forest structural attributes that included three Li DAR metrics(95 th percentile canopy height,canopy density and surface area ratio) and one image metric(proportion of broadleaf cover),was used to classify forest structure into structural complexity classes.Our results revealed significant correlation between field and remote sensing metrics,indicating that these two sets of measurements captured similar patterns of structure in mixed conifer–broadleaf forests.Further,cluster analysis identified six forest structural complexity classes includingtwo low-complexity classes and four high-complexity classes that were distributed in different elevation ranges.In this study,we could reliably analyze the structural complexity of mixed conifer–broadleaf forests using a simple and easy to calculate set of forest structural attributes derived from airborne Li DAR data and high-resolution aerial photography.This study provides a good example of the use of airborne Li DAR data sets for wider purposes in forest ecology as well as in forest management.展开更多
Airborne laser scanning(ALS)and terrestrial laser scanning(TLS)has attracted attention due to their forest parameter investigation and research applications.ALS is limited to obtaining fi ne structure information belo...Airborne laser scanning(ALS)and terrestrial laser scanning(TLS)has attracted attention due to their forest parameter investigation and research applications.ALS is limited to obtaining fi ne structure information below the forest canopy due to the occlusion of trees in natural forests.In contrast,TLS is unable to gather fi ne structure information about the upper canopy.To address the problem of incomplete acquisition of natural forest point cloud data by ALS and TLS on a single platform,this study proposes data registration without control points.The ALS and TLS original data were cropped according to sample plot size,and the ALS point cloud data was converted into relative coordinates with the center of the cropped data as the origin.The same feature point pairs of the ALS and TLS point cloud data were then selected to register the point cloud data.The initial registered point cloud data was fi nely and optimally registered via the iterative closest point(ICP)algorithm.The results show that the proposed method achieved highprecision registration of ALS and TLS point cloud data from two natural forest plots of Pinus yunnanensis Franch.and Picea asperata Mast.which included diff erent species and environments.An average registration accuracy of 0.06 m and 0.09 m were obtained for P.yunnanensis and P.asperata,respectively.展开更多
Background:Modern remote sensing methods enable the prediction of tree-level forest resource data.However,the benefits of using tree-level data in forest or harvest planning is not clear given a relative paucity of re...Background:Modern remote sensing methods enable the prediction of tree-level forest resource data.However,the benefits of using tree-level data in forest or harvest planning is not clear given a relative paucity of research.In particular,there is a need for tree-level methods that simultaneously account for the spatial distribution of trees and other objectives.In this study,we developed a spatial tree selection method that considers tree-level(relative value increment),neighborhood related(proximity of cut trees)and global objectives(total harvest).Methods:We partitioned the whole surface area of the stand to trees,with the assumption that a large tree occupies a larger area than a small tree.This was implemented using a power diagram.We also utilized spatially explicit tree-level growth models that accounted for competition by neighboring trees.Optimization was conducted with a variant of cellular automata.The proposed method was tested in stone pine(Pinus pinea L.)stands in Spain where we implemented basic individual tree detection with airborne laser scanning data.Results:We showed how to mimic four different spatial distributions of cut trees using alternative weightings of objective variables.The Non-spatial selection did not aim at a particular spatial layout,the Single-tree selection dispersed the trees to be cut,and the Tree group and Clearcut selections clustered harvested trees at different magnitudes.Conclusions:The proposed method can be used to control the spatial layout of trees while extracting trees that are the most economically mature.展开更多
Background： An examination of the distribution of ancient charcoal kiln sites in the forest landscape seems to be worthwhile, since general trends in the selection of suitable kiln site locations in the past might be...Background： An examination of the distribution of ancient charcoal kiln sites in the forest landscape seems to be worthwhile, since general trends in the selection of suitable kiln site locations in the past might become obvious. In this way forest landscape elements with a more intense usage by charcoal burning can be identified. By doing this, we can expect to gain information on the former condition and tree species composition of woodland. Investigations on the spatial distribution of charcoal kiln sites in relation to landscape attributes are sparse, however, probably due to the high on-site mapping effort. The outstanding suitability of LiDAR-derived digital terrain models （DTMs） for the detection of charcoal kiln sites has been recently proved. Hence, DTM-based surveys of charcoal kiln sites represent a promising attempt to fill this research gap. Methods： Based on DTM-based surveys, we analyzed the spatial distribution of charcoal kiln sites in two forest landscapes in the German federal state of Hesse： Reinhardswald and Kellerwald-Edersee National Park. In doing so, we considered the landscape attibutes ＂tree species composition＂, ＂water supply status＂, ＂nutrient supply status＂, ＂soil complex classes＂, ＂altitude＂, ＂exposition＂, and ＂inclination＂. Results： We found that charcoal kiln sites were established preferably on hillside locations that provided optimal growing and regeneration conditions for European beech （Fagus sylvatico） due to their acidic brown soils and sufficient water supply. These results are in line with instructions for the selection of appropriate kiln site locations, found in literature from the 18th to the 19th century. Conclusions： We conclude that there were well-stocked, beech-dominated deciduous forest stands in northern Hesse before 1800, particularly at poorly accessible hillside locations. These large stocks of beech wood were utilized by the governments of the different Hessian territories through the establishment of ironworks and hammer mills. Our argumentation is well in line with findings which underline that not all Hessian forests were overexploited in the 18th century. Frequently repeated complaints about ＂wood shortage＂ seemed to be more a political instrument than reality, not only in Hesse, but all over Europe. Consequently, a differentiated assessment of woodland conditions in proto-industrial times is strictly advised, even if contemporary sources draw a dark picture of the historic situation.展开更多
基金part of the Centre for Research-based Innovation SmartForest:Bringing Industry 4.0 to the Norwegian forest sector(NFR SFI project no.309671,smartforest.no)。
文摘Site index(SI)is determined from the top height development and is a proxy for forest productivity,defined as the expected top height for a given species at a certain index age.In Norway,an index age of 40 years is used.By using bi-temporal airborne laser scanning(ALS)data,SI can be determined using models estimated from SI observed on field plots(the direct approach)or from predicted top heights at two points in time(the height differential approach).Time series of ALS data may enhance SI determination compared to conventional methods used in operational forest inventory by providing more detailed information about the top height development.We used longitudinal data comprising spatially consistent field and ALS data collected from training plots in 1999,2010,and 2022 to determine SI using the direct and height differential approaches using all combinations of years and performed an external validation.We also evaluated the use of data assimilation.Values of root mean square error obtained from external validation were in the ranges of 16.3%–21.4%and 12.8%–20.6%of the mean fieldregistered SI for the direct approach and the height differential approach,respectively.There were no statistically significant effects of time series length or the number of points in time on the obtained accuracies.Data assimilation did not result in any substantial improvement in the obtained accuracies.Although a time series of ALS data did not yield greater accuracies compared to using only two points in time,a larger proportion of the study area could be used in ALS-based determination of SI when a time series was available.This was because areas that were unsuitable for SI determination between two points in time could be subject to SI determination based on data from another part of the time series.
基金supported by Ministry of Business, Innovation and Employment core funding to Crown Research Institutes
文摘Background： Forests are a key component of the global carbon cycle, and research is needed into the effects of human-driven and natural processes on their carbon pools. Airborne laser scanning （ALS） produces detailed 3D maps of forest canopy structure from which aboveground carbon density can be estimated. Working with a ALS dataset collected over the 8049-km2 Wellington Region of New Zealand we create maps of indigenous forest carbon and evaluate the influence of wind by examining how carbon storage varies with aspect. Storms flowing from the west are a common cause of disturbance in this region, and we hypothesised that west-facing forests exposed to these winds would be shorter than those in sheltered east-facing sites. Methods： The aboveground carbon density of 31 forest inventory plots located within the ALS survey region were used to develop estimation models relating carbon density to ALS information. Power-law models using rasters of top-of-the-canopy height were compared with models using tree-level information extracted from the ALS dataset. A forest carbon map with spatial resolution of 25 m was generated from ALS maps of forest height and the estimation models. The map was used to evaluate the influences of wind on forests. Results： Power-law models were slightly less accurate than tree-centric models （RMSE 35% vs 32%） but were selected for map generation for computational efficiency. The carbon map comprised 4.5 million natural forest pixels within which canopy height had been measured by ALS, providing an unprecedented dataset with which to examine drivers of carbon density. Forests facing in the direction of westerly storms stored less carbon, as hypothesised. They had much greater above-ground carbon density for a given height than any of 14 tropical forests previously analysed by the same approach, and had exceptionally high basal areas for their height. We speculate that strong winds have kept forests short without impeding basal area growth. Conclusion： Simple estimation models based on top-of-the canopy height are almost as accurate as state-of-the-art tree-centric approaches, which require more computing power. High-resolution carbon maps produced by ALS provide powerful datasets for evaluating the environmental drivers of forest structure, such as wind.
文摘Background: The distribution of forest vegetation within urban environments is critically important as it influences urban environmental conditions and the energy exchange through the absorption of solar radiation and modulation of evapotranspiration. It also plays an important role filtering urban water systems and reducing storm water runoff.Methods: We investigate the capacity of ALS data to individually detect, map and characterize large(taller than15 m) trees within the City of Vancouver. Large trees are critical for the function and character of Vancouver’s urban forest. We used an object-based approach for individual tree detection and segmentation to determine tree locations(position of the stem), to delineate the shape of the crowns and to categorize the latter either as coniferous or deciduous.Results: Results indicate a detection rate of 76.6% for trees > 15 m with a positioning error of 2.11 m(stem location). Extracted tree heights possessed a RMSE of 2.60 m and a bias of-1.87 m, whereas crown diameter was derived with a RMSE of 3.85 m and a bias of-2.06 m. Missed trees are principally a result of undetected treetops occurring in dense, overlapping canopies with more accurate detection and delineation of trees in open areas.Conclusion: By identifying key structural trees across Vancouver’s urban forests, we can better understand their role in providing ecosystem goods and services for city residents.
基金supported by MODFIRE project—A multiple criteria approach to integrate wildfire behavior in forest management planning(PCIF/MOS/0217/2017)benefited from the research exchange platform provided by the Su Fo Run project(Marie SklodowskaCurie Grant Agreement No.691149)。
文摘Airborne laser scanning(ALS)has been widely applied to estimate tree and forest attributes,but it can also drive the segmentation of forest areas.Clustering algorithms are the dominant technique in segmentation but spatial optimization using exact methods remains untested.This study presents a novel approach to segmentation based on mixed integer programming to create forest management units(FMUs).This investigation focuses on using raster information derived from ALS surveys.Two mainstream clustering algorithms were compared to the new MIP formula that simultaneously accounts for area and adjacency restrictions,FMUs size and homogeneity in terms of vegetation height.The optimal problem solution was found when using less than 150 cells,showing the problem formulation is solvable.The results for MIP were better than for the clustering algorithms;FMUs were more compact based on the intravariation of canopy height and the variability in size was lower.The MIP model allows the user to strictly control the size of FMUs,which is not possible in heuristic optimization and in the clustering algorithms tested.The definition of forest management units based on remote sensing data is an important operation and our study pioneers the use of MIP ALS-based optimal segmentation.
基金the research project entitled“Remote sensing-based assessment of woody biomass and carbon storage in forests”,which was financially supported by the National Centre for Research and Development(Poland),under the BIOSTRATEG programme(Agreement No.BIOSTRATEG1/267755/4/NCBR/2015)Financial support was also received from the project entitled“Rozbudowa metody inwentaryzacji urządzeniowej stanu lasu z wykorzystaniem efektów projektu REMBIOFOR”(Project No.500463,agreement No.EO.271.3.12.2019 with the Polish State Forests National Forest Holding,signed on 14.10.2019),which constitutes a continuation of the former project.
文摘Background: Forest inventories have always been a primary information source concerning the forest ecosystem state. Various applied survey approaches arise from the numerous important factors during sampling scheme planning. Paramount aspects include the survey goal and scale, target population inherent variation and patterns,and available resources. The last factor commonly inhibits the goal, and compromises have to be made. Airborne laser scanning(ALS) has been intensively tested as a cost-effective option for forest inventories. Despite existing foundations, research has provided disparate results. Environmental conditions are one of the factors greatly influencing inventory performance. Therefore, a need for site-related sampling optimization is well founded.Moreover, as stands are the basic operational unit of managed forest holdings, few related studies have presented stand-level results. As such, herein, we tested the sampling intensity influence on the performance of the ALSenhanced stand-level inventory.Results: Distributions of possible errors were plotted by comparing ALS model estimates, with reference values derived from field surveys of 3300 sample plots and more than 300 control stands located in 5 forest districts. No improvement in results was observed due to the scanning density. The variance in obtained errors stabilized in the interval of 200–300 sample plots, maintaining the bias within +/-5% and the precision above 80%. The sample plot area affected scores mostly when transitioning from 100 to 200 m2. Only a slight gain was observed when bigger plots were used.Conclusions: ALS-enhanced inventories effectively address the demand for comprehensive and detailed information on the structure of single stands over vast areas. Knowledge of the relation between the sampling intensity and accuracy of ALS estimates allows the determination of certain sampling intensity thresholds. This should be useful when matching the required sample size and accuracy with available resources. Site optimization may be necessary, as certain errors may occur due to the sampling scheme, estimator type or forest site, making these factors worth further consideration.
基金supported by the Scientific Grant Agency of the Ministry of Education,Science,Research and Sport of the Slovak Republicthe Slovak Academy of Sciences under Project No.1/0953/13:‘‘Geographic information on forest and forest landscape:creation and utilization of particularity’’
文摘Identifying tree locations is a basic step in the derivation of other tree parameters using remote sensing techniques, particularly when using airborne laser scanning. There are several techniques for identifying tree positions. In this paper, we present a raster-based method for determining tree position and delineating crown coverage. We collected data from nine research plots that supported different mixes of species. We applied a raster-based method to raster layers with six different spatial resolutions and used terrestrial measurement data as reference data. Tree identification at a spatial resolution of 1.5 m was demonstrated to be the most accurate, with an average identification ratio (IR) of 95% and average detection ratio of 68% being observed. At a higher spatial resolution of 0.5 m, IR was overestimated by more than 600%. At a lower spatial resolution of 3 m, IR was underestimated at less than 44% of terrestrial measurements. The inventory process was timed to enable evaluation of the time efficiency of automatic methods.
基金funded by University College GhentGhent University。
文摘Sustainable forest management heavily relies on the accurate estimation of tree parameters.Among others,the diameter at breast height(DBH) is important for extracting the volume and mass of an individual tree.For systematically estimating the volume of entire plots,airborne laser scanning(ALS) data are used.The estimation model is frequently calibrated using manual DBH measurements or static terrestrial laser scans(STLS) of sample plots.Although reliable,this method is time-consuming,which greatly hampers its use.Here,a handheld mobile terrestrial laser scanning(HMTLS) was demonstrated to be a useful alternative technique to precisely and efficiently calculate DBH.Different data acquisition techniques were applied at a sample plot,then the resulting parameters were comparatively analysed.The calculated DBH values were comparable to the manual measurements for HMTLS,STLS,and ALS data sets.Given the comparability of the extracted parameters,with a reduced point density of HTMLS compared to STLS data,and the reasonable increase of performance,with a reduction of acquisition time with a factor of5 compared to conventional STLS techniques and a factor of3 compared to manual measurements,HMTLS is considered a useful alternative technique.
文摘Determining forest structural complexity,i.e.,a measure of the number of different attributes of a forest and the relative abundance of each attribute,is important for forest management and conservation.In this study,we examined the structural complexity of mixed conifer–broadleaf forests by integrating multiple forest structural attributes derived from airborne Li DAR data and aerial photography.We sampled 76 plots from an unmanaged mixed conifer–broadleaf forest reserve in northern Japan.Plot-level metrics were computed for all plots using both field and remote sensing data to assess their ability to capture the vertical and horizontal variations of forest structure.A multivariate set of forest structural attributes that included three Li DAR metrics(95 th percentile canopy height,canopy density and surface area ratio) and one image metric(proportion of broadleaf cover),was used to classify forest structure into structural complexity classes.Our results revealed significant correlation between field and remote sensing metrics,indicating that these two sets of measurements captured similar patterns of structure in mixed conifer–broadleaf forests.Further,cluster analysis identified six forest structural complexity classes includingtwo low-complexity classes and four high-complexity classes that were distributed in different elevation ranges.In this study,we could reliably analyze the structural complexity of mixed conifer–broadleaf forests using a simple and easy to calculate set of forest structural attributes derived from airborne Li DAR data and high-resolution aerial photography.This study provides a good example of the use of airborne Li DAR data sets for wider purposes in forest ecology as well as in forest management.
基金supported by the National Natural Science Foundation of China,Grant Number 41961060by the Program for Innovative Research Team (in Science and Technology) in the University of Yunnan Province,Grant Number IRTSTYN+1 种基金by the Scientific Research Fund Project of the Education Department of Yunnan Province,Grant Numbers 2020J0256 and 2021J0438by the Postgraduate Scientific Research and Innovation Fund Project of Yunnan Normal University,Grant Number YJSJJ21-A08
文摘Airborne laser scanning(ALS)and terrestrial laser scanning(TLS)has attracted attention due to their forest parameter investigation and research applications.ALS is limited to obtaining fi ne structure information below the forest canopy due to the occlusion of trees in natural forests.In contrast,TLS is unable to gather fi ne structure information about the upper canopy.To address the problem of incomplete acquisition of natural forest point cloud data by ALS and TLS on a single platform,this study proposes data registration without control points.The ALS and TLS original data were cropped according to sample plot size,and the ALS point cloud data was converted into relative coordinates with the center of the cropped data as the origin.The same feature point pairs of the ALS and TLS point cloud data were then selected to register the point cloud data.The initial registered point cloud data was fi nely and optimally registered via the iterative closest point(ICP)algorithm.The results show that the proposed method achieved highprecision registration of ALS and TLS point cloud data from two natural forest plots of Pinus yunnanensis Franch.and Picea asperata Mast.which included diff erent species and environments.An average registration accuracy of 0.06 m and 0.09 m were obtained for P.yunnanensis and P.asperata,respectively.
基金supported by the University of Eastern Finland Strategic Funding,School of Forest Sciences and the Strategic Research Council of the Academy of Finland for the FORBIO project(Decision Number 314224)partially funded by Portuguese National Funds through FCT-Fundacao para a Ciencia e a Tecnologia,I.P.in the scope of Norma Transitoria-DL57/2016/CP5151903067/CT4151900586the project MODFIRE-A multiple criteria approach to integrate wildfire behavior in forest management planning with the reference PCIF/MOS/0217/2017。
文摘Background:Modern remote sensing methods enable the prediction of tree-level forest resource data.However,the benefits of using tree-level data in forest or harvest planning is not clear given a relative paucity of research.In particular,there is a need for tree-level methods that simultaneously account for the spatial distribution of trees and other objectives.In this study,we developed a spatial tree selection method that considers tree-level(relative value increment),neighborhood related(proximity of cut trees)and global objectives(total harvest).Methods:We partitioned the whole surface area of the stand to trees,with the assumption that a large tree occupies a larger area than a small tree.This was implemented using a power diagram.We also utilized spatially explicit tree-level growth models that accounted for competition by neighboring trees.Optimization was conducted with a variant of cellular automata.The proposed method was tested in stone pine(Pinus pinea L.)stands in Spain where we implemented basic individual tree detection with airborne laser scanning data.Results:We showed how to mimic four different spatial distributions of cut trees using alternative weightings of objective variables.The Non-spatial selection did not aim at a particular spatial layout,the Single-tree selection dispersed the trees to be cut,and the Tree group and Clearcut selections clustered harvested trees at different magnitudes.Conclusions:The proposed method can be used to control the spatial layout of trees while extracting trees that are the most economically mature.
文摘Background： An examination of the distribution of ancient charcoal kiln sites in the forest landscape seems to be worthwhile, since general trends in the selection of suitable kiln site locations in the past might become obvious. In this way forest landscape elements with a more intense usage by charcoal burning can be identified. By doing this, we can expect to gain information on the former condition and tree species composition of woodland. Investigations on the spatial distribution of charcoal kiln sites in relation to landscape attributes are sparse, however, probably due to the high on-site mapping effort. The outstanding suitability of LiDAR-derived digital terrain models （DTMs） for the detection of charcoal kiln sites has been recently proved. Hence, DTM-based surveys of charcoal kiln sites represent a promising attempt to fill this research gap. Methods： Based on DTM-based surveys, we analyzed the spatial distribution of charcoal kiln sites in two forest landscapes in the German federal state of Hesse： Reinhardswald and Kellerwald-Edersee National Park. In doing so, we considered the landscape attibutes ＂tree species composition＂, ＂water supply status＂, ＂nutrient supply status＂, ＂soil complex classes＂, ＂altitude＂, ＂exposition＂, and ＂inclination＂. Results： We found that charcoal kiln sites were established preferably on hillside locations that provided optimal growing and regeneration conditions for European beech （Fagus sylvatico） due to their acidic brown soils and sufficient water supply. These results are in line with instructions for the selection of appropriate kiln site locations, found in literature from the 18th to the 19th century. Conclusions： We conclude that there were well-stocked, beech-dominated deciduous forest stands in northern Hesse before 1800, particularly at poorly accessible hillside locations. These large stocks of beech wood were utilized by the governments of the different Hessian territories through the establishment of ironworks and hammer mills. Our argumentation is well in line with findings which underline that not all Hessian forests were overexploited in the 18th century. Frequently repeated complaints about ＂wood shortage＂ seemed to be more a political instrument than reality, not only in Hesse, but all over Europe. Consequently, a differentiated assessment of woodland conditions in proto-industrial times is strictly advised, even if contemporary sources draw a dark picture of the historic situation.
