Accurate and up-to-date information concerning vegetation characteristics is needed for decision-making from individual-tree-level management activities to the strategic planning of forest resources. Outdated information may lead to unbeneficial or even wrong decisions, at least when it comes to the timing of management activities. Airborne laser scanning (ALS) has so far been successfully used for applications involving detailed vegetation mapping because of its capability to simultaneously produce accurate information on vegetation and ground surfaces. The aim of this dissertation was to develop methods for characterizing vegetation and its changes in varying environments. A method called multisource single-tree inventory (MS-STI) was developed in substudy I to update urban tree attributes. In MSSTI stem map was produced with terrestrial laser scanning and by combining the stem map with predictors derived from ALS data it was possible to obtain improved estimates of diameter-at-breast height but also to produce new attributes such as height and crown size. Boat-based mobile laser scanning (MLS) data were employed in substudy II to map riverbank vegetation and identify changes. The overall classification accuracy of 73% was obtained, which is similar to accuracies found in other studies. With multi-temporal MLS data sets changes in vegetation were mapped year to year. In substudy III, open access ALS data were combined with multisource national forest inventory (NFI) data to investigate the drivers associated to wind damage. The special interest was in ALS-based predictors to map areas with wind disturbance and apply logistic regression to produce a continuous probability surface of wind predisposition to identify areas most likely to experience wind damage. The results demonstrated that a combination of ALS and multisource NFI in the modelling approach increased the prediction accuracy from 76% to 81%. The dissertation showed the capability of ALS and MLS for characterizing vegetation and mapping changes in varying environments. The developed applications could increase and expand the utilization of multi-temporal 3D data sets as well as increase data value. The results of this dissertation can be utilized in producing more accurate, diverse, and up-to-date information for decision-making related to natural resources.
{"title":"Predicting vegetation characteristics in a changing environment by means of laser scanning","authors":"N. Saarinen","doi":"10.14214/DF.216","DOIUrl":"https://doi.org/10.14214/DF.216","url":null,"abstract":"Accurate and up-to-date information concerning vegetation characteristics is needed for decision-making from individual-tree-level management activities to the strategic planning of forest resources. Outdated information may lead to unbeneficial or even wrong decisions, at least when it comes to the timing of management activities. Airborne laser scanning (ALS) has so far been successfully used for applications involving detailed vegetation mapping because of its capability to simultaneously produce accurate information on vegetation and ground surfaces. The aim of this dissertation was to develop methods for characterizing vegetation and its changes in varying environments. A method called multisource single-tree inventory (MS-STI) was developed in substudy I to update urban tree attributes. In MSSTI stem map was produced with terrestrial laser scanning and by combining the stem map with predictors derived from ALS data it was possible to obtain improved estimates of diameter-at-breast height but also to produce new attributes such as height and crown size. Boat-based mobile laser scanning (MLS) data were employed in substudy II to map riverbank vegetation and identify changes. The overall classification accuracy of 73% was obtained, which is similar to accuracies found in other studies. With multi-temporal MLS data sets changes in vegetation were mapped year to year. In substudy III, open access ALS data were combined with multisource national forest inventory (NFI) data to investigate the drivers associated to wind damage. The special interest was in ALS-based predictors to map areas with wind disturbance and apply logistic regression to produce a continuous probability surface of wind predisposition to identify areas most likely to experience wind damage. The results demonstrated that a combination of ALS and multisource NFI in the modelling approach increased the prediction accuracy from 76% to 81%. The dissertation showed the capability of ALS and MLS for characterizing vegetation and mapping changes in varying environments. The developed applications could increase and expand the utilization of multi-temporal 3D data sets as well as increase data value. The results of this dissertation can be utilized in producing more accurate, diverse, and up-to-date information for decision-making related to natural resources.","PeriodicalId":375560,"journal":{"name":"Dissertationes Forestales","volume":"48 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113982761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this study latent heat flux (kE) measurements made at 65 boreal and arctic eddy-covariance (EC) sites were analyses by using the Penman–Monteith equation. Sites were stratified into nine different ecosystem types: harvested and burnt forest areas, pine forests, spruce or fir forests, Douglas-fir forests, broadleaf deciduous forests, larch forests, wetlands, tundra and natural grasslands. The Penman–Monteith equation was calibrated with variable surface resistances against half-hourly eddy-covariance data and clear differences between ecosystem types were observed. Based on the modeled behavior of surface and aerodynamic resistances, surface resistance tightly control kE in most mature forests, while it had less importance in ecosystems having shorter vegetation like young or recently harvested forests, grasslands, wetlands and tundra. The parameters of the Penman–Monteith equation were clearly different for winter and summer conditions, indicating that phenological effects on surface resistance are important. We also compared the simulated kE of different ecosystem types under meteorological conditions at one site. Values of kE varied between 15% and 38% of the net radiation in the simulations with mean ecosystem parameters. In general, the simulations suggest that kE is higher from forested ecosystems than from grasslands, wetlands or tundra-type ecosystems. Forests showed usually a tighter stomatal control of kE as indicated by a pronounced sensitivity of surface resistance to atmospheric vapor pressure deficit. Nevertheless, the surface resistance of forests was lower than for open vegetation types including wetlands. Tundra and wetlands had higher surface resistances, which were less sensitive to vapor pressure deficits. The results indicate that the variation in surface resistance within and between different vegetation types might play a significant role in energy exchange between terrestrial ecosystems and atmosphere. These results suggest the need to take into account vegetation type and phenology in energy exchange modeling.
{"title":"Linking water and carbon cycles: modeling latent heat exchange and dissolved organic carbon","authors":"V. Kasurinen","doi":"10.14214/df215.htm","DOIUrl":"https://doi.org/10.14214/df215.htm","url":null,"abstract":"In this study latent heat flux (kE) measurements made at 65 boreal and arctic eddy-covariance (EC) sites were analyses by using the Penman–Monteith equation. Sites were stratified into nine different ecosystem types: harvested and burnt forest areas, pine forests, spruce or fir forests, Douglas-fir forests, broadleaf deciduous forests, larch forests, wetlands, tundra and natural grasslands. The Penman–Monteith equation was calibrated with variable surface resistances against half-hourly eddy-covariance data and clear differences between ecosystem types were observed. Based on the modeled behavior of surface and aerodynamic resistances, surface resistance tightly control kE in most mature forests, while it had less importance in ecosystems having shorter vegetation like young or recently harvested forests, grasslands, wetlands and tundra. The parameters of the Penman–Monteith equation were clearly different for winter and summer conditions, indicating that phenological effects on surface resistance are important. We also compared the simulated kE of different ecosystem types under meteorological conditions at one site. Values of kE varied between 15% and 38% of the net radiation in the simulations with mean ecosystem parameters. In general, the simulations suggest that kE is higher from forested ecosystems than from grasslands, wetlands or tundra-type ecosystems. Forests showed usually a tighter stomatal control of kE as indicated by a pronounced sensitivity of surface resistance to atmospheric vapor pressure deficit. Nevertheless, the surface resistance of forests was lower than for open vegetation types including wetlands. Tundra and wetlands had higher surface resistances, which were less sensitive to vapor pressure deficits. The results indicate that the variation in surface resistance within and between different vegetation types might play a significant role in energy exchange between terrestrial ecosystems and atmosphere. These results suggest the need to take into account vegetation type and phenology in energy exchange modeling.","PeriodicalId":375560,"journal":{"name":"Dissertationes Forestales","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124857659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The emergence and early development of forest resource economic thought: From land and forest valuation to marginal analysis and vintage capital models","authors":"E. Viitala","doi":"10.14214/DF.212","DOIUrl":"https://doi.org/10.14214/DF.212","url":null,"abstract":"","PeriodicalId":375560,"journal":{"name":"Dissertationes Forestales","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122462950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Seasonal and spatial variation of VOC emissions from boreal Scots pine forest","authors":"J. Aalto","doi":"10.14214/DF.208","DOIUrl":"https://doi.org/10.14214/DF.208","url":null,"abstract":"","PeriodicalId":375560,"journal":{"name":"Dissertationes Forestales","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116918316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Annual commercial roundwood removal in Finland has reached approximately 50 million m3, delivering almost 1.6 billion Euros of stumpage earnings to forest owners. The aim of this dissertation is to study and model the production costs of saw-, pulp and paper mills and the combined heat and power (CHP) plant, which are the branches of forest industry that create most of the industry’s wood-paying capability. The modelling was performed by implementing the activity-based costing (ABC) method for virtual greenfield mills located in Finland. Firstly, according to the principles of ABC, mill productions were divided into processes. The sawmills consisted of eight processes, while the pulp and paper mills of ten each and the CHP plant consisted of four processes. Secondly, all required production resources of each process were defined and quantified. Thirdly, the costs of each process caused by using the wood processing or energy use resources were allocated to the products or raw materials with cost drivers. Results of the example calculations indicated that the cost structures of the studied mills shared some similarities: wood, pulp or paper drying was a relatively expensive process. The share of drying was 40%, 39% and 18% of the annual costs in the sawmill, pulp mill and paper mill, respectively. The fluidized bed boiler represented 47% of the total costs of the CHP plant. Taking into consideration the practical limitations of the test calculations, the profitability of the pulp and paper mills and CHP plant were on a healthy level. The sawmilling case was left out of the profit calculations due to lack of market price information. According to the results, ABC was well-suited to the demands of forest industry. The models provide useful tools for cost-based decision-making for both forestry specialists and the forest industry. The results indicate that the sawing pattern is a very important cost factor in sawmilling, while energy production was crucial for the pulp and paper industry and the utilization rate was in a key position for CHP. From the forest industry viewpoint the models directly aid in performance analyses; results of the calculations revealed that the relatively high share of drying costs in the industry signals that the most cost-effective improvements could be found from energy savings, which has been the tendency in past years. These results can be combined with the forest end of the supply chain, whereby forest engineers have access to better control over tree-bucking optimization and different parallel value chains of forestry can be compared and evaluated with high accuracy.
{"title":"Activity-based costing method in forest industry modelling the production and costs of sawing, the pulp and paper industry, and energy production","authors":"H. Korpunen","doi":"10.14214/DF.203","DOIUrl":"https://doi.org/10.14214/DF.203","url":null,"abstract":"Annual commercial roundwood removal in Finland has reached approximately 50 million m3, delivering almost 1.6 billion Euros of stumpage earnings to forest owners. The aim of this dissertation is to study and model the production costs of saw-, pulp and paper mills and the combined heat and power (CHP) plant, which are the branches of forest industry that create most of the industry’s wood-paying capability. The modelling was performed by implementing the activity-based costing (ABC) method for virtual greenfield mills located in Finland. Firstly, according to the principles of ABC, mill productions were divided into processes. The sawmills consisted of eight processes, while the pulp and paper mills of ten each and the CHP plant consisted of four processes. Secondly, all required production resources of each process were defined and quantified. Thirdly, the costs of each process caused by using the wood processing or energy use resources were allocated to the products or raw materials with cost drivers. Results of the example calculations indicated that the cost structures of the studied mills shared some similarities: wood, pulp or paper drying was a relatively expensive process. The share of drying was 40%, 39% and 18% of the annual costs in the sawmill, pulp mill and paper mill, respectively. The fluidized bed boiler represented 47% of the total costs of the CHP plant. Taking into consideration the practical limitations of the test calculations, the profitability of the pulp and paper mills and CHP plant were on a healthy level. The sawmilling case was left out of the profit calculations due to lack of market price information. According to the results, ABC was well-suited to the demands of forest industry. The models provide useful tools for cost-based decision-making for both forestry specialists and the forest industry. The results indicate that the sawing pattern is a very important cost factor in sawmilling, while energy production was crucial for the pulp and paper industry and the utilization rate was in a key position for CHP. From the forest industry viewpoint the models directly aid in performance analyses; results of the calculations revealed that the relatively high share of drying costs in the industry signals that the most cost-effective improvements could be found from energy savings, which has been the tendency in past years. These results can be combined with the forest end of the supply chain, whereby forest engineers have access to better control over tree-bucking optimization and different parallel value chains of forestry can be compared and evaluated with high accuracy.","PeriodicalId":375560,"journal":{"name":"Dissertationes Forestales","volume":"693 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122979036","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Environmental quality has a direct effect on citizens’ welfare. To quantify this effect, the four articles of this thesis analyse Finnish citizens’ willingness to pay (WTP) for increased forest conservation using the contingent valuation (CV) and choice experiment (CE) methods. These methods are based on neo-classical welfare economics augmented with the choice process framework originating from psychology and behavioural economics. Using the CV method, we analyse how WTP is affected by respondents’ uncertainty, by the share of nonrespondents and by the considerably high share of “yes” responses at the highest proposed costs to households. The CE data are used to study the effects of different conservation programme characteristics on WTP. The results show that Finnish citizens support increased forest conservation. The median WTP in the contingent valuation was 72 EUR, i.e. 50% of respondents supported increased conservation if the costs per household did not exceed 72 EUR. The mean WTP estimates were sensitive to modelling assumptions and assumptions concerning the nonrespondent preferences. This emphasises the need for careful sensitivity analyses when results are used for welfare measurement and policy planning. Respondents’ choices in the valuation questions were affected by the household costs of conservation and other socioeconomic characteristics. The results suggest that the choices in valuation tasks are affected by economic and psychological factors. The study gives important insights into the choice behaviour and lower and upper bound estimates of WTP. These estimates are somewhat lower than those in comparable earlier Finnish studies. In CV, respondents seemed insensitive to programme size while the extent of the proposed project had a significant effect on the choices in CE.
{"title":"Contingent valuation and choice experiment of citizens' willingness to pay for forest conservation in southern Finland","authors":"E. Haltia","doi":"10.14214/DF.204","DOIUrl":"https://doi.org/10.14214/DF.204","url":null,"abstract":"Environmental quality has a direct effect on citizens’ welfare. To quantify this effect, the four articles of this thesis analyse Finnish citizens’ willingness to pay (WTP) for increased forest conservation using the contingent valuation (CV) and choice experiment (CE) methods. These methods are based on neo-classical welfare economics augmented with the choice process framework originating from psychology and behavioural economics. Using the CV method, we analyse how WTP is affected by respondents’ uncertainty, by the share of nonrespondents and by the considerably high share of “yes” responses at the highest proposed costs to households. The CE data are used to study the effects of different conservation programme characteristics on WTP. The results show that Finnish citizens support increased forest conservation. The median WTP in the contingent valuation was 72 EUR, i.e. 50% of respondents supported increased conservation if the costs per household did not exceed 72 EUR. The mean WTP estimates were sensitive to modelling assumptions and assumptions concerning the nonrespondent preferences. This emphasises the need for careful sensitivity analyses when results are used for welfare measurement and policy planning. Respondents’ choices in the valuation questions were affected by the household costs of conservation and other socioeconomic characteristics. The results suggest that the choices in valuation tasks are affected by economic and psychological factors. The study gives important insights into the choice behaviour and lower and upper bound estimates of WTP. These estimates are somewhat lower than those in comparable earlier Finnish studies. In CV, respondents seemed insensitive to programme size while the extent of the proposed project had a significant effect on the choices in CE.","PeriodicalId":375560,"journal":{"name":"Dissertationes Forestales","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126015756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Replacing fossil fuels with renewable energy sources is an increasingly important research subject in order to combat the global climate change. Wood is a well utilised source of energy that has some problematic characteristics common to all lignocellulosic biomass. Moisture affects the supply chain of wood fuels negatively by complicating logistics and combustion. Hygroscopicity of stored wood leads to fungal deterioration and consequent losses in heating value. The problem has been addressed by reducing the hygroscopicity through the thermal pre-treatment process of torrefaction. The torrefied material is said to be resistant to fungal degradation and subsequent dry matter losses. However, only few studies exist, and the material’s performance in storage has been pointed out as an important research area. This thesis aims to provide much needed answers related to the storage properties of torrefied wood and charcoal, most importantly the effect of moisture. This thesis is made up of four studies, in which the sorption properties and fungal degradation of torrefied spruce and birch, as well as charcoal produced from the same feedstock, were investigated. In one part study, torrefied and steam exploded pellets were compared with the undensified material. The material adsorbed only minor amounts of water vapour, and the hydroxyl group accessibility and particle size were reduced. Although the capillary absorption became slower, the capacity for water uptake increased. This led to high moisture contents during the storage trials. It was also shown that the material is degraded by fungi. The degradation was slow, but dry matter losses were recorded in laboratory conditions. Furthermore, the fungal activity increased the material’s moisture content. The torrefied material hosted abundant fungal flora following outside storage trials, and many of the identified genera were known allergens. It was shown that torrefied pellets do not tolerate contact with water and should be stored covered.
{"title":"Moisture sorption properties and fungal degradation of torrefied wood in storage","authors":"M. Kymäläinen","doi":"10.14214/DF.206","DOIUrl":"https://doi.org/10.14214/DF.206","url":null,"abstract":"Replacing fossil fuels with renewable energy sources is an increasingly important research subject in order to combat the global climate change. Wood is a well utilised source of energy that has some problematic characteristics common to all lignocellulosic biomass. Moisture affects the supply chain of wood fuels negatively by complicating logistics and combustion. Hygroscopicity of stored wood leads to fungal deterioration and consequent losses in heating value. The problem has been addressed by reducing the hygroscopicity through the thermal pre-treatment process of torrefaction. The torrefied material is said to be resistant to fungal degradation and subsequent dry matter losses. However, only few studies exist, and the material’s performance in storage has been pointed out as an important research area. This thesis aims to provide much needed answers related to the storage properties of torrefied wood and charcoal, most importantly the effect of moisture. This thesis is made up of four studies, in which the sorption properties and fungal degradation of torrefied spruce and birch, as well as charcoal produced from the same feedstock, were investigated. In one part study, torrefied and steam exploded pellets were compared with the undensified material. The material adsorbed only minor amounts of water vapour, and the hydroxyl group accessibility and particle size were reduced. Although the capillary absorption became slower, the capacity for water uptake increased. This led to high moisture contents during the storage trials. It was also shown that the material is degraded by fungi. The degradation was slow, but dry matter losses were recorded in laboratory conditions. Furthermore, the fungal activity increased the material’s moisture content. The torrefied material hosted abundant fungal flora following outside storage trials, and many of the identified genera were known allergens. It was shown that torrefied pellets do not tolerate contact with water and should be stored covered.","PeriodicalId":375560,"journal":{"name":"Dissertationes Forestales","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133555204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Over the past decades it has been shown that remotely sensed auxiliary data have a potential to increase the precision of key estimators in sample-based forest surveys. This thesis was motivated by the increasing availability of remotely sensed data, and the objectives were to investigate how this type of auxiliary data can be used for improving both the design and the estimators in sample-based surveys. Two different modes of inference were studied: model-based inference and design-based inference. Empirical data for the studies were acquired from a boreal forest area in the Kuortane region of western Finland. The data comprised a combination of auxiliary information derived from airborne LiDAR and Landsat data, and field sample plot data collected using a modification of the 10 Finnish National Forest Inventory. The studied forest attribute was growing stock volume. In Paper I, remotely sensed data were applied at the design stage, using a newly developed design which spreads the sample efficiently in the space of auxiliary data. The analysis was carried out through Monte Carlo sampling simulation using a simulated population developed by way of a copula technique utilizing empirical data from Kuortane. The results of the study showed that the new design resulted in a higher precision when compared to a traditional design where the samples were spread only in the space of geographical data. In Paper II, remotely sensed auxiliary data were applied in connection with model-assisted estimation. The auxiliary data were used mainly in the estimation stage, but also in the design stage through probabilityproportional-to-size sampling utilizing Landsat data. The results showed that LiDAR auxiliary data considerably improved the precision compared to estimation based only on field samples. Additionally, in spite of their low correlation with growing stock volume, adding Landsat data as auxiliary data further improved the precision of the estimators. In Paper III, the focus was set on model-based inference and the influence of the use of different models on the precision of estimators. For this study, a second simulated population was developed utilizing the empirical data, including only non-zero growing stock volume observations. The results revealed that the choice of model form in model-based inference had minor to moderate effects on the precision of the estimators. Furthermore, as expected, it was found that model-based prediction and model-assisted estimation performed almost equally well. In Paper IV, the precision of model-based prediction and model-assisted estimation was compared in a case where field and remotely sensed data were geographically mismatched. The same simulated population as used in Paper III was employed in this study. The results showed that the precision in most cases decreased considerably, and more so when LiDAR auxiliary data were applied, compared to when Landsat auxiliary data were used. As for the choice of inferential
{"title":"Use of remotely sensed auxiliary data for improving sample-based forest inventories","authors":"S. Saarela","doi":"10.14214/DF.201","DOIUrl":"https://doi.org/10.14214/DF.201","url":null,"abstract":"Over the past decades it has been shown that remotely sensed auxiliary data have a potential to increase the precision of key estimators in sample-based forest surveys. This thesis was motivated by the increasing availability of remotely sensed data, and the objectives were to investigate how this type of auxiliary data can be used for improving both the design and the estimators in sample-based surveys. Two different modes of inference were studied: model-based inference and design-based inference. Empirical data for the studies were acquired from a boreal forest area in the Kuortane region of western Finland. The data comprised a combination of auxiliary information derived from airborne LiDAR and Landsat data, and field sample plot data collected using a modification of the 10 Finnish National Forest Inventory. The studied forest attribute was growing stock volume. In Paper I, remotely sensed data were applied at the design stage, using a newly developed design which spreads the sample efficiently in the space of auxiliary data. The analysis was carried out through Monte Carlo sampling simulation using a simulated population developed by way of a copula technique utilizing empirical data from Kuortane. The results of the study showed that the new design resulted in a higher precision when compared to a traditional design where the samples were spread only in the space of geographical data. In Paper II, remotely sensed auxiliary data were applied in connection with model-assisted estimation. The auxiliary data were used mainly in the estimation stage, but also in the design stage through probabilityproportional-to-size sampling utilizing Landsat data. The results showed that LiDAR auxiliary data considerably improved the precision compared to estimation based only on field samples. Additionally, in spite of their low correlation with growing stock volume, adding Landsat data as auxiliary data further improved the precision of the estimators. In Paper III, the focus was set on model-based inference and the influence of the use of different models on the precision of estimators. For this study, a second simulated population was developed utilizing the empirical data, including only non-zero growing stock volume observations. The results revealed that the choice of model form in model-based inference had minor to moderate effects on the precision of the estimators. Furthermore, as expected, it was found that model-based prediction and model-assisted estimation performed almost equally well. In Paper IV, the precision of model-based prediction and model-assisted estimation was compared in a case where field and remotely sensed data were geographically mismatched. The same simulated population as used in Paper III was employed in this study. The results showed that the precision in most cases decreased considerably, and more so when LiDAR auxiliary data were applied, compared to when Landsat auxiliary data were used. As for the choice of inferential","PeriodicalId":375560,"journal":{"name":"Dissertationes Forestales","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121024371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This thesis presents basic research on how airborne LiDAR measurements of forest vegetation are influenced by the interplay of the geometric-optical properties of vegetation, sensor function and acquisition settings. Within the work, examining the potential of waveform (WF) recording sensors was of particular interest. Study I focused upon discrete return LiDAR measurements of understory trees. It showed that transmission losses influenced the intensity of observations and echo triggering probabilities, and also skewed the distribution of echoes towards those triggered by highly reflective or dense targets. The intensity data were of low value for species identification, but the abundance of understory trees could be predicted based on echo height distributions. In study II, a method of close-range terrestrial photogrammetry was developed. Images were shown as being useful for visualizations and even the geometric quality control of LiDAR data. The strength of backscattering was shown to correlate with the projected area extracted from the images. In study III, a LiDAR simulation model was developed and validated against real measurements. The model was able to be used for sensitivity analyses to illustrate how plant structure or different pulse properties influence the WF data. Both simulated and real data showed that WF data were able to capture small-scale variations in the structural and optical properties of juvenile forest vegetation. Study IV illustrated the potential of WF data in the species classification of larger trees. The WF features that separated tree species were also dependent on other variables such as tree size and phenology. Inherent between-tree differences in structure were quantified and the effects of pulse density on the features were examined. Overall, the thesis provides basic findings on how LiDAR pulses interact with forest vegetation, and serves to link theory with real observations. The results contribute to an improved understanding of LiDAR measurements and their limitations, and thus provide support for further improvements in both data interpretation methods and specific sensor design.
{"title":"Towards an enhanced understanding of airborne LiDAR measurements of forest vegetation","authors":"A. Hovi","doi":"10.14214/DF.200","DOIUrl":"https://doi.org/10.14214/DF.200","url":null,"abstract":"This thesis presents basic research on how airborne LiDAR measurements of forest vegetation are influenced by the interplay of the geometric-optical properties of vegetation, sensor function and acquisition settings. Within the work, examining the potential of waveform (WF) recording sensors was of particular interest. Study I focused upon discrete return LiDAR measurements of understory trees. It showed that transmission losses influenced the intensity of observations and echo triggering probabilities, and also skewed the distribution of echoes towards those triggered by highly reflective or dense targets. The intensity data were of low value for species identification, but the abundance of understory trees could be predicted based on echo height distributions. In study II, a method of close-range terrestrial photogrammetry was developed. Images were shown as being useful for visualizations and even the geometric quality control of LiDAR data. The strength of backscattering was shown to correlate with the projected area extracted from the images. In study III, a LiDAR simulation model was developed and validated against real measurements. The model was able to be used for sensitivity analyses to illustrate how plant structure or different pulse properties influence the WF data. Both simulated and real data showed that WF data were able to capture small-scale variations in the structural and optical properties of juvenile forest vegetation. Study IV illustrated the potential of WF data in the species classification of larger trees. The WF features that separated tree species were also dependent on other variables such as tree size and phenology. Inherent between-tree differences in structure were quantified and the effects of pulse density on the features were examined. Overall, the thesis provides basic findings on how LiDAR pulses interact with forest vegetation, and serves to link theory with real observations. The results contribute to an improved understanding of LiDAR measurements and their limitations, and thus provide support for further improvements in both data interpretation methods and specific sensor design.","PeriodicalId":375560,"journal":{"name":"Dissertationes Forestales","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127528888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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