Laserkeilaus puutason biomassan, puutavaralajien sekä laatutiedon ennustamisessa

The precise knowledge of forest structural attributes play an essential role in decision-making, forest management procedure planning and in wood supply chain optimization. Laser scanning (LS) is one of the most promising remote sensing techniques, which can be used to estimate forest attributes at all levels, from single trees to global applications. The main objectives of the present thesis were to develop LS-based methodologies for mapping and measuring single trees. More specifically, new high-density LS-based models and methodologies were developed for the prediction of aboveground biomass (AGB), logging recovery, stem curve and external tree quality estimation. Multisource remote sensing methodologies were additionally introduced for the detailed next generation forest-inventory process. Substudies I and II concentrated on developing LS-based biomass models. Total AGB was estimated with the relative root mean squared errors (RMSE%) of 12.9% and 11.9% for Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies (L.) H.Karst.), respectively using terrestrial LS (TLS) -derived predictors in multiple regression modelling. TLS-based AGB models significantly improved the estimation accuracy of AGB components compared to state-of-the-art allometric biomass models. Airborne LS (ALS) resulted in slightly higher RMSE% values of 26.3% and 36.8% for Scots pine and Norway spruce compared to results obtained with TLS. The goal of substudies III and IV was to predict timber assortment and tree quality information using high-density LS data. Sawlog volumes were estimated with RMSE% of 17.5% and 16.8% with TLS and a combination of TLS and ALS, respectively. Results in IV showed that trees could be successfully classified in different quality classes based on TLS-measured attributes with accuracies between 76.4% and 83.6% depending on the amount of quality classes. Substudies V and VI presented new automatic processing tools for TLS data and a multisource approach for the more detailed prediction of diameter distribution. Automatic processing of TLS data was demonstrated to be effective and accurate and could be utilized to make future TLS measurements more efficient. Accuracies of ~1 cm were achieved using the automatic stem curve procedure. The multisource single-tree inventory approach combined accurate treemaps produced automatically from the TLS data, and ALS individual tree detection technique. Results from diverse forest conditions were promising, resulting in diameter prediction accuracies between 1.4 cm and 4.7 cm depending on tree density and main tree species. Each substudy (I VI) presented new methods and results for single-tree AGB modelling, external tree quality classification, automatic stem reconstruction and multisource approaches.Yksityiskohtainen metsävaratieto on merkittävässä roolissa metsänomistajien päätöksenteon, metsänhoidon suunnittelun sekä puunhankintaketjun optimoinnin tukena. Laserkeilaus on yksi lupaavimmista kaukokartoitustekniikoista, jolla on mahdollista ennustaa metsävaratietoa yksittäisen puun tasolta laajoihin alueisiin. Väitöskirjatyön päätavoitteina oli kehittää laserkeilauspohjaisia menetelmiä yksittäisten puiden kartoitukseen ja mittaukseen. Osajulkaisuissa I ja II selvitettiin laserkeilausmenetelmien tarkkuutta puutason biomassaositteiden mallinnuksessa. Kokonaisbiomassan mallinnustarkkuus maastolaserkeilaukseen perustuen oli männylle 12,9 % ja kuuselle 11,9 %. Maastolaserkeilauksen hyödyntäminen biomassan mallintamisessa tarkensi erityisesti latvusbiomassan mallinnustarkkuutta verrattuna läpimittaan ja pituuteen perustuviin biomassamalleihin. Lentolaserkeilauksen tarkkuudet olivat hieman heikompia verrattuna maastolaserkeilaukseen. Kokonaisbiomassan tarkkuudet olivat männylle 26,3 % ja kuuselle 36,8 %. Osajulkaisuissa III ja IV tavoitteena oli ennustaa puutavaralajikohtaisia tilavuuksia sekä laatutietoa maastolaserkeilauksen ja lentolaserkeilauksen avulla. Tukkipuun tilavuuden ennustetarkkuudet olivat maastolaserkeilausta käytettäessä 17,5 % ja maasto- ja lentolaserkeilauksen yhdistelmää käytettäessä 16,8 %. Puuston laatu on erittäin tärkeä tekijä metsikköä arvioitaessa. Maastolaserkeilauksen avulla yksittäiset puut luokiteltiin puunhankinnan kannalta tärkeisiin laatuluokkiin 76,4 % 83,6 % tarkkuudella. Osajulkaisuissa V ja VI tavoitteena oli kehittää uusia automaattisia menetelmiä maastolaserkeilausaineiston käsittelyyn, sekä monilähdemenetelmiä läpimittajakauman ennustamiseen. Automaattisten menetelmien avulla maastolaserkeilausaineiston käsittelyä on mahdollista tehostaa ja jopa tarkentaa manuaaliseen aineiston käsittelyyn verrattuna. Osajulkaisussa V runkokäyrän mittaustarkkuus oli automaattista aineistonkäsittelymenetelmää käytettäessä ~ 1 cm. Osajulkaisussa VI hyödynnettiin monilähdemenetelmää, jossa tarvittu puukartta mitattiin automaattisesti maastolaserkeilausaineistosta ja läpimittajakaumat ennustettiin maasto- ja lentolaserkeilausaineistojen avulla. Läpimitan ennustetarkkuus oli 1,4 cm ja 4,7 cm välillä puustoltaan hyvin vaihtelevissa metsiköissä. Väitöskirjatyön osajulkaisuissa kehitetyt menetelmät ja esitetyt tulokset osoittivat laserkeilausmenetelmien olevan varteenotettava vaihtoehto yksittäisten puiden kartoitukselle ja mittaamiselle tulevaisuudessa

Puustobiomassan kartoituksen ja seurannan kehittäminen

Tieteen tori: Luonnonvarariskien hallint

Structural Changes in Boreal Forests Can Be Quantified Using Terrestrial Laser Scanning

Terrestrial laser scanning (TLS) has been adopted as a feasible technique to digitize trees and forest stands, providing accurate information on tree and forest structural attributes. However, there is limited understanding on how a variety of forest structural changes can be quantified using TLS in boreal forest conditions. In this study, we assessed the accuracy and feasibility of TLS in quantifying changes in the structure of boreal forests. We collected TLS data and field reference from 37 sample plots in 2014 (T1) and 2019 (T2). Tree stems typically have planar, vertical, and cylindrical characteristics in a point cloud, and thus we applied surface normal filtering, point cloud clustering, and RANSAC-cylinder filtering to identify these geometries and to characterize trees and forest stands at both time points. The results strengthened the existing knowledge that TLS has the capacity to characterize trees and forest stands in space and showed that TLS could characterize structural changes in time in boreal forest conditions. Root-mean-square-errors (RMSEs) in the estimates for changes in the tree attributes were 0.99–1.22 cm for diameter at breast height (Δdbh), 44.14–55.49 cm2 for basal area (Δg), and 1.91–4.85 m for tree height (Δh). In general, tree attributes were estimated more accurately for Scots pine trees, followed by Norway spruce and broadleaved trees. At the forest stand level, an RMSE of 0.60–1.13 cm was recorded for changes in basal area-weighted mean diameter (ΔDg), 0.81–2.26 m for changes in basal area-weighted mean height (ΔHg), 1.40–2.34 m2/ha for changes in mean basal area (ΔG), and 74–193 n/ha for changes in the number of trees per hectare (ΔTPH). The plot-level accuracy was higher in Scots pine-dominated sample plots than in Norway spruce-dominated and mixed-species sample plots. TLS-derived tree and forest structural attributes at time points T1 and T2 differed significantly from each other (p < 0.05). If there was an increase or decrease in dbh, g, h, height of the crown base, crown ratio, Dg, Hg, or G recorded in the field, a similar outcome was achieved by using TLS. Our results provided new information on the feasibility of TLS for the purposes of forest ecosystem growth monitoring

Feasibility of Bi-Temporal Airborne Laser Scanning Data in Detecting Species-Specific Individual Tree Crown Growth of Boreal Forests

The tree crown, with its functionality of assimilation, respiration, and transpiration, is a key forest ecosystem structure, resulting in high demand for characterizing tree crown structure and growth on a spatiotemporal scale. Airborne laser scanning (ALS) was found to be useful in measuring the structural properties associated with individual tree crowns. However, established ALS-assisted monitoring frameworks are still limited. The main objective of this study was to investigate the feasibility of detecting species-specific individual tree crown growth by means of airborne laser scanning (ALS) measurements in 2009 (T1) and 2014 (T2). Our study was conducted in southern Finland over 91 sample plots with a size of 32 × 32 m. The ALS crown metrics of width (WD), projection area (A2D), volume (V), and surface area (A3D) were derived for species-specific individually matched trees in T1 and T2. The Scots pine (Pinus sylvestris), Norway spruce (Picea abies (L.) H. Karst), and birch (Betula sp.) were the three species groups that studied. We found a high capability of bi-temporal ALS measurements in the detection of species-specific crown growth (Δ), especially for the 3D crown metrics of V and A3D, with Cohen’s D values of 1.09–1.46 (p-value < 0.0001). Scots pine was observed to have the highest relative crown growth (rΔ) and showed statistically significant differences with Norway spruce and birch in terms of rΔWD, rΔA2D, rΔV, and rΔA3D at a 95% confidence interval. Meanwhile, birch and Norway spruce had no statistically significant differences in rΔWD, rΔV, and rΔA3D (p-value < 0.0001). However, the amount of rΔ variability that could be explained by the species was only 2–5%. This revealed the complex nature of growth controlled by many biotic and abiotic factors other than species. Our results address the great potential of ALS data in crown growth detection that can be used for growth studies at large scales

Structural Changes in Boreal Forests Can Be Quantified Using Terrestrial Laser Scanning

Terrestrial laser scanning (TLS) has been adopted as a feasible technique to digitize trees and forest stands, providing accurate information on tree and forest structural attributes. However, there is limited understanding on how a variety of forest structural changes can be quantified using TLS in boreal forest conditions. In this study, we assessed the accuracy and feasibility of TLS in quantifying changes in the structure of boreal forests. We collected TLS data and field reference from 37 sample plots in 2014 (T1) and 2019 (T2). Tree stems typically have planar, vertical, and cylindrical characteristics in a point cloud, and thus we applied surface normal filtering, point cloud clustering, and RANSAC-cylinder filtering to identify these geometries and to characterize trees and forest stands at both time points. The results strengthened the existing knowledge that TLS has the capacity to characterize trees and forest stands in space and showed that TLS could characterize structural changes in time in boreal forest conditions. Root-mean-square-errors (RMSEs) in the estimates for changes in the tree attributes were 0.99–1.22 cm for diameter at breast height (Δdbh), 44.14–55.49 cm2 for basal area (Δg), and 1.91–4.85 m for tree height (Δh). In general, tree attributes were estimated more accurately for Scots pine trees, followed by Norway spruce and broadleaved trees. At the forest stand level, an RMSE of 0.60–1.13 cm was recorded for changes in basal area-weighted mean diameter (ΔDg), 0.81–2.26 m for changes in basal area-weighted mean height (ΔHg), 1.40–2.34 m2/ha for changes in mean basal area (ΔG), and 74–193 n/ha for changes in the number of trees per hectare (ΔTPH). The plot-level accuracy was higher in Scots pine-dominated sample plots than in Norway spruce-dominated and mixed-species sample plots. TLS-derived tree and forest structural attributes at time points T1 and T2 differed significantly from each other (p < 0.05). If there was an increase or decrease in dbh, g, h, height of the crown base, crown ratio, Dg, Hg, or G recorded in the field, a similar outcome was achieved by using TLS. Our results provided new information on the feasibility of TLS for the purposes of forest ecosystem growth monitoring

Terrestrial Laser Scanning Reveal Connection Between Changes in Tree Stem Dimensions and Crown Structure

Peer reviewe

Understanding 3D structural complexity of individual Scots pine trees with different management history

Tree functional traits together with processes such as forest regeneration, growth, and mortality affect forest and tree structure. Forest management inherently impacts these processes. Moreover, forest structure, biodiversity, resilience, and carbon uptake can be sustained and enhanced with forest management activities. To assess structural complexity of individual trees, comprehensive and quantitative measures are needed, and they are often lacking for current forest management practices. Here, we utilized 3D information from individual Scots pine (Pinus sylvestris L.) trees obtained with terrestrial laser scanning to, first, assess effects of forest management on structural complexity of individual trees and, second, understand relationship between several tree attributes and structural complexity. We studied structural complexity of individual trees represented by a single scale-independent metric called "box dimension." This study aimed at identifying drivers affecting structural complexity of individual Scots pine trees in boreal forest conditions. The results showed that thinning increased structural complexity of individual Scots pine trees. Furthermore, we found a relationship between structural complexity and stem and crown size and shape as well as tree growth. Thus, it can be concluded that forest management affected structural complexity of individual Scots pine trees in managed boreal forests, and stem, crown, and growth attributes were identified as drivers of it.Peer reviewe

Detecting and characterizing downed dead wood using terrestrial laser scanning

Dead wood is a key forest structural component for maintaining biodiversity and storing carbon. Despite its important role in a forest ecosystem, quantifying dead wood alongside standing trees has often neglected when investigating the feasibility of terrestrial laser scanning (TLS) in forest inventories. The objective of this study was therefore to develop an automatic method for detecting and characterizing downed dead wood with a diameter exceeding 5 cm using multi-scan TLS data. The developed four-stage algorithm included (1) RANSAC-cylinder filtering, (2) point cloud rasterization, (3) raster image segmentation, and (4) dead wood trunk positioning. For each detected trunk, geometry-related quality attributes such as dimensions and volume were automatically determined from the point cloud. For method development and validation, reference data were collected from 20 sample plots representing diverse southern boreal forest conditions. Using the developed method, the downed dead wood trunks were detected with an overall completeness of 33% and correctness of 76%. Up to 92% of the downed dead wood volume were detected at plot level with mean value of 68%. We were able to improve the detection accuracy of individual trunks with visual interpretation of the point cloud, in which case the overall completeness was increased to 72% with mean proportion of detected dead wood volume of 83%. Downed dead wood volume was automatically estimated with an RMSE of 15.0 m(3)/ha (59.3%), which was reduced to 6.4 m(3)/ha (25.3%) as visual interpretation was utilized to aid the trunk detection. The reliability of TLS-based dead wood mapping was found to increase as the dimensions of dead wood trunks increased. Dense vegetation caused occlusion and reduced the trunk detection accuracy. Therefore, when collecting the data, attention must be paid to the point cloud quality. Nevertheless, the results of this study strengthen the feasibility of TLS-based approaches in mapping biodiversity indicators by demonstrating an improved performance in quantifying ecologically most valuable downed dead wood in diverse forest conditions.Peer reviewe

Examining Changes in Stem Taper and Volume Growth with Two-Date 3D Point Clouds

Exact knowledge over tree growth is valuable information for decision makers when considering the purposes of sustainable forest management and planning or optimizing the use of timber, for example. Terrestrial laser scanning (TLS) can be used for measuring tree and forest attributes in very high detail. The study aims at characterizing changes in individual tree attributes (e.g., stem volume growth and taper) during a nine year-long study period in boreal forest conditions. TLS-based three-dimensional (3D) point cloud data were used for identifying and quantifying these changes. The results showed that observing changes in stem volume was possible from TLS point cloud data collected at two different time points. The average volume growth of sample trees was 0.226 m3 during the study period, and the mean relative change in stem volume was 65.0%. In addition, the results of a pairwise Student’s t-test gave strong support (p-value 0.0001) that the used method was able to detect tree growth within the nine-year period between 2008–2017. The findings of this study allow the further development of enhanced methods for TLS-based single tree and forest growth modeling and estimation, which can thus improve the accuracy of forest inventories and offer better tools for future decision-making processes

Assessing feasibility of the forest trafficability map for avoiding rutting - a case study

Information on forest trafficability (i.e. carrying capacity of the forest floor) is required before harvesting operations in Southern Boreal forest conditions. It describes the seasons when harvesting operations may take place without causing substantial damage to the forest soil using standard logging machinery. The available trafficability information have been based on subjective observations made during the wood procurement planning. For supporting forest operations, an open access map product has been developed to provide information on trafficability of forests. The forest stands are distributed into classes that characterize different harvesting seasons based on topographic wetness index, amount of vegetation, ground water height and ditch depth. The main goal of this case study was to evaluate the information of the static forest trafficability map in relation to the detected rutting within logging tracks measured in the field. The analysis concentrated on thinning stands since the effect of rutting is significant on the growth of the remaining trees. The results showed that the static trafficability map provided reliable and slightly conservative estimation of the forest trafficability. The majority (91.7%) of the evaluated stands were harvested without causing significant damage if harvesting was timed correctly compared to the trafficability information. However, it should be pointed out that the weather history at small scale, the skills of a driver, and effects of used machinery are not considered in the map product although they can have a considerable impact on the rutting.Peer reviewe