Browsing by Subject "Forest inventory"

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  • Alekseev, Alexander; Tomppo, Erkki; McRoberts, Ronald E.; von Gadow, Klaus (Springer Singapore, 2019)
    Abstract The State Forest Inventory (SFI) in the Russian Federation is a relatively new project that is little known in the English-language scientific literature. Following the stipulations of the Forest Act of 2006, the first SFI sample plots in this vast territory were established in 2007. The 34 Russian forest regions were the basic geographical units for all statistical estimates and served as a first-level stratification, while a second level was based on old inventory data and remotely sensed data. The sampling design was to consist of a simple random sample of 84,700 circular 500 m2 sample plots over forest land. Each sample plot consists of three nested concentric circular subplots with radii of 12.62, 5.64 and 2.82 m and additional subplots for assessing and describing undergrowth, regeneration and ground vegetation. In total, 117 variables were to be measured or assessed on each plot. Although field work has begun, the methodology has elicited some criticism. The simple random sampling design is less efficient than a systematic design featuring sample plot clusters and a mix of temporary and permanent plots. The second-level stratification is mostly ineffective for increasing precision. Qualitative variables, which are not always essential, are dominant, while important quantitative variables are under-represented. Because of very slow progress, in 2018 the original plan was adjusted by reducing the number of permanent sample plots from 84,700 to 68,287 so that the first SFI cycle could be completed by 2020.
  • Alekseev, Alexander; Tomppo, Erkki; McRoberts, Ronald E.; von Gadow, Klaus (2019)
    The State Forest Inventory (SFI) in the Russian Federation is a relatively new project that is little known in the English-language scientific literature. Following the stipulations of the Forest Act of 2006, the first SFI sample plots in this vast territory were established in 2007. The 34 Russian forest regions were the basic geographical units for all statistical estimates and served as a first-level stratification, while a second level was based on old inventory data and remotely sensed data. The sampling design was to consist of a simple random sample of 84,700 circular 500m(2) sample plots over forest land. Each sample plot consists of three nested concentric circular subplots with radii of 12.62, 5.64 and 2.82m and additional subplots for assessing and describing undergrowth, regeneration and ground vegetation. In total, 117 variables were to be measured or assessed on each plot.Although field work has begun, the methodology has elicited some criticism. The simple random sampling design is less efficient than a systematic design featuring sample plot clusters and a mix of temporary and permanent plots. The second-level stratification is mostly ineffective for increasing precision. Qualitative variables, which are not always essential, are dominant, while important quantitative variables are under-represented. Because of very slow progress, in 2018 the original plan was adjusted by reducing the number of permanent sample plots from 84,700 to 68,287 so that the first SFI cycle could be completed by 2020.
  • Korpela, Ilkka (2017)
    Forest inventories comprise observations, models and sampling. Airborne LiDAR has established its role in providing observations of canopy geometry and topography. These data are input for estimation of important forest properties to support forestry-related decision-making. A major deficiency in forest remote sensing is tree species identification. This study examines the option of using multi-footprint airborne LiDAR data. Features of such sensor design exist in recently introduced multispectral laser scanners. The first objective was to acquire radiometrically normalized, multi-footprint (11, 22, 44 and 59 cm) waveform (WF) data that characterize 1064nm backscatter reflectance on the interval scale. The second objective was to analyze and validate the data quality in order to draw the correct conclusions about the effect of footprint size on WFs from natural and man-made targets. The experiment was carried out in Finland. Footprint variation was generated by acquiring data at different flying heights and by adjusting the transmitted power. The LiDAR campaign was successful and the data were of sufficient quality, except for a 1 dB trend due to the atmosphere. Significant findings were made conceming the magnitude of atmospheric losses, the linearity of the amplitude scale and the bandwidth characteristics of the receiver, the stability of the transmitter, the precision of the amplitude data and the transmission losses in canopies and power lines, as well as the response of WF attributes to footprint size in forest canopies. Multi-footprint data are a promising approach although the tree species-specific signatures were weak. (C) 2016 Elsevier Inc. All rights reserved.
  • Vauhkonen, Jari; Ruotsalainen, Roope (2017)
    Determining optimal forest management to provide multiple goods and services, also referred to as Ecosystem Services (ESs), requires operational-scale information on the suitability of the forest for the provisioning of various ESs. Remote sensing allows wall-to-wall assessments and provides pixel data for a flexible composition of the management units. The purpose of this study was to incorporate models of ES provisioning potential in a spatial prioritization framework and to assess the pixel-level allocation of the land use. We tessellated the forested area in a landscape of altogether 7500 ha to 27,595 pixels of 48 x 48 m(2) and modeled the potential of each pixel to provide biodiversity, timber, carbon storage, and recreational amenities as indicators of supporting, provisioning, regulating, and cultural ESs, respectively. We analyzed spatial overlaps between the individual ESs, the potential to provide multiple ESs, and tradeoffs due to production constraints in a fraction of the landscape. The pixels considered most important for the individual ESs overlapped as much as 78% between carbon storage and timber production and up to 52.5% between the other ESs. The potential for multiple ESs could be largely explained in terms of forest structure as being emphasized to sparsely populated, spruce-dominated old forests with large average tree size. Constraining the production of the ESs in the landscape based on the priority maps, however, resulted in sub-optimal choices compared to an optimized production. Even though the land-use planning cannot be completed without involving the stakeholders' preferences, we conclude that the workflow described in this paper produced valuable information on the overlaps and tradeoffs of the ESs for the related decision support. (C) 2016 Elsevier B.V. All rights reserved.
  • Vauhkonen, Jari (2020)
    Key Message Tree-level forest inventory data are becoming increasingly available, which motivates the use of these data for decision-making. However, airborne inventories carried out tree-by-tree typically include systematic errors, which can propagate to objective function variables used to determine optimal forest management. Effects of under-detection focused on the smallest trees on predicted immediate harvest profits and future expectation values were assessed assuming different sites and interest rates. Management decisions based on the erroneous information caused losses of 0-17% of the total immediate and future expected income of Scots pine stands. Context Optimal decisions on how to manage forest stands can depend on the absence or presence of intermediate and understory trees. Yet, these tree strata are likely prone to inventory errors. Aims The aim of this study is to examine implications of making stand management decisions based on data that include systematic errors resembling those typically observed in airborne inventories carried out tree-by-tree. Methods Stand management instructions were developed based on theoretical diameter distribution functions simulated to have different shape, scale, and frequency parameters corresponding to various degrees of under-detection focused on the smallest trees. Immediate harvest income and future expectation value were derived based on various management alternatives simulated. Results Errors in diameter distributions affected the predicted harvest profits and future expectation values differently between the simulated alternatives and depending on site type and interest rate assumptions. As a result, different alternatives were considered as optimal management compared to the use of the error-free reference distributions. In particular, the use of no management or most intensive management alternatives became preferred over alternatives with intermediate harvesting intensities. Certain harvesting types such as thinning from below became preferred more often than what was optimal. The errors did not affect the selection of the management alternative in 71% of the simulations, whereas in the remaining proportion, relying on the erroneous information would have caused losing 2%, on average, and 17% at maximum, of the total immediate and future expected income. Conclusion The effects above might not have been discovered, if the results were validated for inventory totals instead of separately considering the immediate and future income and losses produced by the erroneous decisions. It is recommended not to separate but to integrate the inventory and planning systems for well-informed decisions.
  • Luoma, Ville; Vastaranta, Mikko; Eyvindson, Kyle; Kankare, Ville; Saarinen, Ninni; Holopainen, Markus; Hyyppa, Juha (Springer International Publishing AG, 2017)
    Lecture Notes in Geoinformation and Cartography
    Currently the forest sector in Finland is looking towards the next generation's forest resource information systems. Information used in forest planning is currently collected by using an area-based approach (ABA) where airborne laser scanning (ALS) data are used to generalize field-measured inventory attributes over an entire inventory area. Inventories are typically updated at 10-year interval. Thus, one of the key challenges is the age of the inventory information and the cost-benefit trade-off between using the old data and obtaining new data. Prediction of future forest resource information is possible through growth modelling. In this paper, the error sources related to ALS-based forest inventory and the growth models applied in forest planning to update the forest resource information were examined. The error sources included (i) forest inventory, (ii) generation of theoretical stem distribution, and (iii) growth modelling. Error sources (ii) and (iii) stem from the calculations used for forest planning, and were combined in the investigations. Our research area, Evo, is located in southern Finland. In all, 34 forest sample plots (300 m(2)) have been measured twice tree-by-tree. First measurements have been carried out in 2007 and the second measurements in 2014 which leads to 7 year updating period. Respectively, ALS-based forest inventory data were available for 2007. The results showed that prediction of theoretical stem distribution and forest growth modelling affected only slightly to the quality of the predicted stem volume in short-term information update when compared to forest inventory error.
  • Kansanen, Kasper; Vauhkonen, Jari; Lahivaara, Timo; Seppanen, Aku; Maltamo, Matti; Mehtatalo, Lauri (2019)
    Errors in individual tree detection and delineation affect diameter distribution predictions based on crown attributes extracted from the detected trees. We develop a methodology for circumventing these problems. The method is based on matching cumulative distribution functions of field measured tree diameter distributions and crown radii distributions extracted from airborne laser scanning data through individual tree detection presented by Vauhkonen and Mehtatalo (2015). In this study, empirical distribution functions and a monotonic, nonlinear model curve are introduced. Tree crown radius distribution produced by individual tree detection is corrected by a method taking into account that all trees cannot be detected. The evaluation is based on the ability of the developed model sequence to predict quadratic mean diameter and total basal area. The studied data consists of 36 field plots in a typical boreal managed forest area in eastern Finland. The suggested enhancements to the model sequence produce improved results in most of the test cases. Most notably, in leaveone-out cross-validation experiments the modified models improve RMSE of basal area 13% in the full data and RMSE of quadratic mean diameter and basal area 69% and 11%, respectively, in pure pine plots. Better modeling of the crown radius distribution and improved matching between crown radii and stem diameters add the operational premises of the full distribution matching.
  • Lukes, Petr; Rautiainen, Miina; Manninen, Terhikki; Stenberg, Pauline; Mottus, Matti (2014)
    Land surface albedo is an essential climate variable controlling the planetary radiative energy budget, yet it is still among the main uncertainties of the radiation budget in the current climate modeling. To date, albedo satellite products have not been linked to extensive forest inventory data sets due to the lack of ground reference data. Here, we used comprehensive and detailed maps of forest inventory variables to couple forest structure and MODIS albedo products for both winter and summer conditions. We investigated how the relationships between forest variables and albedo change seasonally and along latitudinal gradients in the forest biomes of Finland between 60° and 70° N. We observed an increase in forest albedo with increasing latitude in winter but not in summer. Also, relationships between forest variables and the black-sky albedo or directional–hemispherical reflectance (DHR) at different latitudes were tighter in winter than in summer, especially for forest biomass. Summer albedo was only weakly correlated with the traditional inventory variables. Our findings suggest that the relationships between forest variables and DHR depend on latitude.
  • Wang, Yunsheng; Lehtomäki, Matti; Liang, Xinlian; Pyörälä, Jiri Kristian; Kukko, Antero; Jaakkola, Anttoni; Liu, Jingbin; Feng, Ziyi; Chen, Ruizhi; Hyyppä, Juha (2019)
    Quantitative comparisons of tree height observations from different sources are scarce due to the difficulties in effective sampling. In this study, the reliability and robustness of tree height observations obtained via a conventional field inventory, airborne laser scanning (ALS) and terrestrial laser scanning (TLS) were investigated. A carefully designed non-destructive experiment was conducted that included 1174 individual trees in 18 sample plots (32 m x 32 m) in a Scandinavian boreal forest. The point density of the ALS data was approximately 450 points/m(2). The TLS data were acquired with multi-scans from the center and the four quadrant directions of the sample plots. Both the ALS and TLS data represented the cutting edge point cloud products. Tree heights were manually measured from the ALS and TLS point clouds with the aid of existing tree maps. Therefore, the evaluation results revealed the capacities of the applied laser scanning (LS) data while excluding the influence of data processing approach such as the individual tree detection. The reliability and robustness of different tree height sources were evaluated through a cross-comparison of the ALS-, TLS-, and field- based tree heights. Compared to ALS and TLS, field measurements were more sensitive to stand complexity, crown classes, and species. Overall, field measurements tend to overestimate height of tall trees, especially tall trees in codominant crown class. In dense stands, high uncertainties also exist in the field measured heights for small trees in intermediate and suppressed crown class. The ALS-based tree height estimates were robust across all stand conditions. The taller the tree, the more reliable was the ALS-based tree height. The highest uncertainty in ALS-based tree heights came from trees in intermediate crown class, due to the difficulty of identifying treetops. When using TLS, reliable tree heights can be expected for trees lower than 15-20 m in height, depending on the complexity of forest stands. The advantage of LS systems was the robustness of the geometric accuracy of the data. The greatest challenges of the LS techniques in measuring individual tree heights lie in the occlusion effects, which lead to omissions of trees in intermediate and suppressed crown classes in ALS data and incomplete crowns of tall trees in TLS data.
  • Yrttimaa, Tuomas; Saarinen, Ninni; Kankare, Ville; Hynynen, Jari; Huuskonen, Saija; Holopainen, Markus; Hyyppä, Juha; Vastaranta, Mikko (2020)
    There is a limited understanding of how forest structure affects the performance of methods based on terrestrial laser scanning (TLS) in characterizing trees and forest environments. We aim to improve this understanding by studying how different forest management activities that shape tree size distributions affect the TLS-based forest characterization accuracy in managed Scots pine (Pinus sylvestris L.) stands. For that purpose, we investigated 27 sample plots consisting of three different thinning types, two thinning intensities as well as control plots without any treatments. Multi-scan TLS point clouds were collected from the sample plots, and a point cloud processing algorithm was used to segment individual trees and classify the segmented point clouds into stem and crown points. The classified point clouds were further used to estimate tree and forest structural attributes. With the TLS-based forest characterization, almost 100% completeness in tree detection, 0.7 cm (3.4%) root-mean-square- error (RMSE) in diameter-at-breast-height measurements, 0.9–1.4 m (4.5–7.3%) RMSE in tree height measure-ments, and <6% relative RMSE in the estimates of forest structural attributes (i.e. mean basal area, number of trees per hectare, mean volume, basal area-weighted mean diameter and height) were obtained depending on the applied thinning type. Thinnings decreased variation in horizontal and vertical forest structure, which especially favoured the TLS-based tree detection and tree height measurements, enabling reliable estimates for forest structural attributes. A considerably lower performance was recorded for the control plots. Thinning intensity was noticed to affect more on the accuracy of TLS-based forest characterization than thinning type. The number of trees per hectare and the proportion of suppressed trees were recognized as the main factors affecting the accuracy of TLS-based forest characterization. The more variation there was in the tree size distribution, the more challenging it was for the TLS-based method to capture all the trees and derive the tree and forest structural attributes. In general, consistent accuracy and reliability in the estimates of tree and forest attributes can be expected when using TLS for characterizing managed boreal forests.
  • Liang, Xinlian; Kankare, Ville; Hyyppä, Juha; Wang, Yunsheng; Kukko, Antero; Haggren, Henrik; Yu, Xiaowei; Kaartinen, Harri; Jaakkola, Anttoni; Guan, Fengying; Holopainen, Markus; Vastaranta, Mikko (2016)
    Decision making on forest resources relies on the precise information that is collected using inventory. There are many different kinds of forest inventory techniques that can be applied depending on the goal, scale, resources and the required accuracy. Most of the forest inventories are based on field sample. Therefore, the accuracy of the forest inventories depends on the quality and quantity of the field sample. Conventionally, field sample has been measured using simple tools. When map is required, remote sensing materials are needed. Terrestrial laser scanning (TLS) provides a measurement technique that can acquire millimeter-level of detail from the surrounding area, which allows rapid, automatic and periodical estimates of many important forest inventory attributes. It is expected that TLS will be operationally used in forest inventories as soon as the appropriate software becomes available, best practices become known and general knowledge of these findings becomes more wide spread. Meanwhile, mobile laser scanning, personal laser scanning, and image-based point clouds became capable of capturing similar terrestrial point cloud data as TLS. This paper reviews the advances of applying TLS in forest inventories, discusses its properties with reference to other related techniques and discusses the future prospects of this technique. (C) 2016 The Authors. Published by Elsevier B.V. on behalf of International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licensesiby-nc-nd/11.0/).