Browsing by Subject "TREE HEIGHT"

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  • Yu, Xiaowei; Hyyppä, Juha; Karjalainen, Mika; Nurminen, Kimmo; Karila, Kirsi; Vastaranta, Mikko; Kankare, Ville; Kaartinen, Harri; Holopainen, Markus; Honkavaara, Eija; Kukko, Antero; Jaakkola, Anttoni; Liang, Xinlian; Wang, Yunsheng; Hyyppä, Hannu; Katoh, Masato (2015)
    It is anticipated that many of the future forest mapping applications will be based on three-dimensional (3D) point clouds. A comparison study was conducted to verify the explanatory power and information contents of several 3D remote sensing data sources on the retrieval of above ground biomass (AGB), stem volume (VOL), basal area (G), basal-area weighted mean diameter (D-g) and Lorey's mean height (H-g) at the plot level, utilizing the following data: synthetic aperture radar (SAR) Interferometry, SAR radargrammetry, satellite-imagery having stereo viewing capability, airborne laser scanning (ALS) with various densities (0.8-6 pulses/m(2)) and aerial stereo imagery. Laser scanning is generally known as the primary source providing a 3D point cloud. However, photogrammetric, radargrammetric and interferometric techniques can be used to produce 3D point clouds from space- and air-borne stereo images. Such an image-based point cloud could be utilized in a similar manner as ALS providing that accurate digital terrain model is available. In this study, the performance of these data sources for providing point cloud data was evaluated with 91 sample plots that were established in Evo, southern Finland within a boreal forest zone and surveyed in 2014 for this comparison. The prediction models were built using random forests technique with features derived from each data sources as independent variables and field measurements of forest attributes as response variable. The relative root mean square errors (RMSEs) varied in the ranges of 4.6% (0.97 m)-13.4% (2.83 m) for H-g, 11.7% (3.0 cm)-20.6% (5.3 cm) for D-g, 14.8% (4.0 m(2)/ha)-25.8% (6.9 m(2)/ha) for G, 15.9% (43.0 m(3)/ha)-31.2% (84.2 m(3)/ha) for VOL and 14.3% (19.2 Mg/ha)-27.5% (37.0 Mg/ha) for AGB, respectively, depending on the data used. Results indicate that ALS data achieved the most accurate estimates for all forest inventory attributes. For image-based 3D data, high-altitude aerial images and WorldView-2 satellite optical image gave similar results for H-g and D-g, which were only slightly worse than those of ALS data. As expected, spaceborne SAR data produced the worst estimates. WorldView-2 satellite data performed well, achieving accuracy comparable to the one with ALS data for G, VOL and AGB estimation. SAR interferometry data seems to contain more information for forest inventory than SAR radargrammetry and reach a better accuracy (relative RMSE decreased from 13.4% to 9.5% for H-g, 20.6% to 19.2% for D-g, 25.8% to 20.9% for G, 31.2% to 22.0% for VOL and 27.5% to 20.7% for AGB, respectively). However, the availability of interferometry data is limited. The results confirmed the high potential of all 3D remote sensing data sources for forest inventory purposes. However, the assumption of using other than ALS data is that there exist a high quality digital terrain model, in our case it was derived from ALS.
  • Domec, Jean-Christophe; Berghoff, Henry; Way, Danielle; Moshelion, Menachem; Palmroth, Sari; Kets, Katre; Huang, Cheng-Wei; Oren, Ram (2019)
    The ability to transport water through tall stems hydraulically limits stomatal conductance (g(s)), thereby constraining photosynthesis and growth. However, some plants are able to minimize this height-related decrease in g(s), regardless of path length. We hypothesized that kudzu (Pueraria lobata) prevents strong declines in g(s) with height through appreciable structural and hydraulic compensative alterations. We observed only a 12% decline in maximum g(s) along 15-m-long stems and were able to model this empirical trend. Increasing resistance with transport distance was not compensated by increasing sapwood-to-leaf-area ratio. Compensating for increasing leaf area by adjusting the driving force would require water potential reaching -1.9 MPa, far below the wilting point (-1.2 MPa). The negative effect of stem length was compensated for by decreasing petiole hydraulic resistance and by increasing stem sapwood area and water storage, with capacitive discharge representing 8-12% of the water flux. In addition, large lateral (petiole, leaves) relative to axial hydraulic resistance helped improve water flow distribution to top leaves. These results indicate that g(s) of distal leaves can be similar to that of basal leaves, provided that resistance is highest in petioles, and sufficient amounts of water storage can be used to subsidize the transpiration stream.
  • Pukkala, Timo; Vauhkonen, Jari; Korhonen, Kari T.; Packalen, Tuula (2021)
    Finnish forest structures vary from even-aged planted forests to two- and multi-storied mixed stands. Also, the range of silvicultural systems in use has increased because thinning from above and continuous cover management are gaining popularity. The data currently available for modelling stand dynamics are insufficient to allow the development of unbiased and reliable models for the simulation of all possible transitions between various current and future stand conditions. Therefore, the models should allow temporal and regional calibration along the accumulation of new information on forest development. If the calibration process is automated, the simulators that use these models constitute a self-Learning system that adapts to the properties of new data on stand dynamics. The current study first developed such a model set for stand dynamics that is technically suitable for simulating the stand development in all stand structures, silvicultural systems and their transitions. The model set consists of individual-tree models for diameter increment and survival and a stand-Level model for ingrowth. The models were based on the permanent sample plots of the 10th and 11th national forest inventories of Finland. Second, a system for calibrating the models based on additional data was presented. This optimization-based system allows different types and degrees of calibration, depending on the intended use of the models and the amount of data available for calibration. The calibration method was demonstrated with two external datasets where a set of sample plots had been measured two times at varying measurement intervals.
  • Yrttimaa, Tuomas; Luoma, Ville; Saarinen, Ninni; Kankare, Ville; Junttila, Samuli; Holopainen, Markus; Hyyppä, Juha; Vastaranta, Mikko (2020)
    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 inquantifying 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 cylindricalcharacteristics 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 foreststands 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 (∆dbh), 44.14–55.49 cm2 for basal area (∆g), and 1.91–4.85 m for tree height (∆h). 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 meandiameter (∆Dg), 0.81–2.26 m for changes in basal area-weighted mean height (∆Hg), 1.40–2.34 m2 /ha for changes in mean basal area (∆G), and 74–193 n/ha for changes in the number of trees per hectare (∆TPH). 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.
  • Hyyppa, Eric; Hyyppa, Juha; Hakala, Teemu; Kukko, Antero; Wulder, Michael A.; White, Joanne C.; Pyorala, Jiri; Yu, Xiaowei; Wang, Yunsheng; Virtanen, Juho-Pekka; Pohjavirta, Onni; Liang, Xinlian; Holopainen, Markus; Kaartinen, Harri (2020)
    Surveying and robotic technologies are converging, offering great potential for robotic-assisted data collection and support for labour intensive surveying activities. From a forest monitoring perspective, there are several technological and operational aspects to address concerning under-canopy flying unmanned airborne vehicles (UAV). To demonstrate this emerging technology, we investigated tree detection and stem curve estimation using laser scanning data obtained with an under-canopy flying UAV. To this end, we mounted a Kaarta Stencil-1 laser scanner with an integrated simultaneous localization and mapping (SLAM) system on board an UAV that was manually piloted with the help of video goggles receiving a live video feed from the onboard camera of the UAV. Using the under-canopy flying UAV, we collected SLAM-corrected point cloud data in a boreal forest on two 32 m x 32 m test sites that were characterized as sparse (n = 42 trees) and obstructed (n = 43 trees), respectively. Novel data processing algorithms were applied for the point clouds in order to detect the stems of individual trees and to extract their stem curves and diameters at breast height (DBH). The estimated tree attributes were compared against highly accurate field reference data that was acquired semi-manually with a multi-scan terrestrial laser scanner (TLS). The proposed method succeeded in detecting 93% of the stems in the sparse plot and 84% of the stems in the obstructed plot. In the sparse plot, the DBH and stem curve estimates had a root-mean-squared error (RMSE) of 0.60 cm (2.2%) and 1.2 cm (5.0%), respectively, whereas the corresponding values for the obstructed plot were 0.92 cm (3.1%) and 1.4 cm (5.2%). By combining the stem curves extracted from the under-canopy UAV laser scanning data with tree heights derived from above-canopy UAV laser scanning data, we computed stem volumes for the detected trees with a relative RMSE of 10.1% in both plots. Thus, the combination of under-canopy and above-canopy UAV laser scanning allowed us to extract the stem volumes with an accuracy comparable to the past best studies based on TLS in boreal forest conditions. Since the stems of several spruces located on the test sites suffered from severe occlusion and could not be detected with the stem-based method, we developed a separate work flow capable of detecting trees with occluded stems. The proposed work flow enabled us to detect 98% of trees in the sparse plot and 93% of the trees in the obstructed plot with a 100% correction level in both plots. A key benefit provided by the under-canopy UAV laser scanner is the short period of time required for data collection, currently demonstrated to be much faster than the time required for field measurements and TLS. The quality of the measurements acquired with the under-canopy flying UAV combined with the demonstrated efficiency indicates operational potential for supporting fast and accurate forest resource inventories.
  • Pyörälä, Jiri; Saarinen, Ninni; Kankare, Ville; Coops, Nicholas C.; Liang, Xinlian; Wang, Yunsheng; Holopainen, Markus; Hyyppä, Juha; Vastaranta, Mikko (2019)
    Information on wood properties is crucial in estimating wood quality and forest biomass and thus developing the precision and sustainability of forest management and use. However, wood properties are highly variable between and within trees due to the complexity of wood formation. Therefore, tree-specific field references and spatially transferable models are required to capture the variability of wood quality and forest biomass at multiple scales, entailing high-resolution terrestrial and aerial remote sensing methods. Here, we aimed at identifying select tree traits that indicate wood properties (i.e. wood quality indicators) with a combination of terrestrial laser scanning (TLS) and airborne laser scanning (ALS) in an examination of 27 even-aged, managed Scots pine (Pinus sylvestris L.) stands in southern Finland. We derived the wood quality indicators from tree models sampled systematically from TLS data and built prediction models with respect to individual crown features delineated from ALS data. The models were incapable of predicting explicit branching parameters (height of the lowest dead branch R2 = 0.25, maximum branch diameter R2 = 0.03) but were suited to predicting stem and crown dimensions from stand, tree, and competition factors (diameter at breast height and sawlog volume R2 = 0.5, and live crown base height R2 = 0.4). We were able to identify the effect of canopy closure on crown longevity and stem growth, which are pivotal to the variability of several wood properties in managed forests. We discussed how the fusions of high-resolution remote sensing methods may be used to enhance sustainable management and use of natural resources in the changing environment.
  • Liu, Che; Hölttä, Teemu; Tian, Xianglin; Berninger, Frank; Mäkelä, Annikki (2020)
    Age-related effects on whole-tree hydraulics are one of the key challenges to better predicting the production and growth of old-growth forests. Previous models have described the optimal state of stomatal behaviour, and field studies have implied on age/size-induced trends in tree ecophysiology related to hydraulics. On these bases, we built a Bayesian hierarchical model to link sap flow density and drivers of transpiration directly. The model included parameters with physiological meanings and accounted for variations in leaf-sapwood area ratio and the time lag between sap flow and transpiration. The model well-simulated the daily pattern of sap flow density and the variation between tree age groups. The results of parameterization show that (1) the usually higher stomatal conductance in young than old trees during mid-summer was mainly because the sap flow of young trees were more activated at low to medium light intensity, and (2) leaf-sapwood area ratio linearly decreased while time lag linearly increased with increasing tree height. Uncertainty partitioning and cross-validation, respectively, indicated a reliable and fairly robust parameter estimation. The model performance may be further improved by higher data quality and more process-based expressions of the internal dynamics of trees.