scholarly journals Multisensorial Close-Range Sensing Generates Benefits for Characterization of Managed Scots Pine (Pinus sylvestris L.) Stands

2020 ◽  
Vol 9 (5) ◽  
pp. 309 ◽  
Author(s):  
Tuomas Yrttimaa ◽  
Ninni Saarinen ◽  
Ville Kankare ◽  
Niko Viljanen ◽  
Jari Hynynen ◽  
...  
Keyword(s):  
Pinus Sylvestris ◽  
Scots Pine ◽  
Forest Canopy ◽  
Basal Area ◽  
Point Clouds ◽  
Stem Volume ◽  
Weighted Mean ◽  
Range Sensing ◽  
Close Range

Terrestrial laser scanning (TLS) provides a detailed three-dimensional representation of surrounding forest structures. However, due to close-range hemispherical scanning geometry, the ability of TLS technique to comprehensively characterize all trees, and especially upper parts of forest canopy, is often limited. In this study, we investigated how much forest characterization capacity can be improved in managed Scots pine (Pinus sylvestris L.) stands if TLS point clouds are complemented with photogrammetric point clouds acquired from above the canopy using unmanned aerial vehicle (UAV). In this multisensorial (TLS+UAV) close-range sensing approach, the used UAV point cloud data were considered especially suitable for characterizing the vertical forest structure and improvements were obtained in estimation accuracy of tree height as well as plot-level basal-area weighted mean height (Hg) and mean stem volume (Vmean). Most notably, the root-mean-square-error (RMSE) in Hg improved from 0.8 to 0.58 m and the bias improved from −0.75 to −0.45 m with the multisensorial close-range sensing approach. However, in managed Scots pine stands, the mere TLS also captured the upper parts of the forest canopy rather well. Both approaches were capable of deriving stem number, basal area, Vmean, Hg, and basal area-weighted mean diameter with the relative RMSE less than 5.5% for all the sample plots. Although the multisensorial close-range sensing approach mainly enhanced the characterization of the forest vertical structure in single-species, single-layer forest conditions, representation of more complex forest structures may benefit more from point clouds collected with sensors of different measurement geometries.

scholarly journals Multisensorial Close-Range Sensing Generates Benefits for Characterization of Managed Scots Pine (Pinus sylvestris L.) Stands

2020 ◽  
Author(s):  
Tuomas Yrttimaa ◽  
Ninni Saarinen ◽  
Ville Kankare ◽  
Niko Viljanen ◽  
Jari Hynynen ◽  
...  
Keyword(s):  
Pinus Sylvestris ◽  
Scots Pine ◽  
Forest Structure ◽  
Point Cloud ◽  
Forest Canopy ◽  
Basal Area ◽  
Weighted Mean ◽  
Range Sensing ◽  
Close Range

Terrestrial laser scanning (TLS) provides detailed three-dimensional representation of the surrounding forest structure. However, due to close-range hemispherical scanning geometry, the ability of TLS technique to comprehensively characterize all trees and especially the upper parts of forest canopy is often limited. In this study, we investigated how much forest characterization capacity can be improved in managed Scots pine (Pinus sylvestris L.) stands if TLS point cloud is complemented with a photogrammetric point cloud acquired from above the canopy using unmanned aerial vehicle (UAV). In this multisensorial (TLS+UAV) close-range sensing approach, the used UAV point cloud data was considered feasible especially in characterizing the vertical forest structure and improvements were obtained in estimation accuracy of tree height as well as plot-level basal-area weighted mean height (Hg) and mean stem volume (Vmean). Most notably the root mean square error (RMSE) in Hg improved from 0.88 m to 0.58 m and the bias improved from -0.75 m to -0.45 m with the multisensorial close-range sensing approach. However, in managed Scots pine stands the mere TLS captured also the upper parts of the forest canopy rather well. Both approaches were capable of deriving stem number, basal area, Vmean, Hg and basal area-weighted mean diameter with a relative RMSE less than 5.5% for all of the sample plots. Although the multisensorial close-range sensing approach mainly enhanced characterization of forest vertical structure in single-species, single-layer forest conditions, representation of more complex forest structures may benefit more from point clouds collected with sensors of different measurement geometries.

scholarly journals Characterization of a Lhcb5 cDNA from Scots Pine (Pinus sylvestris)

1994 ◽  
Vol 106 (4) ◽  
pp. 1695-1696 ◽  
Author(s):  
S. Jansson ◽  
P. Gustafsson
Keyword(s):  
Pinus Sylvestris ◽  
Scots Pine

Characterization of the Proteinases Present in Germinating Seeds of Scots Pine, Pinus sylvestris

1978 ◽  
Vol 42 (2) ◽  
pp. 252-256 ◽  
Author(s):  
M. Aulikki SALMIA ◽  
SEIJA A. NYMAN ◽  
JUHANI J. MIKOLA
Keyword(s):  
Pinus Sylvestris ◽  
Scots Pine ◽  
Germinating Seeds

scholarly journals Characterization of morphological units in a small, forested stream using close-range remotely piloted aircraft imagery

2020 ◽  
Vol 8 (4) ◽  
pp. 913-929
Author(s):  
Carina Helm ◽  
Marwan A. Hassan ◽  
David Reid
Keyword(s):  
Spatial Scale ◽  
Forest Canopy ◽  
Morphological Variability ◽  
Morphological Diversity ◽  
Point Clouds ◽  
Flying Height ◽  
Small Width ◽  
Remotely Piloted Aircraft ◽  
Close Range ◽  
Channel Unit

Abstract. Forested, gravel-bed streams possess complex channel morphologies which are difficult to objectively characterize. The spatial scale necessary to adequately capture variability in these streams is often unclear, as channels are governed by irregularly spaced features and episodic processes. This issue is compounded by the high cost and time-consuming nature of field surveys in these complex fluvial environments. In larger streams, remotely piloted aircraft (RPA) have proven to be effective tools for characterizing channels at high resolutions over large spatial extents, but to date their use in small, forested streams with closed forest canopies has been limited. This paper seeks to demonstrate an effective method for classifying channel morphological units in small, forested streams and for providing information on the spatial scale necessary to capture the dominant spatial morphological variability of these channels. This goal was achieved using easily extractable data from close-range RPA imagery collected under the forest canopy (flying height of 5–15 m above ground level; ma.g.l.) in a small (width of 10–15 m) stream along its 3 km of salmon-bearing channel. First, the accuracy and coverage of RPA for extracting channel data were investigated through a subcanopy survey. From these survey data, relevant cross-sectional variables (hydraulic radius, sediment texture, and channel slope) were extracted from high-resolution point clouds and digital elevation models (DEMs) of the channel and used to characterize channel unit morphology using a principal component analysis-clustering (PCA-clustering) technique. Finally, the length scale required to capture dominant morphological variability was investigated from an analysis of morphological diversity along the channel. The results demonstrate that subcanopy RPA surveys provide a viable alternative to traditional ground-based survey approaches for mapping morphological units, with 87 % coverage of the main channel stream bed achieved. The PCA-clustering analysis provided a comparatively objective means of classifying channel unit morphology with a correct classification rate of 85 %. An analysis of the morphological diversity along the surveyed channel indicates that reaches of at least 15 bankfull width equivalents are required to capture the channel's dominant morphological heterogeneity. Altogether, the results provide a precedent for using RPA to characterize the morphology and diversity of forested streams under dense canopies.

scholarly journals Comparison of interferometric and stereo-radargrammetric 3D metrics in mapping of forest resources

2015 ◽  
Vol XL-7/W3 ◽  
pp. 425-431
Author(s):  
K. Karila ◽  
M. Karjalainen ◽  
X. Yu ◽  
M. Vastaranta ◽  
M. Holopainen ◽  
...  
Keyword(s):  
Forest Inventory ◽  
Forest Canopy ◽  
Basal Area ◽  
Tree Height ◽  
Forest Resources ◽  
Canopy Height ◽  
Stem Diameter ◽  
Stem Volume ◽  
Test Plot ◽  
3D Data

Accurate forest resources maps are needed in diverse applications ranging from the local forest management to the global climate change research. In particular, it is important to have tools to map changes in forest resources, which helps us to understand the significance of the forest biomass changes in the global carbon cycle. In the task of mapping changes in forest resources for wide areas, Earth Observing satellites could play the key role. In 2013, an EU/FP7-Space funded project “Advanced_SAR” was started with the main objective to develop novel forest resources mapping methods based on the fusion of satellite based 3D measurements and in-situ field measurements of forests. During the summer 2014, an extensive field surveying campaign was carried out in the Evo test site, Southern Finland. Forest inventory attributes of mean tree height, basal area, mean stem diameter, stem volume, and biomass, were determined for 91 test plots having the size of 32 by 32 meters (1024 m<sup>2</sup>). Simultaneously, a comprehensive set of satellite and airborne data was collected. Satellite data also included a set of TanDEM-X (TDX) and TerraSAR-X (TSX) X-band synthetic aperture radar (SAR) images, suitable for interferometric and stereo-radargrammetric processing to extract 3D elevation data representing the forest canopy. In the present study, we compared the accuracy of TDX InSAR and TSX stereo-radargrammetric derived 3D metrics in forest inventory attribute prediction. First, 3D data were extracted from TDX and TSX images. Then, 3D data were processed as elevations above the ground surface (forest canopy height values) using an accurate Digital Terrain Model (DTM) based on airborne laser scanning survey. Finally, 3D metrics were calculated from the canopy height values for each test plot and the 3D metrics were compared with the field reference data. The Random Forest method was used in the forest inventory attributes prediction. Based on the results InSAR showed slightly better performance in forest attribute (i.e. mean tree height, basal area, mean stem diameter, stem volume, and biomass) prediction than stereo-radargrammetry. The results were 20.1% and 28.6% in relative root mean square error (RMSE) for biomass prediction, for TDX and TSX respectively.

scholarly journals Growth Differences in the Progeny Trials of the Scots Pine (Pinus sylvestris L.)

2009 ◽  
Vol 50 (1) ◽  
pp. 84-97
Author(s):  
Malle Kurm ◽  
Andres Kiviste ◽  
Ursula Kaur ◽  
Tiit Maaten
Keyword(s):  
Pinus Sylvestris ◽  
Scots Pine ◽  
Basal Area ◽  
Data Set ◽  
Mother Tree ◽  
Single Tree ◽  
Plus Tree ◽  
Growth Differences ◽  
Forest District ◽  
Area And Volume

Kasvuomaduste erinevused hariliku männi (Pinus sylvestrisL.) järglaskatsetesThe progeny trials of Scots pine founded in Järvselja Training and Experimental Forest District in 1967 and 1968 by E. Pihelgas were analysed to estimate the dependence of progeny growth variables on mother tree or mother stand origin and age. Our progeny data set consists of 4622 DBH and 486 height measurements of the 41- and 42-year-old progeny trials. In 2008 and in 1995 all trees of the progeny trial were callipered and height of nine sample trees was measured on each plot. The analysis was carried out with the SAS/GLM procedure. It was proved that height of inland-originated progeny stands was significantly higher than height of progeny stands originated from maritime regions. Plus-tree progeny stands exceeded single tree and mixture-of-seeds progeny stands in height, diameter, basal area and volume.

scholarly journals Evaporation from Scots pine (Pinus sylvestris) following natural re-colonisation of the Cairngorm mountains, Scotland

2000 ◽  
Vol 4 (3) ◽  
pp. 451-461 ◽  
Author(s):  
Atul H. Haria ◽  
David J. Price
Keyword(s):  
Land Use ◽  
Soil Moisture ◽  
Water Balance ◽  
Pinus Sylvestris ◽  
Scots Pine ◽  
Forest Canopy ◽  
Physical Structure ◽  
Forest Site ◽  
Natural Forests ◽  
Canopy Interception

Abstract. Recently, changing land-use practices in the uplands of Scotland have resulted in increased re-colonisation of wet heath moorland by natural Scots pine (Pinus sylvestris) woodland. The simple semi-empirical water use model, HYLUC, was used to determine the change in water balance with increasing natural pine colonisation. The model worked well for 1996. However, values of soil moisture deficit simulated by HYLUC diverged significantly from measurements in 1997 when rainfall quantity and intensities were less. Measured interception by the forest canopy (interception by the undergrowth was not measured) was very different from HYLUC simulated values. By changing interception parameters to those optimised against measured canopy interception, HYLUC simulated changing soil moisture deficits better and gave more confidence in the resulting transpiration values. The results showed that natural pine woodland interception may be similar to plantation stands although the physical structure of the natural and plantation forests are different. Though having fewer storage sites for interception in the canopy, the natural pine woodland had greater ventilation and so evaporation of intercepted rainfall was enhanced, especially during low intensity rainfall. To understand the hydrological changes that would result with changing land-use (an expansion of natural forests into the wet heath land), the modelled outputs of the wet heath and mature forest sites were compared. Evaporation, a combination of transpiration and interception, was 41% greater for the forest site than for the wet heath moorland. This may have significant consequences for the rainfall-runoff relationship and consequently for the hydrological response of the catchment as the natural woodland cover increases Keywords: Evaporation; interception; transpiration; water balance; Scots pine; forest

scholarly journals Seoseid puistu juurdekasvu ja koosseisu vahel hariliku männi (Pinus sylvestris L.) enamusega segametsades / Relationships between stand volume growth and composition in mixed stands dominated by Scots Pine (Pinus sylvestris L.)

2011 ◽  
Vol 54 (1) ◽  
pp. 18-27
Author(s):  
Ando Lilleleht
Keyword(s):  
Species Composition ◽  
Pinus Sylvestris ◽  
Scots Pine ◽  
Linear Regression Analysis ◽  
Volume Growth ◽  
Basal Area ◽  
Height Growth ◽  
Forest Growth ◽  
Mixed Stands ◽  
Study Results

Abstract. Relationships between the volume growth of mixed stands and their species composition were analyzed in order to examine the so-called “mixture effect” on stand productivity. The influence of co-species was studied using multiple linear regression analysis. Stand level basal area and height growth models were constructed in order to find out which stand characteristics can be used to describe mixture-effects. The study material originates from the Estonian network of permanent forest growth plots, only stands consisting of mainly (≥ 50% of volume) Scots Pine with Norway spruce and/or Birch spp. as co-species were used. Sample size was 139 5-year measurement periods on 88 plots; stand ages range from 14 to 167 years. The study results indicate that an increasing proportion of birch in the stand causes a negative effect on both basal area and height growth. Spruce seems to be a weaker competitor than other pines as its trend in the model is positive. Also, height growth is more rapid when the mean diameter of spruce is smaller than that of pine. Species composition coefficients for co-species (calculated by standing volume) proved to be the most significant variables that describe stand composition in the models

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