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Articles containing the keyword 'spatial distribution'.

Category: Research article

article id 7743, category Research article
Sakari Tuominen, Timo Pitkänen, Andras Balazs, Annika Kangas. (2017). Improving Finnish Multi-Source National Forest Inventory by 3D aerial imaging. Silva Fennica vol. 51 no. 4 article id 7743. https://doi.org/10.14214/sf.7743
Highlights: 3D aerial imaging provides a feasible method for estimating forest variables in the form of thematic maps in large area inventories; Photogrammetric 3D data based on aerial imagery that was originally acquired for orthomosaic production was tested in estimating stand variables; Photogrammetric 3D data highly improved the accuracy of forest estimates compared to traditional 2D remote sensing imagery.

Optical 2D remote sensing techniques such as aerial photographing and satellite imaging have been used in forest inventory for a long time. During the last 15 years, airborne laser scanning (ALS) has been adopted in many countries for the estimation of forest attributes at stand and sub-stand levels. Compared to optical remote sensing data sources, ALS data are particularly well-suited for the estimation of forest attributes related to the physical dimensions of trees due to its 3D information. Similar to ALS, it is possible to derive a 3D forest canopy model based on aerial imagery using digital aerial photogrammetry. In this study, we compared the accuracy and spatial characteristics of 2D satellite and aerial imagery as well as 3D ALS and photogrammetric remote sensing data in the estimation of forest inventory variables using k-NN imputation and 2469 National Forest Inventory (NFI) sample plots in a study area covering approximately 5800 km2. Both 2D data were very close to each other in terms of accuracy, as were both the 3D materials. On the other hand, the difference between the 2D and 3D materials was very clear. The 3D data produce a map where the hotspots of volume, for instance, are much clearer than with 2D remote sensing imagery. The spatial correlation in the map produced with 2D data shows a lower short-range correlation, but the correlations approach the same level after 200 meters. The difference may be of importance, for instance, when analyzing the efficiency of different sampling designs and when estimating harvesting potential.

  • Tuominen, Natural Resources Institute Finland (Luke), Economics and Society, P.O. Box 2, FI-00791 Helsinki, Finland ORCID ID:E-mail: sakari.tuominen@luke.fi (email)
  • Pitkänen, Natural Resources Institute Finland (Luke), Economics and Society, P.O. Box 2, FI-00791 Helsinki, Finland ORCID ID:E-mail: timo.p.pitkanen@luke.fi
  • Balazs, Natural Resources Institute Finland (Luke), Economics and Society, P.O. Box 2, FI-00791 Helsinki, Finland ORCID ID:E-mail: andras.balazs@luke.fi
  • Kangas, Natural Resources Institute Finland (Luke), Economics and Society, P.O. Box 68, FI-80101 Joensuu, Finland ORCID ID:E-mail: Annika.Kangas@luke.fi
article id 306, category Research article
Niina Tanskanen, Hannu Ilvesniemi. (2007). Spatial distribution of fine roots at ploughed Norway spruce forest sites. Silva Fennica vol. 41 no. 1 article id 306. https://doi.org/10.14214/sf.306
We examined the spatial distribution of fine roots at two forest sites that were ploughed 20 (site K1) and 33 years (site K2) before sampling and planted with Norway spruce (Picea abies (L.) Karst.) seedlings. Soil core samples were taken from the tilt and beneath the tilt, the furrow and the intermediate undisturbed soil to a depth of 0.4 m for fine root biomass, length and necromass determinations. Norway spruce fine roots were found throughout the ploughed forest sites. The fine roots were, however, unevenly distributed: the fine root biomass was highest in the tilt (624 and 452 g m–2 at sites K1 and K2, respectively) and lowest in the undisturbed soil at site K1 (79 g m–2) and in the furrow at site K2 (145 g m–2). The estimated average fine root biomass at the ploughed forest sites (268 and 248 g m–2 at sites K1 and K2, respectively) was, however, similar to those presented in other studies concerning sites that had not been ploughed. In the tilt, a substantial proportion of the fine roots was in the inverted mineral soil horizons and in the new organic horizon above the tilt. Consistent with the fine root biomass findings, the Norway spruce necromass was highest in the tilt but the vertical distribution of the dead roots was different: the necromass was highest in the buried OBT horizon. The results of this study suggest that at the ploughed forest sites, a substantial part of Norway spruce nutrient and water uptake occured in the tilt during the first 20 or 33 years after plantation.
  • Tanskanen, Department of Forest Ecology, P.O. Box 27, FI-00014 University of Helsinki, Finland ORCID ID:E-mail: niina.tanskanen@helsinki.fi (email)
  • Ilvesniemi, Finnish Forest Research Institute, P.O. Box 18, FI-01301 Vantaa, Finland ORCID ID:E-mail:
article id 562, category Research article
Tero Kokkila, Annikki Mäkelä, Eero Nikinmaa. (2002). A method for generating stand structures using Gibbs marked point process. Silva Fennica vol. 36 no. 1 article id 562. https://doi.org/10.14214/sf.562
Stand growth modelling based on single tree responses to their surroundings requires a description of the spatial structure of a stand. While such detailed information is rarely available from field measurements, a method to create it from more general stand variables is needed. A marked Gibbs point potential theory combined with Markov chain Monte Carlo (MCMC) random process was used to create a spatial configuration for any given number of trees. The trees are considered as charges rejecting each other and building ‘potential energy’. As an analogue of the potential energy in physical systems, the potential of a stand is defined in terms of size-dependent tree-to-tree interactions that can be thought of as related to resource depletion and competition. The idea that bigger trees induce larger potentials brings 3-dimensional effects into the system. Any feasible spatial structure is a state of the system, and the related potential can be calculated. The probability that a certain state occurs is assumed to be a decreasing function of its potential. Because more regular structures have lower potentials, by adjusting the steepness of the probability distribution the spatial structure can be allowed to have a lot of randomness (naturally regenerated stands) or forced to be very regular (planted stands). The MCMC algorithm is a numerical method of finding stand configurations that correspond to the expected level of the potential, given the size distribution of trees and the shape of the probability density function. The method also allows us to take into account spatial variation in the terrain. Some spots can be defined to have lower basic potential than others (ditch, planting furrow, etc.) in order to create areas of higher than average stocking density. A preliminary test of the method was conducted on two measured stands. The results suggest that the method could provide an efficient and flexible means of mimicking variable stand structures.
  • Kokkila, University of Helsinki, Department of Forest Ecology, P.O. Box 27, FIN-00014 Helsingin yliopisto, Finland ORCID ID:E-mail: tero.kokkila@helsinki.fi (email)
  • Mäkelä, University of Helsinki, Department of Forest Ecology, P.O. Box 27, FIN-00014 Helsingin yliopisto, Finland ORCID ID:E-mail:
  • Nikinmaa, University of Helsinki, Department of Forest Ecology, P.O. Box 27, FIN-00014 Helsingin yliopisto, Finland ORCID ID:E-mail:

Category: Article

article id 5449, category Article
Timo Pukkala, Taneli Kolström. (1991). Effect of spatial pattern of trees on the growth of Norway spruce stand. Silva Fennica vol. 25 no. 3 article id 5449. https://doi.org/10.14214/sf.a15603

The simulation model consists of a method to generate theoretical Norway spruce (Picea abies (L.) H. Karst.) stands, and a spatial growth model to predict the growth of these stands. The stand generation procedure first predicts the tree diameters from a few stand characteristics and from tree locations. Tree age and height are predicted using spatial models. Spatial growth models were made for both diameter growth and basal area growth. Past growth was used as a predictor in one pair of models and omitted in another pair. The stand generation method and the growth models were utilized in studying the effect of tree arrangement and thinning method on the growth of a Norway spruce stand.

The PDF includes an abstract in Finnish.

  • Pukkala, ORCID ID:E-mail:
  • Kolström, ORCID ID:E-mail:
article id 5376, category Article
Timo Pukkala. (1989). Predicting diameter growth in even-aged Scots pine stands with a spatial and non-spatial model. Silva Fennica vol. 23 no. 2 article id 5376. https://doi.org/10.14214/sf.a15533

The single tree growth models presented in this study were based on about 4,000 trees measured in 50 even-aged Scots pine (Pinus sylvestris L.) sample plots with varying density, spatial pattern of trees and stand age. Predictors that used information about tree locations decreased the relative standard error of estimate by 10 percentage points (15%), if past growth was not used as a predictor, and about 15 percentage points (30%) when past growth was one of the predictors. When ranked according to the degree of determination, the best growth models were obtained for the basal area increment, the next best for relative growth, and the poorest for diameter increment. The past growth decreased the relative standard error of estimate by 15–20 percentage points, but did not make the spatial predictors unnecessary. The degree of determination of the spatial basal area growth model was almost 80% if the past growth was unknown and almost 90% if the past growth was known. Variables that described the amount of removed competition did not improve the growth models.

The PDF includes an abstract in Finnish.

  • Pukkala, ORCID ID:E-mail:
article id 5375, category Article
Timo Pukkala. (1989). Prediction of tree diameter and height in a Scots pine stand as a function of the spatial pattern of trees. Silva Fennica vol. 23 no. 2 article id 5375. https://doi.org/10.14214/sf.a15532

The study presents two methods of predicting tree dimensions in a Scots pine (Pinus sylvestris L.) stand if only the location of trees is known. The first method predicts the tree diameter from the spatial location of neighbours. In the second method the diameter distribution of a subarea is estimated from the local stand density. This distribution is then sampled to obtain diameters. In both methods the tree height is predicted with a spatial model on the basis of diameters and locations of trees. The main purpose of the presented models is to generate realistic stands for simulation studies.

The PDF includes an abstract in Finnish.

  • Pukkala, ORCID ID:E-mail:
article id 5338, category Article
Timo Pukkala. (1988). Effect of spatial distribution of trees on the volume increment of a young Scots pine stand. Silva Fennica vol. 22 no. 1 article id 5338. https://doi.org/10.14214/sf.a15495

The effect of grouping on 5-year old volume increment was studied by a simulation technique using spatial growth models estimated in Scots pine (Pinus sylvestris L.) stands in the phase of the first commercial thinning. A total of 24 model stands were regenerated by applying 12 spatial processes for two different diameter distributions. In addition to model stands, 6 different thinnings were simulated in two real stands. The clustering of trees was described with Fisher’s grouping index and by estimating the relative interception of diffuse radiation. In model stands with constant diameter distribution the correlation between the grouping index and volume increment ranged from -0.81 to -0.91. The correlation between volume increment and interception was 0.81–0.83 with one diameter distribution and 0.70 if both distributions were combined. In one thinned stand the correlation between the growth estimate and grouping index varied between -0.33 and 0.76. The correlation between interception and growth was about 0.30 in one stand and 0.72 if both stands were combined. Small irregularities do not decrease the volume production of a young Scots pine stand, but if the clustering is considerable or there are reasonably wide harvest strips, growth will be reduced by 10–20%.

The PDF includes a summary in Finnish.

  • Pukkala, ORCID ID:E-mail:
article id 5235, category Article
Pekka Kilkki, Tapani Pohjola, Eljas Pohtila. (1985). Puiden ryhmittäisyyden huomioonottaminen harvennusmalleissa. Silva Fennica vol. 19 no. 2 article id 5235. https://doi.org/10.14214/sf.a15414
English title: Use of the spatial distribution of trees in thinning models.

Thinning models are generally based on the density of the stand measured by the average basal area per hectare, for instance. These models are handicapped by the uneven structure of the stands. In uneven stands the averages are inadequate indicators for the need and amount of thinnings.

Small relascope plots were tested in the measurement of the spatial distribution of trees and in the determination of the need and amount of thinnings. The thinning quantity was determined as the difference between the actual distribution of the relascope plots into basal area classes and the ideal distribution after thinning. Sequential sampling was used in the derivation of the decision equations. A respective BASIC-program for a programmable pocket calculator is given.

The PDF includes a summary in English.

  • Kilkki, ORCID ID:E-mail:
  • Pohjola, ORCID ID:E-mail:
  • Pohtila, ORCID ID:E-mail:

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