Articles containing the keyword 'stand characteristics'

The purpose of this study was to test the benefits of a forest site quality map, when applying satellite image-based forest inventory. By combining field sample plot data from national forest inventories with satellite imagery and forest site quality data, it is possible to estimate forest stand characteristics with higher accuracy for smaller areas. The reliability of the estimates was evaluated using the data from a stand-wise survey for area sizes ranging from 0.06 ha to 300 ha. When the mean volume was estimated, a relative error of 14 per cent was obtained for areas of 50 ha; for areas of 30 ha the corresponding figure was below 20 per cent. The relative gain in interpretation accuracy, when including the forest site quality information, ranged between 1 and 6 per cent. The advantage increased according to the size of the target area. The forest site quality map had the effect of decreasing the relative error in Norway spruce (Picea abies) volume estimations, but it did not contribute to Scots pine (Pinus sylvestris) volume estimation procedure.

• Tokola, E-mail: tt@mm.unknown
• Heikkilä, E-mail: jh@mm.unknown

This paper deals with the testing of dynamic stratification for estimating stand level forest characteristics (basal areas, mean diameter, mean height and mean age) for a 117 ha study areas in Finland. The results do not show possibilities to achieve more accurate estimates using only Landsat TM principal components as auxiliary data opposed to static stratification. It was found that in dynamic stratification non-measured observations should be assigned the mean characteristics of the measured observations that belong to the same cube (class) instead of stratification variable classes until a certain limit. If only one principal component is used the number of classes has, however, little influence. Low field values are overestimated and high values underestimated.

The only successful results were obtained using two variables of different origin – the qualitative development stage class and the quantitative 1st principal component. The lowest root mean square error in estimating basal area was 6.40 m²/ha, mean diameter 3.34 cm, mean height 2.65 m and mean age 14.06 years. This increase of stratification accuracy is mainly resulted by the use of development stage class as an auxiliary variable.

• Mozgeris, E-mail: gm@mm.unknown

A method for using satellite data in forest inventories and updating is described and tested. The stand characteristics estimated by the method showed high correlation with the same characteristics measured in the field. The correlation coefficients for volume, age and mean height were about 0.85. It seems that the method is applicable to practical forestry. Extensive work in programming, however, is required.

The PDF includes an abstract in Finnish.

• Poso, E-mail: sp@mm.unknown
• Paananen, E-mail: rp@mm.unknown
• Similä, E-mail: ms@mm.unknown

The effect of competition on the radial growth of Scots pine (Pinus sylvestris L.) was studied in three naturally regenerated stands located in North Karelia, Finland. The competition situation of an individual tree was described with various competition indices which depended on the sizes and distances from the neighbouring trees. One competition index explained about 50% of the variation in 5-year radial growth in one stand. If all stands were combined, one index explained 43.5%, two indices 48.9% and three indices 51.2% of the variation. In one stand, the best competition indices accounted for about 20% of that variation which could not be explained by tree diameter. If all three stands were combined, the best index explained 11% of the residual variation. About 40% of the variation in 5-year radial growth could not be explained by the diameter and competition indices.
The PDF includes an abstract in Finnish.

• Pukkala, E-mail: tp@mm.unknown
• Kolström, E-mail: tk@mm.unknown

Vegetation data collected from a random sample of mature forest stands representing mesic upland forest sites in Southern Finland were analysed and classified using two-way indicator species analysis (TWINSPAN). The variation of some characteristics of the tree stand and soil fertility between the produced vegetation units were analysed statistically.

Both the species list and the sample list arranged by TWINSPAN reflects the overall site fertility considerably well. The results are in agreement with the main division of mesic forest sites in the Finnish forest site type classification: vegetation units which can be assigned to the Oxalis-Myrtillus site type are clearly separated from the remaining units, and the overall site fertility indicates a statistically significant difference. The within-type variation in the vegetation composition in the Oxalis-Myrtillus site type reflects the variation in site fertility, whereas the within-type variation in the Myrtillus site type is mainly caused by the tree stand factor.

The PDF includes a summary in Finnish.

• Kuusipalo, E-mail: jk@mm.unknown

The aim of the study was to determine which characteristics of tree stands could be used in urban noise control and to develop guidelines for practical urban forestry. The attenuation of artificially produced noise was measured in various types of stands. The effect of tree stands on noise attenuation has been analysed using a model based on the physics of sound propagation.

The results show that the excess noise attenuation caused by trees can be in good situations 60% measured in energy units, compared with the attenuation caused by geometric spreading. This is 5–8 dB. The total amount of needles, leaves and branches of a stand proved to be the most important factors in noise attenuation. However, the density and height of a stand had rather high value in predicting the behaviour of noise in tree stands. Based on multiple regression between noise attenuation and tree species composition, density and height of a stand it was developed the nomograms with which the noise level at a certain point can be predicted when the tree stand characteristics, the distance and the noise level of the noise source are known and on the opposite way.

The PDF includes a summary in Finnish.

• Kellomäki, E-mail: sk@mm.unknown
• Haapanen, E-mail: ah@mm.unknown
• Salonen, E-mail: hs@mm.unknown

The purpose of this study was that of providing a long-term timber production model (Kilkki and Pökkälä 1975) with growing stock models. The paper is divided into two parts; the first is concerned with generation of the stand data through Monte-Carlo simulation. The growing stock of each stand was described by a DBH-height distribution. The necessary information on the relationships between the stand characteristics was derived from sample plots measured in the national forest inventory of Finland. A total of 1,500 Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) H. Karst), and birch (Betula sp.) stands, each comprising 100 trees were provided by simulation.

In the second part, models predicting the form factor, timber assortment distribution, and value of the growing stock were derived through regression analysis for each species of tree. The predicting variables included the form factor of the basal area median tree, basal area median diameter, and height in the form factor models. In the timber assortment and value models, the only predicting variable was the volume of the basal area median tree. The Matchcurve-technique (Jensen 1973) was employed in derivation of the regression models.

The PDF includes a summary in English.

• Kilkki, E-mail: pk@mm.unknown
• Siitonen, E-mail: ms@mm.unknown

• Siipilehto, Finnish Forest Research Institute, Vantaa Research Unit, P.O. Box 18, FI-01301 Vantaa, Finland E-mail: jouni.siipilehto@metla.fi
• Mehtätalo, University of Eastern Finland, School of Computing, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: lauri.mehtatalo@uef.fi

• Siipilehto, Finnish Forest Research Institute, Vantaa Research Unit, P.O. Box 18, FI-01301 Vantaa, Finland E-mail: jouni.siipilehto@metla.fi

• Siipilehto, Finnish Forest Research Institute, P.O. Box 18, FI-01301 Vantaa, Finland E-mail: jouni.siipilehto@metla.fi

• Malinen, University of Joensuu, Faculty of Forestry, P.O. Box 111, FIN-80101 Joensuu, Finland E-mail: jukka.malinen@joensuu.fi