Kalle Eerikäinen

Predicting the height–diameter pattern of planted Pinus kesiya stands in Zambia and Zimbabwe

Abstract The aim of the study was to define and analyse a prediction model for the relationship between tree height and diameter of Pinus kesiya (Royle ex Gordon) grown in the forest plantations of Zambia and Zimbabwe. The modelling was based on an equation of the power type. The development of the height–diameter pattern was assumed to be dependent on both tree size and stand characteristics. The tree diameter at breast height, stand age, dominant height and diameter were used as predictors of the tree height. Due to the spatially hierarchical (stands, trees) and temporal (measurement occasions) correlation structures in the data, the basic assumption about noncorrelated error terms did not hold. Therefore, the generalised least squares method was used in the parameter estimation of the random parameter model. In model applications, the development of the height–diameter pattern is predicted with the parameters of the fixed model part. The variance estimates for the random stand, measurement and tree effects can be used in model calibration by applying the standard linear prediction theory. These results lead to the recommendation that the power type of model be used as the predictor of the height–diameter relationship of P. kesiya stands in the tree plantations of southeastern Africa.

Using airborne laser scanning data for detecting canopy gaps and their understory type in mature boreal forest

Abstract• IntroductionCanopy gap dynamics in old-growth boreal forests is a result of tree mortality caused by insects, diseases, or meteorological phenomena. Canopy gaps improve the possibilities of natural regeneration, and concentrations of decomposed deadwood are often found in these natural openings, which provide specific habitats for many deadwood-dependent species and organisms.• MethodsDetailed monitoring setups for canopy gaps have been difficult to organize because of the expense of conventional field inventory techniques. Using three-dimensional airborne laser scanning (ALS), canopy gaps can be detected and analyzed even over large sample areas.• ResultsIn this study, we show how differences between the canopy gaps of seminatural and managed forests can be determined and how canopy gaps can be categorized using ALS data because the ALS characteristics reflect the variation of vertical structure due to different vegetation or deadwood layers in the canopy gaps.• ConclusionThe study show promising results on the applicability of ALS data for the automatic identification of canopy gap types and detection of indirect indicator characteristics usable for assessing the naturalness of boreal forests. Moreover, our method bases on the vertical distribution of laser pulses characterizing the vegetation layer, and it can therefore be applied to other vegetation zones where the ALS is applicable.

Ingrowth, survival and height growth of small trees in uneven-aged Picea abies stands in southern Finland

The purpose of the study was to analyse height growth, mortality, and ingrowth of individual small-sized trees in uneven-aged spruce-dominated stands. It was based on experimental data from 16 stands for a 15-year observation period including four measurements with a 5-year interval. In the data of this study, the heights of small-sized trees varied from 0.1 to about 9 m. Results showed that the growth of small trees was rather slow, particularly in the smallest size classes. With average growth rates it would take about 60 years for a freshly emerged spruce germinant to achieve 1.3 m in height. The stand density, site quality and selection cuttings affected the growth of small-sized spruces. Average five-year mortality rates for spruce, birch and pine were 17.0%, 40.9% and 33.9%, respectively. Annual ingrowth rates with the threshold height of 1.3 m for the three species were on average 30.4, 2.8 and less than 0.1 trees per hectare, respectively. Even if, a selection cutting of modest intensity (25% of basal area removed on average) seemed to have accelerated the growth of small spruces, it is recommended that more intensive harvestings be applied to enhance the survival and growth of small spruces. It is also concluded that shade intolerant species like birch and pine do not seem to be capable of developing into viable undergrowth in spruce selection stands with their current levels of stand density.

Detection of Aspens Using High Resolution Aerial Laser Scanning Data and Digital Aerial Images

The aim was to use high resolution Aerial Laser Scanning (ALS) data and aerial images to detect European aspen (Populus tremula L.) from among other deciduous trees. The field data consisted of 14 sample plots of 30 m × 30 m size located in the Koli National Park in the North Karelia, Eastern Finland. A Canopy Height Model (CHM) was interpolated from the ALS data with a pulse density of 3.86/m2, low-pass filtered using Height-Based Filtering (HBF) and binarized to create the mask needed to separate the ground pixels from the canopy pixels within individual areas. Watershed segmentation was applied to the low-pass filtered CHM in order to create preliminary canopy segments, from which the non-canopy elements were extracted to obtain the final canopy segmentation, i.e. the ground mask was analysed against the canopy mask. A manual classification of aerial images was employed to separate the canopy segments of deciduous trees from those of coniferous trees. Finally, linear discriminant analysis was applied to the correctly classified canopy segments of deciduous trees to classify them into segments belonging to aspen and those belonging to other deciduous trees. The independent variables used in the classification were obtained from the first pulse ALS point data. The accuracy of discrimination between aspen and other deciduous trees was 78.6%. The independent variables in the classification function were the proportion of vegetation hits, the standard deviation of in pulse heights, accumulated intensity at the 90th percentile and the proportion of laser points reflected at the 60th height percentile. The accuracy of classification corresponded to the validation results of earlier ALS-based studies on the classification of individual deciduous trees to tree species.

Modeling Forest Regeneration

The aim of this chapter is to review different approaches for simulating forest development in regeneration modeling. The features, shortcomings, further needs and trends of regeneration modeling are presented and discussed in the context of mechanistic, gap, statistical and nonparametric forest models. The data requirements are also described. Special emphasis is put on supplying information for modelers applying individual-tree models in uneven-aged stands.

Diameter distribution, stem volume and stem quality models for grey alder (Alnus incana) in eastern Finland

Stand-level predictions of basal-areadiameter distributions, height, positions of lowestdead and live branches and stem-rot are provided forgrey alder in eastern Finland. The usability of modelswas tested by calculating the accuracy of predictedvolume characteristics. The data were collected from 33stands situated in the provinces of North Karelia andNorth Savo in eastern Finland. These stands wereregenerated naturally, but some have been managed. Oneto three angle-count sample plots were placedsystematically in each stand using a 1 m2 ha−1 basal-area factor. The models can beapplied in two settings: tree diameters are eithermeasured or not. The prediction of branch heightcharacteristics, especially height to the lowest deadbranch, proved problematic due to weak correlationsbetween these characteristics and other treedimensions. Compared to previous studies it was foundthat stem-rot was higher in grey alder than in sprucebut lower than in white birch.

A percentile based basal area diameter distribution model for predicting the stand development of Pinus kesiya plantations in Zambia and Zimbabwe

The aim of the study was to model the development of the basal area diameter distribution of Pinus kesiya (Royle ex Gordon) stands in Zambian and Zimbabwean forest plantations. The development of stand mean characteristics and basal area diameter distributions are predicted using a combination of a simultaneous yield model (SYM) for stand characteristics and models for the basal area diameter distribution. The stand basal area diameter distribution was calculated from prediction and projection models for diameters at selected percentile points of the basal area, i.e. the percentile based distribution (PBD) model was applied. The models for the percentiles formed a system of equations. Earlier models were used to construct a simulator, which was used in validity tests. According to the reliability tests of total stand volume predictions, the accuracy of the PBD model is comparable to the SYM model and better than the Weibull model, which was used as a reference method for the PBD model. However, the PBD model provides a more detailed description of the stand structure and its development than the SYM model. The models of this study may be flexibly used in yield predictions of P. kesiya plantations in Zambia and Zimbabwe.

Airborne Laser Scanning for the Site Type Identification of Mature Boreal Forest Stands

In Finland, forest site types are used to assess the need of silvicultural operations and the growth potential of the forests and, therefore, provide important inventory information. This study introduces airborne laser scanner (ALS) data and the k-NN classifier data analysis technique applicable to the site quality assessment of mature forests. Both the echo height and the intensity value percentiles of different echo types of ALS data were used in the analysis. The data are of 274 mature forest stands of different sizes, belonging to five forest site types, varying from very fertile to poor forests, in Koli National Park, eastern Finland. The k-NN classifier was applied with values of k varying from 1 to 5. The best overall classification accuracy achieved for all the forest site types and for a single type, were 58% and 73%, respectively. The conclusion is that when conducting large-scale forest inventories ALS-data based analysis would be a useful technology for the identification of mature boreal site types. However, the technique could still be improved and further studies are needed to ensure its applicability under different local conditions and with data representing earlier stages of stand development.

Models for predicting tree and stand development on larch plantations in Hallormsstaður, Iceland

The aim was to model the growth of Siberian larch (Larix sibirica Ledeb.) and Russian larch (Larix sukaczewii Dyl., syn. L. sibirica var. sukaczewii) plantations in Hallormsstaður, Iceland. The field inventory was carried out in eastern Iceland in June 2006. Models were constructed for predicting dominant height, total tree height and 5-year diameter increment. Several linear and non-linear forms of models were tested in preliminary analyses to find the equations that fitted the modelled characteristics best. Due to the spatially hierarchical correlation structure of the data (stands, plots and trees), the assumption of non-correlated error terms did not hold. Therefore, a random parameter modelling approach was adopted using mixed models when the estimates obtained for the random effects were statistically significant. The variance estimates for the random effects can be further used to calibrate the models. The models generated here performed well with independent test data and were consistent with the forest growth theory. They can be used to evaluate site quality and to estimate the growth and yield of larch stands in eastern Iceland in connection with forest planning.

Utilizing a Multi-Source Forest Inventory Technique, MODIS Data and Landsat TM Images in the Production of Forest Cover and Volume Maps for the Terai Physiographic Zone in Nepal

An approach based on the nearest neighbors techniques is presented for producing thematic maps of forest cover (forest/non-forest) and total stand volume for the Terai region in southern Nepal. To create the forest cover map, we used a combination of Landsat TM satellite data and visual interpretation data, i.e., a sample grid of visual interpretation plots for which we obtained the land use classification according to the FAO standard. These visual interpretation plots together with the field plots for volume mapping originate from an operative forest inventory project, i.e., the Forest Resource Assessment of Nepal (FRA Nepal) project. The field plots were also used in checking the classification accuracy. MODIS satellite data were used as a reference in a local correction approach conducted for the relative calibration of Landsat TM images. This study applied a non-parametric k-nearest neighbor technique (k-NN) to the forest cover and volume mapping. A tree height prediction approach based on a nonlinear, mixed-effects (NLME) modeling procedure is presented in the Appendix. The MODIS image data performed well as reference data for the calibration approach applied to make the Landsat image mosaic. The agreement between the forest cover map and the field observed values of forest cover was substantial in Western Terai (KHAT 0.745) and strong in Eastern Terai (KHAT 0.825). The forest cover and volume maps that were estimated using the k-NN method and the inventory data from the FRA Nepal project are already appropriate and valuable data for research purposes and for the planning of forthcoming forest inventories. Adaptation of the methods and techniques was carried out using Open Source software tools.