Quality Assessment of a Forest Inventory Based on Airborne Laser Scanning

In this study, a quality assessment method based on sampling of primary laser inventory units (microsegments) was analysed. The accuracy of a laser inventory carried out in Kuhmo was analysed as a case study. Field sample plots were measured on the sampled microsegments in the Kuhmo inventory area. Two main questions were considered. Did the ALS based inventory meet the accuracy requirements set for the provider and how should a reliable, cost-efficient and independent quality assessment be undertaken. The agreement between control measurement and ALS based inventory was analysed in four ways: 1) The root mean squared errors (RMSEs) and bias were calculated. 2) Scatter plots with 95% confidence intervals were plotted and the placing of identity lines was checked. 3) Bland-Altman plots were drawn so that the mean difference of attributes between the control method and ALS-method was calculated and plotted against average value of attributes. 4) The tolerance limits were defined and combined with Bland-Altman plots. The RMSE values were compared to a reference study from which the accuracy requirements had been set to the service provider. The accuracy requirements in Kuhmo were achieved, however comparison of RMSE values proved to be difficult. Field control measurements are costly and time-consuming, but they are considered to be robust. However, control measurements might include errors, which are difficult to take into account. Using the Bland-Altman plots none of the compared methods are considered to be completely exact, so this offers a fair way to interpret results of assessment. The tolerance limits to be set on order combined with Bland-Altman plots were suggested to be taken in practise. In addition, bias should be calculated for total area. Some other approaches for quality control were briefly examined. No method was found to fulfil all the required demands of statistical reliability, cost-efficiency, time efficiency, simplicity and speed of implementation. Some benefits and shortcomings of the studied methods were discussed.

Dynamic Factor Models and Forecasting Finnish Macroeconomic Variables

In recent years, thanks to developments in information technology, large-dimensional datasets have been increasingly available. Researchers now have access to thousands of economic series and the information contained in them can be used to create accurate forecasts and to test economic theories. To exploit this large amount of information, researchers and policymakers need an appropriate econometric model.Usual time series models, vector autoregression for example, cannot incorporate more than a few variables. There are two ways to solve this problem: use variable selection procedures or gather the information contained in the series to create an index model. This thesis focuses on one of the most widespread index model, the dynamic factor model (the theory behind this model, based on previous literature, is the core of the first part of this study), and its use in forecasting Finnish macroeconomic indicators (which is the focus of the second part of the thesis). In particular, I forecast economic activity indicators (e.g. GDP) and price indicators (e.g. consumer price index), from 3 large Finnish datasets. The first dataset contains a large series of aggregated data obtained from the Statistics Finland database. The second dataset is composed by economic indicators from Bank of Finland. The last dataset is formed by disaggregated data from Statistic Finland, which I call micro dataset. The forecasts are computed following a two steps procedure: in the first step I estimate a set of common factors from the original dataset. The second step consists in formulating forecasting equations including the factors extracted previously. The predictions are evaluated using relative mean squared forecast error, where the benchmark model is a univariate autoregressive model. The results are dataset-dependent. The forecasts based on factor models are very accurate for the first dataset (the Statistics Finland one), while they are considerably worse for the Bank of Finland dataset. The forecasts derived from the micro dataset are still good, but less accurate than the ones obtained in the first case. This work leads to multiple research developments. The results here obtained can be replicated for longer datasets. The non-aggregated data can be represented in an even more disaggregated form (firm level). Finally, the use of the micro data, one of the major contributions of this thesis, can be useful in the imputation of missing values and the creation of flash estimates of macroeconomic indicator (nowcasting).

Understorey vegetation as an indicator of forest site potential in Southern Finland.

The relationship between site characteristics and understorey vegetation composition was analysed with quantitative methods, especially from the viewpoint of site quality estimation. Theoretical models were applied to an empirical data set collected from the upland forests of southern Finland comprising 104 sites dominated by Scots pine (Pinus sylvestris L.), and 165 sites dominated by Norway spruce (Picea abies (L.) Karsten). Site index H100 was used as an independent measure of site quality. A new model for the estimation of site quality at sites with a known understorey vegetation composition was introduced. It is based on the application of Bayes' theorem to the density function of site quality within the study area combined with the species-specific presence-absence response curves. The resulting posterior probability density function may be used for calculating an estimate for the site variable. Using this method, a jackknife estimate of site index H100 was calculated separately for pine- and spruce-dominated sites. The results indicated that the cross-validation root mean squared error (RMSEcv) of the estimates improved from 2.98 m down to 2.34 m relative to the "null" model (standard deviation of the sample distribution) in pine-dominated forests. In spruce-dominated forests RMSEcv decreased from 3.94 m down to 3.16 m. In order to assess these results, four other estimation methods based on understorey vegetation composition were applied to the same data set. The results showed that none of the methods was clearly superior to the others. In pine-dominated forests, RMSEcv varied between 2.34 and 2.47 m, and the corresponding range for spruce-dominated forests was from 3.13 to 3.57 m.

Local numerical modelling of magnetoconvection and turbulence - implications for mean-field theories

During the last decades mean-field models, in which large-scale magnetic fields and differential rotation arise due to the interaction of rotation and small-scale turbulence, have been enormously successful in reproducing many of the observed features of the Sun. In the meantime, new observational techniques, most prominently helioseismology, have yielded invaluable information about the interior of the Sun. This new information, however, imposes strict conditions on mean-field models. Moreover, most of the present mean-field models depend on knowledge of the small-scale turbulent effects that give rise to the large-scale phenomena. In many mean-field models these effects are prescribed in ad hoc fashion due to the lack of this knowledge. With large enough computers it would be possible to solve the MHD equations numerically under stellar conditions. However, the problem is too large by several orders of magnitude for the present day and any foreseeable computers. In our view, a combination of mean-field modelling and local 3D calculations is a more fruitful approach. The large-scale structures are well described by global mean-field models, provided that the small-scale turbulent effects are adequately parameterized. The latter can be achieved by performing local calculations which allow a much higher spatial resolution than what can be achieved in direct global calculations. In the present dissertation three aspects of mean-field theories and models of stars are studied. Firstly, the basic assumptions of different mean-field theories are tested with calculations of isotropic turbulence and hydrodynamic, as well as magnetohydrodynamic, convection. Secondly, even if the mean-field theory is unable to give the required transport coefficients from first principles, it is in some cases possible to compute these coefficients from 3D numerical models in a parameter range that can be considered to describe the main physical effects in an adequately realistic manner. In the present study, the Reynolds stresses and turbulent heat transport, responsible for the generation of differential rotation, were determined along the mixing length relations describing convection in stellar structure models. Furthermore, the alpha-effect and magnetic pumping due to turbulent convection in the rapid rotation regime were studied. The third area of the present study is to apply the local results in mean-field models, which task we start to undertake by applying the results concerning the alpha-effect and turbulent pumping in mean-field models describing the solar dynamo.

Short-Horizon Asymmetric Mean-Reversion and Overreactions: Evidence from the Nordic Stock Markets

This paper examines the asymmetric behavior of conditional mean and variance. Short-horizon mean-reversion behavior in mean is modeled with an asymmetric nonlinear autoregressive model, and the variance is modeled with an Exponential GARCH in Mean model. The results of the empirical investigation of the Nordic stock markets indicates that negative returns revert faster to positive returns when positive returns generally persist longer. Asymmetry in both mean and variance can be seen on all included markets and are fairly similar. Volatility rises following negative returns more than following positive returns which is an indication of overreactions. Negative returns lead to increased variance and positive returns leads even to decreased variance.

Effects of Mean Luminance Changes on Human Contrast Perception

Background When we are viewing natural scenes, every saccade abruptly changes both the mean luminance and the contrast structure falling on any given retinal location. Thus it would be useful if the two were independently encoded by the visual system, even when they change simultaneously. Recordings from single neurons in the cat visual system have suggested that contrast information may be quite independently represented in neural responses to simultaneous changes in contrast and luminance. Here we test to what extent this is true in human perception. Methodology/Principal Findings Small contrast stimuli were presented together with a 7-fold upward or downward step of mean luminance (between 185 and 1295 Td, corresponding to 14 and 98 cd/m2), either simultaneously or with various delays (50–800 ms). The perceived contrast of the target under the different conditions was measured with an adaptive staircase method. Over the contrast range 0.1–0.45, mainly subtractive attenuation was found. Perceived contrast decreased by 0.052±0.021 (N = 3) when target onset was simultaneous with the luminance increase. The attenuation subsided within 400 ms, and even faster after luminance decreases, where the effect was also smaller. The main results were robust against differences in target types and the size of the field over which luminance changed. Conclusions/Significance Perceived contrast is attenuated mainly by a subtractive term when coincident with a luminance change. The effect is of ecologically relevant magnitude and duration; in other words, strict contrast constancy must often fail during normal human visual behaviour. Still, the relative robustness of the contrast signal is remarkable in view of the limited dynamic response range of retinal cones. We propose a conceptual model for how early retinal signalling may allow this.

Phonological Mean Length of Utterance as an indicator of typical and impaired phonological development in children acquiring Finnish

The aim of this study was to examine the applicability of the Phonological Mean Length of Utterance (pMLU) method to the data of children acquiring Finnish, for both typically developing children and children with a Specific Language Impairment (SLI). Study I examined typically developing children at the end of the one-word stage (N=17, mean age 1;8), and Study II analysed children s (N=5) productions in a follow-up study with four assessment points (ages 2;0, 2;6, 3;0, 3;6). Study III was carried out in the form of a review article that examined recent research on the phonological development of children acquiring Finnish and compared the results with general trends and cross-linguistic findings in phonological development. Study IV included children with SLI (N=4, mean age 4;10) and age-matched peers. The analyses in Studies I, II and IV were made using the quantitative pMLU method. In the pMLU method, pMLU values are counted for both the words that the children targeted (so-called target words) and the words produced by the children. When the child s average pMLU value was divided with the average target word pMLU value, it is possible to examine that child s accuracy in producing the words with the Whole-Word Proximity (PWP) value. In addition, the number of entirely correctly produced words is counted to obtain the Whole-Word Correctness (PWC) value. Qualitative analyses were carried out in order to examine how the children s phoneme inventories and deficiencies in phonotactics would explain the observed pMLU, PWP and PWC values. The results showed that the pMLU values for children acquiring Finnish were relatively high already at the end of the one-word stage (Study I). The values were found to reflect the characteristics of the ambient language. Typological features that lead to cross-linguistic differences in pMLU values were also observed in the review article (Study III), which noted that in the course of phonological acquisition there are a large number of language-specific phenomena and processes. Study II indicated that overall the children s phonological development during the follow-up period was reflected in the pMLU, PWP and PWC values, although the method showed limitations in detecting qualitative differences between the children. Correct vowels were not scored in the pMLU counts, which led to some misleadingly high pMLU and PWP results: vowel errors were only reflected in the PWC values. Typically developing children in Study II reached the highest possible pMLU results already around age 3;6. At the same time, the differences between the children with SLI and age-matched peers in the pMLU values were very prominent (Study IV). The values for the children with SLI were similar to the ones reported for two-year-old children. Qualitative analyses revealed that the phonologies of the children with SLI largely resembled the ones of younger, typically developing children. However, unusual errors were also witnessed (e.g., vowel errors, omissions of word-initial stops, consonants added to the initial position in words beginning with a vowel). This dissertation provides an application of a new tool for quantitative phonological assessment and analysis in children acquiring Finnish. The preliminary results suggest that, with some modifications, the pMLU method can be used to assess children s phonological development and that it has some advantages compared to the earlier, segment-oriented approaches. Qualitative analyses complemented the pMLU s observations on the children s phonologies. More research is needed in order to verify the levels of the pMLU, PWP and PWC values in children acquiring Finnish.