Browsing by Subject "models"

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  • Kilkki, Pekka; Pökälä, Raimo (Suomen metsätieteellinen seura, 1975)
  • Tan, Jimin (Suomen metsätieteellinen seura, 1987)
  • Mäkelä, A.; Hari, P.; Kellomäki, Seppo (Suomen metsätieteellinen seura, 1981)
  • Kellomäki, Seppo; Hänninen, Heikki; Kolström, Taneli; Kotisaari, Ahti; Pukkala, Timo (Suomen metsätieteellinen seura, 1987)
  • Omwami, Raymond K. (Suomen metsätieteellinen seura, 1986)
  • Omwami, Raymond K. (Suomen metsätieteellinen seura, 1988)
    A study aimed at applying concepts of economic theory relevant to the formulation of a long-term timber production model as a basis of forest policy. A vertically integrated forest sector production model is described, together with its application in a developing economy and the derivation of a dynamic silvicultural investment criterion (in a labour surplus economy).
  • Mykkänen, Reijo (The Society of Forestry in Finland - The Finnish Forest Research Institute, 1994)
    The study presents a theory of utility models based on aspiration levels, as well as the application of this theory to the planning of timber flow economics. The first part of the study comprises a derivation of the utility-theoretic basis for the application of aspiration levels. Two basic models are dealt with: the additive and the multiplicative. Applied here solely for partial utility functions, aspiration and reservation levels are interpreted as defining piecewisely linear functions. The standpoint of the choices of the decision-maker is emphasized by the use of indifference curves. The second part of the study introduces a model for the management of timber flows. The model is based on the assumption that the decision-maker is willing to specify a shape of income flow which is different from that of the capital-theoretic optimum. The utility model comprises four aspiration-based compound utility functions. The theory and the flow model are tested numerically by computations covering three forest holdings. The results show that the additive model is sensitive even to slight changes in relative importances and aspiration levels. This applies particularly to nearly linear production possibility boundaries of monetary variables. The multiplicative model, on the other hand, is stable because it generates strictly convex indifference curves. Due to a higher marginal rate of substitution, the multiplicative model implies a stronger dependence on forest management than the additive function. For income trajectory optimization, a method utilizing an income trajectory index is more efficient than one based on the use of aspiration levels per management period. Smooth trajectories can be attained by squaring the deviations of the feasible trajectories from the desired one.
  • Väisänen, Rauno; Heliövaara, Kari (The Society of Forestry in Finland - The Finnish Forest Research Institute, 1994)
    The presence/absence data of twenty-seven forest insect taxa (e.g. Retinia resinella, Formica spp., Pissodes spp., several scolytids) and recorded environmental variation were used to investigate the applicability of modelling insect occurrence based on satellite imagery. The sampling was based on 1800 sample plots (25 m by 25 m) placed along the sides of 30 equilateral triangles (side 1 km) in a fragmented forest area (approximately 100 km2) in Evo, S Finland. The triangles were overlaid on land use maps interpreted from satellite images (Landsat TM 30 m multispectral scanner imagery 1991) and digitized geological maps. Insect occurrence was explained using either environmental variables measured in the field or those interpreted from the land use and geological maps. The fit of logistic regression models varied between species, possibly because some species may be associated with the characteristics of single trees while other species with stand characteristics. The occurrence of certain insect species at least, especially those associated with Scots pine, could be relatively accurately assessed indirectly on the basis of satellite imagery and geological maps. Models based on both remotely sensed and geological data better predicted the distribution of forest insects except in the case of Xylechinus pilosus, Dryocoetes sp. and Trypodendron lineatum, where the differences were relatively small in favour of the models based on field measurements. The number of species was related to habitat compartment size and distance from the habitat edge calculated from the land use maps, but logistic regressions suggested that other environmental variables in general masked the effect of these variables in species occurrence at the present scale.
  • Kangas, Annika; Raty, Minna; Korhonen, Kari T.; Vauhkonen, Jari; Packalen, Tuula (2019)
    Forest information is needed at global, national and local scales. This review aimed at providing insights of potential of national forest inventories (NFIs) as well as challenges they have to cater to those needs. Within NFIs, the authors address the methodological challenges introduced by the multitude of scales the forest data are needed, and the challenges in acknowledging the errors due to the measurements and models in addition to sampling errors. Between NFIs, the challenges related to the different harmonization tasks were reviewed. While a design-based approach is often considered more attractive than a model-based approach as it is guaranteed to provide unbiased results, the model-based approach is needed for downscaling the information to smaller scales and acknowledging the measurement and model errors. However, while a model-based inference is possible in small areas, the unknown random effects introduce biased estimators. The NFIs need to cater for the national information requirements and maintain the existing time series, while at the same time providing comparable information across the countries. In upscaling the NFI information to continental and global information needs, representative samples across the area are of utmost importance. Without representative data, the model-based approaches enable provision of forest information with unknown and indeterminable biases. Both design-based and model-based approaches need to be applied to cater to all information needs. This must be accomplished in a comprehensive way In particular, a need to have standardized quality requirements has been identified, acknowledging the possibility for bias and its implications, for all data used in policy making.
  • Shuku, Takayuki; Ropponen, Janne; Juntunen, Janne; Suito, Hiroshi (Springer, 2022)
    Meteorology and Atmospheric Physics
    This study presents a data-driven model of the local wind field over two small lakes in Jyväskylä, Finland. Five temporary monitoring stations installed during the summers of 2015 and 2016 observed wind speed/direction around the two lakes. In addition, an official meteorological station located 15 km north of the lakes is permanently available. Our goal was to develop a model that could evaluate wind speed and direction over the two lakes using only data from the permanent station. Statistical analysis for the spatio-temporal wind data revealed that (1) local wind speed is correlated with the elevation and its cyclic pattern is identical to that of the official-station data, and (2) the local wind direction field is spatially homogeneous and is strongly correlated with the official-station data. Based on these results, we built two regression models for estimating spatial distribution of local wind speed and directions based on the digital elevation model (DEM) and official-station data. We compared the predicted wind speeds/directions by the proposed model with the corresponding observation data and a numerical result for model validation. We found that the proposed model could effectively simulate heterogeneous local wind fields and considers uncertainty of estimates.
  • Riihinen, Päiviö (Suomen metsätieteellinen seura, 1963)
  • Hänninen, Heikki (Suomen metsätieteellinen seura, 1987)
  • Bettencourt da Silva, Ricardo J.N; Saame, Jaan; Anes, Bárbara; Heering, Agnes; Leito, Ivo; Näykki, Teemu; Stoica, Daniela; Deleebeeck, Lisa; Bastkowski, Frank; Snedden, Alan; Camões, M. Filomena (Elsevier, 2021)
    Analytica Chimica Acta 1182 (2021), 338923
    The use of the unified pH concept, pHabsH2O, applicable to aqueous and non-aqueous solutions, which allows interpreting and comparison of the acidity of different types of solutions, requires reliable and objective determination. The pHabsH2O can be determined by a single differential potentiometry measurement referenced to an aqueous reference buffer or by a ladder of differential potentiometric measurements that allows minimisation of inconsistencies of various determinations. This work describes and assesses bottom-up evaluations of the uncertainty of these measurements, where uncertainty components are combined by the Monte Carlo Method (MCM) or Taylor Series Approximation (TSM). The MCM allows a detailed simulation of the measurements, including an iterative process involving in minimising ladder deviations. On the other hand, the TSM requires the approximate determination of minimisation uncertainty. The uncertainty evaluation was successfully applied to measuring aqueous buffers with pH of 2.00, 4.00, 7.00, and 10.00, with a standard uncertainty of 0.01. The reference and estimated values from both approaches are metrologically compatible for a 95% confidence level even when a negligible contribution of liquid junction potential uncertainty is assumed. The MCM estimated pH values with an expanded uncertainty, for the 95% confidence level, between 0.26 and 0.51, depending on the pH value and ladder inconsistencies. The minimisation uncertainty is negligible or responsible for up to 87% of the measurement uncertainty. The TSM quantified measurement uncertainties on average only 0.05 units larger than the MCM estimated ones. Additional experimental tests should be performed to test these uncertainty models for analysis performed in other laboratories and on non-aqueous solutions.
  • Aydinonat, N. Emrah; Köksal, Emin (2019)
    There is a striking contrast between the significance of Harold Hotelling’s contribution to industrial economics and the fact that his location model was invalid, unrealistic and non-robust. It is difficult to make sense of the explanatory value of Hotelling’s model based on philosophical accounts that emphasize logical validity, representational adequacy, and robustness as determinants of explanatory value. However, these accounts are misleading because they overlook the context within which the explanatory value added of a model is apprehensible. We present Hotelling’s model in its historical context and show why it is an important and explanatory model despite its apparent deficiencies.
  • Solberg, Birger (Suomen metsätieteellinen seura, 1986)
  • Kangas, Annika; Korhonen, Kari T. (The Finnish Society of Forest Science and The Finnish Forest Research Institute, 1995)
    Semiparametric models, ordinary regression models and mixed models were compared for modelling stem volume in National Forest Inventory data. MSE was lowest for the mixed model. Examination of spatial distribution of residuals showed that spatial correlation of residuals is lower for semiparametric and mixed models than for parametric models with fixed regressors. Mixed models and semiparametric models can both be used for describing the effect of geographic location on stem form.
  • Laakom, Firas; Raitoharju, Jenni; Passalis, Nikolaos; Iosifidis, Alexandros; Gabbouj, Moncef (Institute of Electrical and Electronics Engineers (IEEE), 2022)
    IEEE Access
    Spectral-based subspace learning is a common data preprocessing step in many machine learning pipelines. The main aim is to learn a meaningful low dimensional embedding of the data. However, most subspace learning methods do not take into consideration possible measurement inaccuracies or artifacts that can lead to data with high uncertainty. Thus, learning directly from raw data can be misleading and can negatively impact the accuracy. In this paper, we propose to model artifacts in training data using probability distributions; each data point is represented by a Gaussian distribution centered at the original data point and having a variance modeling its uncertainty. We reformulate the Graph Embedding framework to make it suitable for learning from distributions and we study as special cases the Linear Discriminant Analysis and the Marginal Fisher Analysis techniques. Furthermore, we propose two schemes for modeling data uncertainty based on pair-wise distances in an unsupervised and a supervised contexts.
  • Rankinen, Katri; Enrique, José; Bernal, Cano; Holmberg, Maria; Vuorio, Kristiina; Granlund, Kirsti (Elsevier, 2019)
    Science of The Total Environment 658 (2019), 1278-1292
    In Finland, a recent ecological classification of surface waters showed that the rivers and coastal waters need attention to improve their ecological state. We combined eco-hydrological and empirical models to study chlorophyll-a concentration as an indicator of eutrophication in a small agricultural river. We used a modified story-and-simulation method to build three storylines for possible changes in future land use due to climate change and political change. The main objective in the first storyline is to stimulate economic activity but also to promote the sustainable and efficient use of resources. The second storyline is based on the high awareness but poor regulation of environmental protection, and the third is to survive as individual countries instead of being part of a unified Europe. We assumed trade of agricultural products to increase to countries outside Europe. We found that chlorophyll-a concentration in the river depended on total phosphorus concentration. In addition, there was a positive synergistic interaction between total phosphorus and water temperature. In future storylines, chlorophyll-a concentration increased due to land use and climate change. Climate change mainly had an indirect influence via increasing nutrient losses from intensified agriculture. We found that well-designed agri-environmental measures had the potential to decrease nutrient loading from fields, as long as the predicted increase in temperature remained under 2 °C. However, we were not able to achieve the nutrient reduction stated in current water protection targets. In addition, the ecological status of the river deteriorated. The influence of temperature on chlorophyll-a growth indicates that novel measures for shading rivers to decrease water temperature may be needed in the future.
  • Holman, Ian P.; Brown, Calum; Carter, Timothy R.; Harrison, Paula A.; Rounsevell, Mark (Springer, 2019)
    Regional Environmental Change 19, 711–721 (2019)
    Climate change adaptation is a complex human process, framed by uncertainties and constraints, which is difficult to capture in existing assessment models. Attempts to improve model representations are hampered by a shortage of systematic descriptions of adaptation processes and their relevance to models. This paper reviews the scientific literature to investigate conceptualisations and models of climate change adaptation, and the ways in which representation of adaptation in models can be improved. The review shows that real-world adaptive responses can be differentiated along a number of dimensions including intent or purpose, timescale, spatial scale, beneficiaries and providers, type of action, and sector. However, models of climate change consequences for land use and water management currently provide poor coverage of these dimensions, instead modelling adaptation in an artificial and subjective manner. While different modelling approaches do capture distinct aspects of the adaptive process, they have done so in relative isolation, without producing improved unified representations. Furthermore, adaptation is often assumed to be objective, effective and consistent through time, with only a minority of models taking account of the human decisions underpinning the choice of adaptation measures (14%), the triggers that motivate actions (38%) or the time-lags and constraints that may limit their uptake and effectiveness (14%). No models included adaptation to take advantage of beneficial opportunities of climate change. Based on these insights, transferable recommendations are made on directions for future model development that may enhance realism within models, while also advancing our understanding of the processes and effectiveness of adaptation to a changing climate.
  • Kilkki, Pekka (Suomen metsätieteellinen seura, 1968)