Local and Regional Scale Determinants of Biodiversity Patterns in Boreal Agricultural Landscapes

This thesis examines the local and regional scale determinants of biodiversity patterns using existing species and environmental data. The research focuses on agricultural environments that have experienced rapid declines of biodiversity during past decades. Existing digital databases provide vast opportunities for habitat mapping, predictive mapping of species occurrences and richness and understanding the speciesenvironment relationships. The applicability of these databases depends on the required accuracy and quality of the data needed to answer the landscape ecological and biogeographical questions in hand. Patterns of biodiversity arise from confounded effects of different factors, such as climate, land cover and geographical location. Complementary statistical approaches that can show the relative effects of different factors are needed in biodiversity analyses in addition to classical multivariate models. Better understanding of the key factors underlying the variation in diversity requires the analyses of multiple taxonomic groups from different perspectives, such as richness, occurrence, threat status and population trends. The geographical coincidence of species richness of different taxonomic groups can be rather limited. This implies that multiple geographical regions should be taken into account in order to preserve various groups of species. Boreal agricultural biodiversity and in particular, distribution and richness of threatened species is strongly associated with various grasslands. Further, heterogeneous agricultural landscapes characterized by moderate field size, forest patches and non-crop agricultural habitats enhance the biodiversity of rural environments. From the landscape ecological perspective, the major threats to Finnish agricultural biodiversity are the decline of connected grassland habitat networks, and general homogenization of landscape structure resulting from both intensification and marginalization of agriculture. The maintenance of key habitats, such as meadows and pastures is an essential task in conservation of agricultural biodiversity. Furthermore, a larger landscape context should be incorporated in conservation planning and decision making processes in order to respond to the needs of different species and to maintain heterogeneous rural landscapes and viable agricultural diversity in the future.

Ennustavaa elinympäristömallinnusta oppikirjamaisissa muodoissa

Kirjallisuusarvostelu

Spatial modeling techniques for mapping and characterization of acid sulfate soils

Acid sulfate (a.s.) soils constitute a major environmental issue. Severe ecological damage results from the considerable amounts of acidity and metals leached by these soils in the recipient watercourses. As even small hot spots may affect large areas of coastal waters, mapping represents a fundamental step in the management and mitigation of a.s. soil environmental risks (i.e. to target strategic areas). Traditional mapping in the field is time-consuming and therefore expensive. Additional more cost-effective techniques have, thus, to be developed in order to narrow down and define in detail the areas of interest. The primary aim of this thesis was to assess different spatial modeling techniques for a.s. soil mapping, and the characterization of soil properties relevant for a.s. soil environmental risk management, using all available data: soil and water samples, as well as datalayers (e.g. geological and geophysical). Different spatial modeling techniques were applied at catchment or regional scale. Two artificial neural networks were assessed on the Sirppujoki River catchment (c. 440 km2) located in southwestern Finland, while fuzzy logic was assessed on several areas along the Finnish coast. Quaternary geology, aerogeophysics and slope data (derived from a digital elevation model) were utilized as evidential datalayers. The methods also required the use of point datasets (i.e. soil profiles corresponding to known a.s. or non-a.s. soil occurrences) for training and/or validation within the modeling processes. Applying these methods, various maps were generated: probability maps for a.s. soil occurrence, as well as predictive maps for different soil properties (sulfur content, organic matter content and critical sulfide depth). The two assessed artificial neural networks (ANNs) demonstrated good classification abilities for a.s. soil probability mapping at catchment scale. Slightly better results were achieved using a Radial Basis Function (RBF) -based ANN than a Radial Basis Functional Link Net (RBFLN) method, narrowing down more accurately the most probable areas for a.s. soil occurrence and defining more properly the least probable areas. The RBF-based ANN also demonstrated promising results for the characterization of different soil properties in the most probable a.s. soil areas at catchment scale. Since a.s. soil areas constitute highly productive lands for agricultural purpose, the combination of a probability map with more specific soil property predictive maps offers a valuable toolset to more precisely target strategic areas for subsequent environmental risk management. Notably, the use of laser scanning (i.e. Light Detection And Ranging, LiDAR) data enabled a more precise definition of a.s. soil probability areas, as well as the soil property modeling classes for sulfur content and the critical sulfide depth. Given suitable training/validation points, ANNs can be trained to yield a more precise modeling of the occurrence of a.s. soils and their properties. By contrast, fuzzy logic represents a simple, fast and objective alternative to carry out preliminary surveys, at catchment or regional scale, in areas offering a limited amount of data. This method enables delimiting and prioritizing the most probable areas for a.s soil occurrence, which can be particularly useful in the field. Being easily transferable from area to area, fuzzy logic modeling can be carried out at regional scale. Mapping at this scale would be extremely time-consuming through manual assessment. The use of spatial modeling techniques enables the creation of valid and comparable maps, which represents an important development within the a.s. soil mapping process. The a.s. soil mapping was also assessed using water chemistry data for 24 different catchments along the Finnish coast (in all, covering c. 21,300 km2) which were mapped with different methods (i.e. conventional mapping, fuzzy logic and an artificial neural network). Two a.s. soil related indicators measured in the river water (sulfate content and sulfate/chloride ratio) were compared to the extent of the most probable areas for a.s. soils in the surveyed catchments. High sulfate contents and sulfate/chloride ratios measured in most of the rivers demonstrated the presence of a.s. soils in the corresponding catchments. The calculated extent of the most probable a.s. soil areas is supported by independent data on water chemistry, suggesting that the a.s. soil probability maps created with different methods are reliable and comparable.

Dementoituneiden asiakkaiden hoidon laadun havainnointi- pilottitutkimus Dementia Care Mapping -menetelmällä

Summary: Assessment of the quality of care of people with dementia - Dementia Care Mapping pilot

Mapping out customer segments and marketing channels in the Finnish Homelift market

Työn tavoitteena oli saada selville ketkä ovat uuden tuotteen, eli kotihissin asiakkaat. Mitkä ovat tuotteen mahdollisuudet Suomen markkinoilla ja onko markkinoilla odotettavissa kasvua, sekä miten tähän mahdolliseen kasvuun päästäisiin käsiksi. Kotihissin ominaisuudet vaikuttavat siihen, että se on tarkoitettu asennettavaksi yksityisiin pientaloihin. Uuden tuotteen ansiosta KONE voi liittää nykyiseen vahvaan toimialaansa, eli kerrostaloihin, uuden aluevaltauksen; Pientalot. Tämä 'laajentuminen' tuo mukanaan kuluttajamarkkinoiden haasteet. Markkinatilanteen selvittämiseen käyttin jo olemassa olevaa tietoa hyväkseni; sanomalehdistä markkinatutkimuksiin. Asiakasryhmät kartoitin tutustumalla messutapahtumissa saatuihin kontakteihin. Päätutkimusmenetelmänä käytin haastatteluja. Niihin osallistui kaikkiaan 14 vastaajaa. He vasatsivat kysymyksiin ostomotiiveista ja tuotteesta. Eräs haastattelujen tärkeimmistä teemoista liittyi yhteydenpito- ja jakelukanaviin, joista 12 vastaajaa antoivat mielipiteitään. Työni tulokset viittaavat siihen, että markkinatilanne näyttää positiiviselta KONEen kannalta. Tutkimuksesta sain selville kotihissin asiakassegmentit ja myös miten nämä potentiaaliset asiakkaat saadaan tehokkaimmin tavoitettua.

Web-pohjaisen videoeditorin toteutus ja Object-Relational Mapping

Tässä insinöörityössä esitellään Stadian verkkoviestinnän VIDEOS-hankkeeseen liittyvän web-pohjaisen videoeditorin kehitys ja käytetyt teknologiat. Fooga-nimiseksi nimetty videoeditorin käyttämät tekniikat ovat Ruby, Ruby on Rails, FFmpeg, Mencoder, ImageMagick ja FLVTool2. Ruby on olio-pohjainen skriptikieli, Ruby on Rails on websovelluskehys ja muut tekniikat ovat komentorivipohjaisia työkaluja, jotka tarjoavat tärkeimmät toiminnallisuudet Foogalle. Tavoitteina oli tämän työn yhteydessä ohjelmoida Foogaan perustoiminnallisuudet, jotka mahdollistavat minimaaliset käyttömahdollisuudet kevääseen 2007 mennessä. Kehitystyö jatkuu vuoteen 2009 asti tarjoamalla samalla mahdollisuuden usealle insinöörityölle tekniikan ja liikenteen koulutusohjelmasta. Tämän lisäksi tässä insinöörityössä perehdytään Object-Relational Mapping-tekniikan perusteisiiin ja verrataan Ruby on Railsin ja Javan ORM-ominaisuuksia. Ruby on Railsin osalta esitellään ActiveRecord-luokka ja Javan osalta Hibernate, jonka johdantona on DAO/DTO-sunnittelumalli.

Spatiotemporal Aspects of Environmental Monitoring in the Complex Coastal Region of Southwest Finland

The management and conservation of coastal waters in the Baltic is challenged by a number of complex environmental problems, including eutrophication and habitat degradation. Demands for a more holistic, integrated and adaptive framework of ecosystem-based management emphasize the importance of appropriate information on the status and changes of the aquatic ecosystems. The thesis focuses on the spatiotemporal aspects of environmental monitoring in the extensive and geomorphologically complex coastal region of SW Finland, where the acquisition of spatially and temporally representative monitoring data is inherently challenging. Furthermore, the region is subject to multiple human interests and uses. A holistic geographical approach is emphasized, as it is ultimately the physical conditions that set the frame for any human activity. Characteristics of the coastal environment were examined using water quality data from the database of the Finnish environmental administration and Landsat TM/ETM+ images. A basic feature of the complex aquatic environment in the Archipelago Sea is its high spatial and temporal variability; this foregrounds the importance of geographical information as a basis of environmental assessments. While evidence of a consistent water turbidity pattern was observed, the coastal hydrodynamic realm is also characterized by high spatial and temporal variability. It is therefore also crucial to consider the spatial and temporal representativeness of field monitoring data. Remote sensing may facilitate evaluation of hydrodynamic conditions in the coastal region and the spatial extrapolation of in situ data despite their restrictions. Additionally, remotely sensed images can be used in the mapping of many of those coastal habitats that need to be considered in environmental management. With regard to surface water monitoring, only a small fraction of the currently available data stored in the Hertta-PIVET register can be used effectively in scientific studies and environmental assessments. Long-term consistent data collection from established sampling stations should be emphasized but research-type seasonal assessments producing abundant data should also be encouraged. Thus a more comprehensive coordination of field work efforts is called for. The integration of remote sensing and various field measurement techniques would be especially useful in the complex coastal waters. The integration and development of monitoring system in Finnish coastal areas also requires further scientific assesement of monitoring practices. A holistic approach to the gathering and management of environmental monitoring data could be a cost-effective way of serving a multitude of information needs, and would fit the holistic, ecosystem-based management regimes that are currently being strongly promoted in Europe.

Multi-sensor Simultaneous Localization and Mapping

Simultaneous localization and mapping(SLAM) is a very important problem in mobile robotics. Many solutions have been proposed by different scientists during the last two decades, nevertheless few studies have considered the use of multiple sensors simultane¬ously. The solution is on combining several data sources with the aid of an Extended Kalman Filter (EKF). Two approaches are proposed. The first one is to use the ordinary EKF SLAM algorithm for each data source separately in parallel and then at the end of each step, fuse the results into one solution. Another proposed approach is the use of multiple data sources simultaneously in a single filter. The comparison of the computational com¬plexity of the two methods is also presented. The first method is almost four times faster than the second one.