Suomen- ja englanninkieliset digitaaliset kaupunkitilat Helsingissä : Case Instagram

Ubiikkien internet yhteyksien, mobiililaitteiden ja nousevien sosiaalisen median käyttäjämäärien myötä massadataa yksilöistä, kaupungeista, kulttuureista ja yhteiskunnista tuotetaan suuria määriä. Tarve nykyaikaisen nopeasti muuttuvan digitalisoituvan maailmamme ymmärtämiselle kasvaa jatkuvasti. Tämä tekee sosiaalisen median massadata-aineistoista arvokkaan maantieteelliselle tutkimukselle, mutta massadata on laadultaan, määrältään ja monipuolisuudeltaan sellaista, että sen käsittely vaatii uusia ja tehokkaita poikkitieteellisiä metodeja. Sosiaalisen median spatiaalisen massadatan tarkastelu mahdollistaa sen kautta välittyvien digitaalisten kaupunkitilojen tutkimisen. Tässä työssä selvitetään Helsingin alueelta tehtyjen suomen- ja englanninkielisten Instagram-julkaisujen lingvististä sisältöä tarkoituksena (1) selvittää kyseisten Instagram-julkaisujen aiheet, (2) aiheiden spatiotemporaalinen rakenne, (3) kielten väliset erot aiheissa ja (4) lingvististen teknologioiden soveltuvuus maantieteelliseen tutkimukseen. Näiden päämäärien saavuttamiseksi, työssä yhdistellään luonnollisen kielen prosessoinnin ja geoinfromatiikan metodeja soveltamalla aihemallinnusta eri spatiaalisissa mittakaavoissa. Erilaisia visualisointitekniikoita hyödynnetään kielikohtaisten aiheiden analysointiin Helsingin eri kaupunginosissa. Tulokset osoittavat, että suomen- ja englanninkielisten Instagram-julkaisujen aiheet eroavat toisistaan spatiaalisesti, temporaalisesti, vaikka molempien kielten osalta aineisto osoittautui sävyltään ja temporaaliselta rytmiltään samankaltaiseksi. Tuloksena syntyneet spatiaaliset aihemallit vaikuttavat tukevan teoreettista keskustelua digitaalisista kaupunkitiloista, mutta useaa sosiaalisen median alustaa ja useita poikkitieteellisiä metodeja yhdistävää tutkimusta tarvitaan vahvemman empiirisen näytön saamiseksi. Luonnollisen kielen prosessinnin metodit vaikuttavat soveltuvan hyvin maantieteelliseen tutkimukseen, erityisesti sosiaalisen median aineistojen kanssa. With ubiquitous internet access, mobile smart devices and increasing amounts of social media users, big data about individuals, cultures and societies is being produced in vast quantities. This renders social media data valuable for geographic research, but such data requires novel interdisciplinary methods. Spatial social media big data enables the investigation of emergent digital urban spaces. This Master’s thesis analyses the linguistic content of English and Finnish Instagram posts uploaded from Helsinki, Finland, in order to identify (1) common topics, (2) how these topics evolve over space and time, (3) differences in finnish and english spatiotemporal topics and (4) applicability of natural language processing in geographic research. To do so, the study combines methods from natural language processing and geoinformatics, applying the technique of topic modelling at various spatial scales. Different visualization techniques are used to support the analysis of language-specific topics in different neighborhoods of Helsinki. The results show that the topics of Finnish and English Instagram posts differ spatially, temporally and at different scales, although the data for both languages was shown to be similar in sentiment and temporal rhythm. The resulting spatial topics models appear to support theories of digital urban spaces to some extent, but more comprehensive analysis of digital urban spaces requires data from various social media platforms and diverse interdisciplinary methods. Natural language processing methods hold much potential for geographic research, particularly for analyzing social media data

Mapping urban linguistic diversity with social media and population register data

Globalization, urbanization and international mobility have led to increasingly diverse urban populations. Compared to traditional traits for measuring urban diversity, such as ethnicity and country of origin, the role of language remains underexplored in understanding diversity, interactions between different groups and socio-spatial segregation. In this article, we analyse language use in the Helsinki Metropolitan Area by combining individual-level register data, socio-economic grid database, mobile phone and social media data to understand spatio-temporal patterns of linguistic diversity better. We measured linguistic diversity using metrics developed in the fields of ecology and information theory, and performed spatial clustering and regression analyses to explore the spatio-temporal patterns of linguistic diversity. We found spatial and temporal differences between register and social media data, show that linguistic diversity is influenced by the physical and socio-economic environment, and identified areas where different linguistic groups are likely to interact. Our results provide insights for urban planning and understanding urban diversity through linguistic information. As global urbanization, international migration and refugee flows and climate change drive diverse populations into cities, understanding urban diversity and its implications for urban planning and sustainability become increasingly important.Peer reviewe

Exploring human–nature interactions in national parks with social media photographs and computer vision

Understanding the activities and preferences of visitors is crucial for managing protected areas and planning conservation strategies. Conservation culturomics promotes the use of user-generated online content in conservation science. Geotagged social media content is a unique source of in situ information on human presence and activities in nature. Photographs posted on social media platforms are a promising source of information, but analyzing large volumes of photographs manually remains laborious. We examined the application of state-of-the-art computer-vision methods to studying human-nature interactions. We used semantic clustering, scene classification, and object detection to automatically analyze photographs taken in Finnish national parks by domestic and international visitors. Our results showed that human-nature interactions can be extracted from user-generated photographs with computer vision. The different methods complemented each other by revealing broad visual themes related to level of the data set, landscape photogeneity, and human activities. Geotagged photographs revealed distinct regional profiles for national parks (e.g., preferences in landscapes and activities), which are potentially useful in park management. Photographic content differed between domestic and international visitors, which indicates differences in activities and preferences. Information extracted automatically from photographs can help identify preferences among diverse visitor groups, which can be used to create profiles of national parks for conservation marketing and to support conservation strategies that rely on public acceptance. The application of computer-vision methods to automatic content analysis of photographs should be explored further in conservation culturomics, particularly in combination with rich metadata available on social media platforms.Peer reviewe

OSMO - a collaborative network testing knowledge and tools for resource-efficient soil health management

Implication Soil and knowledge are the most important resources for agriculture. In order to create new knowhow on managing soils, collaboration between research, advisory services, product development and farmers is necessary. OSMO –project has provided these opportunities in farmer learning groups, workshops and field trials. Based on the first year of results it is clear that soil health is a complex system, where different aspects interact. Many of the problems observed as nutrient deficiencies can be sourced to compaction from machinery or lack of drainage. On the other hand problems in soil nutritional status may be behind compaction and weed problems. The current hypothesis is that each field has its own set of problems. Soil health can be improved only by identifying the crop yield reducing factors, determining their causes and planning for effective ways to remedy them. Simplified decision support tools are needed to couple the complexity of soil systems into the needs of farm management. Identifying and remedying soil problems have a large potential for increasing the productivity of organic and conventional agriculture. Background and objectives Agricultural soils are under increasing pressure. During the last decades crop rotations have simplified, annual crop areas have increased and machinery has gotten heavier. At the same time the progress in crop yields has stagnated. Compared to the yield potential which is theoretically possible from sunlight and water availability, crop yields are very low, especially in organic agriculture. At the same time, variability between farms, fields and field parts is high. It is unclear why some fields have low yields while other adjacent fields have very good yields. The concept of soil health is an emerging paradigm for looking at soil as a system. It appreciates the interconnections between components of soils and different views on problems (i.e. chemical, physical and biological). The objective of the project is to apply new knowledge on soil quality and health and to test their applicability in practice on farms. This is done through improving knowledge on soil testing, farmer know-how on soil health management and developing tools and study materials. Methods for analyzing and repairing soil problems are tested on 8 experimental problem fields, with adjacent good fields serving as the reference. The approach has been problem oriented, analysis methods and tested techniques have been tailored to each problem field. The aim is to identify and fix all barriers to better productivity and soil health and to test how (and if) the approach works. Key results and discussion The project has been running since 2016 and most of the work is still ongoing. Final results for the test farms will be available in 2018. For now, five regional learning groups are running, each with ca. 20 farms. These have included a six month intensive period of soil management education and application of skills to on-farm work. The separate tools for soil management have been assembled into a soil management planning toolbox, which is being refined based on user experience. Several problems have been identified in the test farms and trials have been run to test for potential solutions. Soil structure has been improved through vetch based cover crop mixes and subsoiling. Gypsum applications have been targeted to remedy Ca:Mg ratio problems and manganese, potassium and boron fertilizers have been tested to remedy common nutrient deficiencies. In 2017, new methods for identifying and solving drainage and compaction issues are being tested. The interaction between research and farmers has been valuable. In the intensive six month courses, researchers have applied new scientific information and converted it into calculators for farm use. Receiving rapid feedback on their applicability and being able to redevelop them into tools has provided useful tools for soil management. How work was carried out? The core of the project was five learning groups with ca. 20 farms in each. Each group held regular meetings and online lectures on the main aspects of soil health (chemical, physical and biological). The participants also had access and guidance on using tools for managing soil fertility, compaction, drainage and crop rotations. The participants filled an online soil management plan for their farm during the course and reported on their own trials and tested solutions for managing soil health. In addition several indepth workshops were arranged on special topics. The scientific work focused on the 8 test fields. Their status was quantified through different soil tests (ammonium acetate extraction, Mehlich 3, Soil Health Tool), physical soil evaluation (visual evaluation of soil structure, soil cover, earthworm counts, water infiltration) and plant nutrient analysis

Early Svecofennian rift-related magmatism: Geochemistry, U-Pb-Hf zircon isotope data and tectonic setting of the Au-hosting Uunimäki gabbro, SW Finland

We characterise the geochemistry, zircon Lu-Hf composition, age and the structure of the Uunimaki gabbro (UGB) in south-western Finland to improve the understanding of i) the early Svecofennian (1.92-1.89 Ga) crustal evolution of the central Fennoscandian Shield, ii) the potential role of rift-related magmatism for the build-up of the Paleoproterozoic accretionary orogens and iii) evaluate, which geological features provide the primary control over the localization of an orogenic gold mineralisation. The zircon U-Pb geochronology defines an age of 1891 +/- 5 Ma for the UGB, which is slightly older than most mafic intrusions in south-western Finland. The obtained chondritic initial zircon eHf values with E-MORB type geochemical affinity suggest a sub continental lithospheric mantle source for the UGB. The overall geochemistry indicates that the UGB magma as well as other E-MORB type rocks in the Pirkanmaa and Hame belts were formed in a rift-related environment in a fore-arc region at 1.89 Ga, predated by arc-type magmatism at similar to ~1.90 Ga and back-arc magmatism at similar to ~1.92 Ga in the Tampere belt. Slab retreat due to roll-back is suggested to cause the extension and related magmatism in the forearc region. Moreover, the timing and compositional and isotopic changes of early-orogenic magmatism are broadly compatible with intervals of extension and contraction, i.e., a tectonic switching model, and may provide a perspective to rapid build-up of Paleoproterozoic crust. Structural characterisation provides a framework where gold mineralisations are preferentially located within the high-strain north-eastern domain of the UGB, within fracture networks adjoining the high-strain zones. Our results indicate that neither the geochemical composition nor age of the intermediate-mafic intrusive host rocks play a major role in controlling the formation of gold mineralisation. By contrast, the localization of orogenic gold is controlled by localised structures (shear zones, fractures), and the variation in lithological composition of the intrusive host may contribute to the style of the mineralisation.</p

LITHOSPHERE 2018: TENTH SYMPOSIUM ON STRUCTURE, COMPOSITION AND EVOLUTION OF THE LITHOSPHERE: PROGRAMME AND EXTENDED ABSTRACTS

The Uunimäki gabbro was studied by zircon U-Pb geochronology which yielded an age of ~1.89 Ga, making it one of the oldest plutonic rocks in the Häme Belt. Geochemical analysis of the gabbro reveals that it lacks several characteristics for typical subduction zone rocks: (i) it does not have a negative Ta-Nb anomaly compared to average NMORB-composition, (ii) it shows a rather unfractionated REE pattern, (iii) it lacks clear enrichment of fluid-mobile elements (e.g. Ba, Rb, Th, Pb). Structurally, the Uunimäki gabbro is located at the intersection of several regional features: (i) steep NE-plunging folds, (ii) a ENE-WSW-trending deformation zone immediately to the north and (iii) a large N-S-trending deformation zone to the west. The gabbro itself has been deformed under both brittle and ductile conditions by primarily NW-SE-trending faults and shears.</p

LITHOSPHERE 2018: TENTH SYMPOSIUM ON STRUCTURE, COMPOSITION AND EVOLUTION OF THE LITHOSPHERE: PROGRAMME AND EXTENDED ABSTRACTS

Shear zones of various ages and orientations are common in Southern Finland. In the study area, E-W and N-S trending shear zones are the dominant structural feature. Mylonitic foliations were identified from the most intensely sheared rocks. Ductile shearing has mainly been of dip-slip type. Structural mapping revealed several larger map-scale folds, which appear to be relatively continuous across the study area from SE to NW. In the central area, folding interfered with the shear zones causing a complex crustal structure such as associated with the Uunimäki mineralization. Aeromagnetic and lithological maps, field observations, stereographic projections and oriented thin sections were used to determine the structural features of the study area.</p