Browsing by master's degree program "Maantieteen maisteriohjelma"

Geographical accessibility to sports facilities plays an important role when choosing a sports facility. The aim of my thesis is to examine geographical accessibility for sports facilities in Helsinki and Jyväskylä. The data of my study consists of the facilities of three different types of sports in Helsinki, Jyväskylä. The chosen types of facilities are ball parks, disc golf courses and fitness centers. I also use demographic data that cover the age groups of 7-12, 20-24 and 60-64. Mapple Analytics Ltd has produced geographical accessibility data covering whole of Finland which I also use as my data. In my thesis I analyzed geographical accessibility of sports facilities and compare the results to demographic data. Both the geographical accessibility data and demographic data is in 250 x 250 m grid level. the methods I used were Local Moran’s I and Bivariate Local Moran’s I. I applied the methods so that I combined the travel-time data and demographic data. The travel-times are from Mapple Insights API. The travel modes I have used are cycling and driving because people travel to sports facilities mostly by driving or by active methods, especially cycling. The travel-times to ball parks and fitness centers are overall good in both study regions. The good geographical accessibility is caused by that the service pattern is so dense for ball parks and fitness centers. The service pattern covers almost all of the inhabited area in both study regions. However, for some postal areas seem to have not so good geographical accessibility to ball parks. In some areas in Helsinki the geographical accessibility to disc golf course can be considered to be somewhat bad. For the chosen age groups only 20-24-year-olds have unsatisfactory travel-times to disc golf course either by cycling or driving. Other age groups do not show a similar pattern because of the different service pattern of ball parks and fitness centers. Demographic variables do not explain the travel times in this context. It is important to see which postal areas have good or bad geographical accessibility to sports facilities. This helps the future planning of sports facilities. In the future it is also possible to apply non spatial methods to the data I have collected or a similar dataset. It would also be possible to which demographic variable best explains travel-times. Because of Mapple Insighs API data is in 250 x 250 m grid level many applications can be developed using the data.

The 2000s have seen major changes to the upper secondary school curricula and matriculation examinations, with subjects like sustainable development becoming increasingly topical. In addition to the changes in content, required thinking skills have changed over the years. There is now an increased emphasis on the application of knowledge rather than on memorising it. This master’s thesis investigates what kind of thinking skills are required in upper secondary school in relation to sustainability, particularly the food crisis, and what thinking skills students use. The different thinking skills and levels of knowledge required can be analysed according to Bloom's revised taxonomy. This is a classification system that can be used to determine the levels of thinking skills and knowledge required in test questions, for example. In contrast, the maturity of the answers and the thinking skills students convey can be classified using the SOLO taxonomy. The study analysed the thinking skills and knowledge levels required for the spring 2020 Finnish matriculation examination (geography examination food-crisis related task 6) according to Bloom's revised taxonomy. In turn, students' answers (n=130) to the task were analysed according to the SOLO taxonomy. The answers were classified according to their maturity into the SOLO categories that were best represented by the answers. The classification was based on factors such as the consistency of the responses and the number of perspectives addressed. The thinking skills required for the test question were comprehension and analysis. The answers mainly reached the level of the multi-structural and pre-transitional phase, i.e. only a small number of answers reached the level required by the task. The results suggest that a large proportion of students are not able to demonstrate in their responses the use of the required thinking skills, and many do not have the required level of knowledge of the content of sustainable development.

Sub-arctic river ecosystems are recognized as biodiversity hotspots in the region. However, gaps exist in understanding the potential impacts of the current climate change on these sensitive environments due to a lack of local data and knowledge of suitable monitoring methods. Remote sensing offers a promising approach to map river bathymetry, a critical factor in monitoring river environments. In this study, I investigated the efficacy of three remote sensing methods – multibeam echo sounding, green-wavelength airborne laser scanning, and multispectral satellite imagery – for mapping bathymetry along the Tana River, located at the border of northern Finland and Norway. Multibeam echo sounding, and laser scanning offer high-resolution and good penetration capabilities for mapping shallow river bathymetry. Satellite imagery can cover large spatial areas, often more cost-effectively than other remote sensing methods, albeit with lower spatial resolution. The analysis involved processing field survey data from two study sites with varying topography, slope, and flow velocity. I conducted the bathymetric model generation by using Inverse Distance Weighting interpolation and Lyzenga algorithm methods. The validation was carried out through error assessment. Performance evaluation of the bathymetric models and their differences were conducted by calculating linear regression and Pearson’s correlation coefficient, vertical difference, and bottom roughness. The results suggest that all three remote sensing methods successfully captured the main characteristics of the river bottom shape, aligning with the geomorphological characteristics of the study sites. The multibeam echo sounding provided densest and most coherent bathymetric models (mean R2=0.57 and RMSE=0.80). The airborne laser scanning produced bathymetric models with highest uncertainty in elevation due to noise and gaps in the data and showed better accuracy above the water surface than below (mean R2=0.27 and RMSE=1.18, compared to R2=0.98 and RMSE=0.18). The comparability of the bathymetry derived from satellite imagery against other methods was not optimal due to notably lower spatial resolution, but the satellite-based bathymetric models were able to capture the general variations in river bottom elevation (mean R2=0.48 and RMSE=0.96). The study area that was shallower, had a slow flow rate, and had a sandy bottom yielded more accurate bathymetric models. This was evidenced by strong positive correlation coefficients (mean r=0.83, compared to r=0.23 in the other site) and fewer river bottom profile differences between the models. The findings highlight the importance of comprehensive validation data and proper data pre-processing. Addressing these challenges is important for advancing the understanding of how to map and monitor sub-arctic river bathymetry.

The ongoing environmental change will cause changes in arctic-alpine environment affecting both abiotic and biotic processes and the distribution of arctic-alpine vegetation that has adapted to the cold environment. Former studies on the distribution of arctic-alpine vegetation have been conducted more from a macroclimatic point of view neglecting the microclimate perspective. Microclimate refers to radiation, temperature, humidity, and wind conditions near the Earth’s surface. These conditions vary notably in the topographically heterogenous mountain tundra. The effect of the microclimatic factors is particularly important when investigating low-growing arctic-alpine vegetation as the microclimatic variables can be expected to describe the climatic conditions of the biotically active layer better than the macroclimatic variables. The purpose of this thesis is to study how the microclimatic conditions vary across different biotopes within mountain tundra and to examine which microclimatic variables best explain the local distribution of the arctic-alpine vegetation. The microclimatic variation in the different biotopes of the mountain tundra was studied by examining the statistical key figures of air and soil temperature and soil moisture measurements. Species distributions modelling was used to examine the distribution of arctic-alpine vascular plants and species correspondence to the microclimate variables as well as the importance of those variables on the species distributions. The research material consists of the microclimate and species data collected on the field as well as data based on topography and remote sensing. The data for the study were collected around Rastigaisa mountain in northern Norway. The explanatory variables used in the species distribution modelling included freezing degree day (FDD), growing degree day, radiation, soil moisture, topographic position index and information on the snow cover persistence. Species distribution modelling was performed using generalized boosted regression. From the modelling results the relative importance of the predictor variables as well as the predicted distributions of the species were interpreted. Microclimate factors varied between biotopes. The biggest variation in air temperature was observed at mountain tundra heath. Soil moisture had a levelling effect on the minimum temperatures and the FDD’s. The species distribution modelling results show that snow and moisture variable have a significant impact on the distribution of the arctic-alpine vegetation. Snow controls both temperature and moisture conditions and hence affects the stress that vegetation undergoes as well as the supply of nutrients.

Global warming is expected to have detrimental consequences on fragile ecosystems in the tropics and to threaten both the global biodiversity as well as food security of millions of people. Forests have the potential to buffer the temperature changes, and the microclimatic conditions below tree canopies usually differ substantially from the ambient macroclimate. Trees cool down their surroundings through several biophysical mechanisms, and the cooling benefits occur also with trees outside forest. Remote sensing technologies offer new possibilities to study how tree cover affects temperatures both in local and regional scales. The aim of this study was to examine canopy cover’s effect on microclimate and land surface temperature (LST) in Taita Hills, Kenya. Temperatures recorded by 19 microclimate sensors under different canopy covers in the study area and LST estimated by Landsat 8 thermal infrared sensor (TIRS) were studied. The main interest was in daytime mean and maximum temperatures measured with the microclimate sensors in June-July 2019. The Landsat 8 imagery was obtained in July 4, 2019 and LST was retrieved using the single-channel method. The temperature records were combined with high-resolution airborne laser scanning (ALS) data of the area from years 2014 and 2015 to address how topographical factors and canopy cover affect temperatures in the area. Four multiple regression models were developed to study the joint impacts of topography and canopy cover on LST. The results showed a negative linear relationship between daytime mean and maximum temperatures and canopy cover percentage (R2 = 0.6–0.74). Any increase in canopy cover contributed to reducing temperatures at all microclimate measuring heights, the magnitude being the highest at soil surface level. The difference in mean temperatures between 0% and 100% canopy cover sites was 4.6–5.9 ˚C and in maximum temperatures 8.9–12.1 ˚C. LST was also affected negatively by canopy cover with a slope of 5.0 ˚C. It was found that canopy cover’s impact on LST depends on altitude and that a considerable dividing line existed at 1000 m a.s.l. as canopy cover’s effect in the highlands decreased to half compared to the lowlands. Based on the results it was concluded that trees have substantial effect on both microclimate and LST, but the effect is highly dependent on altitude. This indicates trees’ increasing significance in hot environments and highlights the importance of maintaining tree cover particularly in the lowland areas. Trees outside forests can increase climate change resilience in the area and the remaining forest fragments should be conserved to control the regional temperatures.

Tree microhabitats are important in assessing forest biodiversity and ecological value. Knowledge of what types of forests and trees bear the most microhabitats can be useful in sustainable forest management and conservation. Based on research that has been done on assessing the main drivers of microhabitats, tree age, size and developmental stage have been established as the main driving factors for microhabitats. Terrestrial laser scanning data has been used in microhabitat modelling, either at forest stand scale, or by directly detecting certain microhabitats from the data using machine learning. However, high precision individual tree level architectural data facilitated by terrestrial laser scanning and quantitative structure modelling has not yet been tested in microhabitat related research. In this thesis I use the detailed tree-level information that the quantitative structure models provide to determine whether high precision tree architectural data improves the modelling performance of tree microhabitats. Terrestrial laser scanning data was collected from ten plots in a hardwood riparian forest area near Leipzig, Germany. Two tree microhabitat inventories from these ten plots collected in the winter of 2020-2021 and January 2023 respectively as reference data sets. Running increasingly complex models for predicting microhabitat richness for the two datasets I found that 1) While the performance gets better with addition of more tree structural variables, the difference was not substantial between models using only variables attainable by less labour-intensive methods and models with more complex, TLS-derived variables. 2) Comparing the performance metrics between the two datasets showed that the models performed very differently between the inventories, suggesting that microhabitat inventory data collection is susceptible to subjectivity, and the surveys are prone to having observer biases. These discrepancies between the datasets further reinforce the established consensus that tree microhabitats are hard to detect. Difficulties with creating reliable reference data sets, along with the inherently random nature of tree microhabitat occurrence can make microhabitat modelling difficult. This thesis concludes that high precision tree structural data might not increase the microhabitat prediction power in a way that justifies the cost. The results support the established consensus that microhabitat occurrence is mainly driven by tree size and living status. Variables such as species, tree neighbourhood metrics and stand level metrics were not included in this study, but should be researched more, as for example, tree structural characteristics and compartmentalization capacity vary between tree species. Additionally, based on the findings in this thesis, further effort into the standardisation of microhabitat inventories and their collection should be done. There should be little to no room for interpretation regarding the typologies of microhabitats and their related field work methodologies, leading to less observer biases and more comparable and comprehensive data.

Suomen aluekehityksen myötä maaseutualueet hiljenevät ihmisten keskittyessä suuriin kaupunkeihin ja kehyskuntiin. Matkailulla on pyritty monilla maaseutualueilla parantamaan elinvoimaa ja taloudellista kehitystä. Matkailun myötä syntyy uusia palveluja sekä työpaikkoja. Matkailun kehittämisen ja onnistumisen kannalta on tärkeää, että paikalliset asukkaat suhatutuvat siihen positiivisesti ja tukevat sen kehittämistä. Tutkimukseni kohdistuu Rantasalmen kuntaan, joka on maaseutumainen kunta Etelä-Savossa. Matkailu on Rantasalmella kasvattanut taloudellista merkitystään tasaisesti ja sen matkailukohteet ovat saanet näkyvyyttä myös eri medioissa. Vaikka Suomessa kotimaanmatkailu on merkittävä matkailualan kannalta, COVID-19 pandemian myötä kasvanut kotimaanmatkailu on vaikuttanut matkustajamääriin Suomen sisällä. Tämän tutkielman tarkoituksena on selvittää mitä mieltä Rantasalmen asukkaat ovat kuntaan kohdistuvasta matkailusta ja miten he kokevat matkailun vaikuttavan kunnan kehitykseen. Ihmisten suhatutumista matkailuun tutkin sosiaalisen vaihdon teorian avulla. Tutkimusaineistona on internetissä jaetun kyselylomakkeen vastaukset, jotka analysoin laadullisen sisällönanalyysin keinoin. Tutkimuksen tulosten perusteella vastaajilla on yleisesti ottaen positiivinen suhtautuminen Rantasalmelle kohdistuvaan matkailuun. Matkailu koetaan taloudellisesti merkittävänä ja sen kehittämiseen suhtaudutaan positiivisesti. Matkailijoita toivotaan saapuvan enemmän ja matkailun laajenevan kunnan alueella nykyistä laajemmalle alueelle. On kuitenkin myös negatiivisia asioita, kuten matkailusta aiheutuneet haitat ympäristölle. Kunnan kehityksen suhteen matkailun koetaan olevan hyvin merkittävässä roolissa kunnan taloudellisen selviytymisen suhteen. Tämän tutkielman perusteella Rantasalmella vastaajat suhtautuvat matkailuun pääosin positiivisesti, mutta huolenaiheitakin on. Huolenaiheet tulisi ottaa huomioon matkailualaa kehitettäessä. Matkailua ollaan valmiita kehittämään tulevaisuudessa lisää ja matkailun koetaan olevan kunnan kehityksen kannalta hyvin merkityksellinen. Matkailua halutaan kehittää yhteistyön voimalla sellaiseksi, että se hyödyttää laajemmin koko kuntaa ja eri toimijoita.

In the current trajectory of human induced global warming, the domains of climate change mitigation and adaptation remain fundamental to the future of human and natural systems. Mitigating the global warming is not only vital but coping with the unavoidable impacts of the global temperature rise will be less disastrous. In terms of the realities of climate change impacts, the climate policies must be implemented. However, the success of mitigation and adaptation efforts might be dependent on how the people and communities are encountered in climate policies. Thus, it is not only crucial how the distribution of climate change burdens and benefits continues, but as important to recognize the multiple entry points to just transition. This thesis contributes to the emerging field of scientific climate justice debate that raises questions of just adaptation and in which ways it is addressed in climate change adaptation policies under the agenda of just transition. The focus of the thesis is particularly on European climate change adaptation dialogue, in the platform of a public consultation organized by the European Commission. With an interpretive approach, the study explores the perceptions of just adaptation in a number of 22 position papers contributed by European and international civic organizations. The analysis is guided by the (1.) the addressment of adaptation injustices and (2.) just adaptation as a transformative pathway. In the prism of environmental and climate justice concerns, and transformative features of adaptation, the results are discussed under the geo-graphy of Carriers of Just Transition. The civic organizations who contributed to the public consultation consider adaptation and just transition important to achieve. At the same time, the civic organizations seem to have adopted a strategy of no-regrets: they actively reclaim on adaptation measures to prepare for the medium and long-term climate impacts while considering that the mitigation efforts of today seem to be failing. At the same time, just adaptation is considered as a way of conserving the present state, while the agenda of just transition seems to be adopted as the desired pathway of fair adaptation. The European adaptation policy dialogue nests in the carriers of just transition – the systemic pathways of consolidating the current European state rather than transformational change.

Due to the harsh conditions in high latitude alpine and arctic regions, climate or land use changes make them very vulnerable. Thus, it is vital to study the habitats of these regions and increase our understanding of what factors impact species distributions. Species distribution modelling can be used to predict possible habitats for species and further inspect the relationships between different environmental variables and species. Generally, these species distribution models have been created using variables describing the topographical and climatic conditions of the study area. Recently there has been more evidence supporting the inclusion of biotic variables to species distribution models at all scales. Including biotic variables can be difficult, as these relationships can be challenging to quantify. This study uses the Normalized Difference Vegetation Index (NDVI) as a surrogate for plant biomass, thus representing biotic interactions. This study aims to answer what are the relationships between environmental variables and the predicted distributions and will including a biotic variable improve the species distribution models. The study data includes observational data from 683 arctic and alpine plant species from Norway, Sweden, and Finland. The observation data were collected from the three national databanks of Norway, Sweden and Finland and completed with observations from the Global Biodiversity Information Facility and observation data collected by the BioGeoClimate Modelling Lab. The cohesive study area was outlined with the biogeographical regions defined by the European Environment Agency. Overall, six environmental variables are used in this study: annual mean temperature, the maximum temperature of the warmest month, annual precipitation, elevation difference in a cell, bedrock class, and NDVI. The NDVI data was gathered by NASA’s MODIS sensors. The observations and the environmental variables were projected into a grid consisting of 1 x 1 km cells covering the whole study area. This study uses the ensemble modelling technique with four individual modelling methods: generalized linear models (GLM), generalized additive models (GAM), generalized boosted models (GBM) and random forests (RF). The modelling process consisted of two modelling rounds so that the impact of NDVI could be evaluated. The first modelling round included all the environmental variables except NDVI (the topoclimate model) and the second modelling round included all the environmental variables (the full model). The two temperature variables, annual mean temperature and the maximum temperature of the warmest month, had the highest mean variable importance values. With the topoclimate model, annual precipitation ranked third with the rest of the climate variables, but when NDVI was added to the models, it rose above annual precipitation. Overall, among the studied arctic and alpine species, the variable importance values of both the edaphic and topographical variables were low. In general, both the topoclimate models and full models performed very well. The mean AUC- and TSS-values were all higher for the full models, indicating that including a biotic variable improved the models. When the binary predictions of both modelling rounds were compared, it was clear that NDVI refined the projected distributions for most species. The results from this study confirm the discovery that including a biotic variable, such as NDVI, has the potential to increase the predictive power of species distribution models. One of the main problems with including biotic variables in species distribution models has been the difficulty of quantifying biotic interactions. NDVI can thus be a promising tool to overcome these difficulties, as it is one of the most direct variables to describe ecosystem productivity, can be acquired at various scales, and as remotely sensed data, it can also cover areas that are difficult to access.

Cartographic interaction, the dialogue between a human and a map, is a process enabling indispensable ways of reasoning with spatial information. Interactive maps are digital applications, increasingly often made with web technologies. Studying and crafting cartographic interaction calls for user-inclusive studies designed around interactive map use, also necessitating the assessment of the rapidly evolving technologies enabling interactive maps. This study combines the technology- and user-centric aspects of cartographic interaction. I ask what the performance bottlenecks of a web map application are, and how different web mapping libraries compare as a platform for real-time cartographic interaction. I also ask how users interact with a highly interactive map interface, and whether cartographic interaction changes the way they perceive the mapped phenomenon. Developing a web map application, a map interface to a massive dataset on spatial accessibility (the Helsinki region Travel Time Matrix), is central to this study. I answer my technology-centric questions by assessing the technological aspects of interactive maps through the development process. To answer my user-centric questions, I carry out a user survey (n=31) by combining the web map application with an online questionnaire. My results show that the geometrical complexity of data, i.e. the number and detail of geometries to render, was the main factor limiting map responsiveness. Notable differences between web mapping libraries existed in the context of dynamic real-time interaction. Survey participants preferred to use the most dynamic mode of map interaction, and perceived the mapped phenomenon differently depending on how they interacted with the map. These results illustrate the dependence between map interface capabilities and technological design choices such as data simplification and software selection. The results also support the wider call for more dynamic map interfaces, indicating that real-time cartographic interaction can be a functional approach to exploring complex data. As a whole, the results highlight the need for the ongoing study of both mapping technologies and map use in order to discover and utilize the potential of cartographic interaction.