. "Geographic Information Science"@en . . "Geography"@en . . "Remote Sensing"@en . . "Computer Science"@en . . "English"@en . . "Planning project"@en . . "15" . "Students will learn modern planning theoretical framework and methods, and apply this knowledge in preparing a planning project as a group work. The general topic of each group project is given by lecturers. During the course, fieldwork is done and a public discussion of the planning solution is simulated, at the end of the course the group work will be presented and defended. The course is divided into three stages (theoretical context of spatial planning, empirical analysis, preparation of a planning solution) and is taught by different lecturers. The results of the statistical analysis are learned to be used as a justification for the planning solution.\n1. Contemporary spatial planning\nIn the first phase, students acquire knowledge of the basic concepts of planning and the most relevant topics in contemporary spatial planning (for example sustainability, mobility, etc.). In addition to this, students become acquainted with the main topics, regulations and spatial plans of the area under study. In the course of the work, suitable theoretical framework for solving the planning project are found. By the end of the first phase, the main goal and task of the Planning Project for each group are formulated.\n2. Statistical analysis\nIn the second phase, each group performs a quantitative analysis based on their specific group-work task. This is done using statistical analysis methods. The goal is to conduct an empirical data analysis and implement the results in the Planning Project. At the end of the second phase, students present their analysis results.\n3. Compilation of a spatial plan\nIn the third phase, the planning solutions and policy recommendations are developed based on the task of the planning project and the analysis performed. A planning map with an explanatory text will be prepared.\n\nOutcome:\nUpon completing the course a student:\n1) knows the principles of contemporary spatial planning and is able to discuss them from different cultural contexts;\n2) is able to use relevant datasets for analyzing social-spatial processes and for preparing spatial plans;\n3) has an overview of the main quantitative and qualitative methods used in spatial planning;\n4) has skills for academic writing;\n5) is able to select and apply appropriate GIS and visualization tools for spatial planning;\n6) is able to develop general planning solutions (explanatory text and maps) based on analysis;\n7) is able to compile spatial plan and design planning maps;\n8) understands the concept of participatory planning and is able to select appropriate involvement methods;\n9) has skills to conduct a public discussion and to introduce publicly the planning solutions;\n10) has participated in group work in international team." . . "Hybrid"@en . "TRUE" . . "Spatial data studio"@en . . "15" . "Combined theoretical (30%) and practical (70%) study.\nCompartments of the studio:\nAcquisition of environmental data.\nSpecifics and acquisition of spatial data.\nReliability and uncertainties of data, spatial data quality.\nData interoperability.\nGeoprocessing\n\nOutcome:\n- Understands and is able to apply methods of data acquisition in different fields\r\n- Is able to design and manage spatial database: knows the formats and software of important spatial data and databases\r\n- Knows spatial coordinate systems and is able to choose correct coordinate system according to region and putpose\r\n- Is able to use and create metadata based on suitable metadata standards, demonstrates the understating of the need for metadata\r\n- Knows main spatial data standards and is able to estimate the spatial data quality\r\n- Is able to independently pose and solve a problem by using spatial data from different geographic regions or global data\r\n- Knows and is able to consider the regional/cultural and sectoral differences in applying geospatial analysis\r\n- Understands the global challenges and is able to put them into local/regional context and provide solutions by using geospatial analysis\r\n- Demonstrates critical thinking and ability to work interdisciplinary teams when working with spatial data\r\n- Is able to communicate and visualise the spatial data in a meaningful way" . . "Hybrid"@en . "TRUE" . . "Demography, global migration and contemporary cities"@en . . "6" . "The course will combine international perspective to migration with the local demographic processes, and place European and Estonian urban trends within the context of the global urbanization. The main migration and demographic approaches and concepts will be discussed: types of migration and intra-urban residential mobility, socio-economic and ethnic segregation, lifecourse theories, transnationalism. Practical exercises and discussions will be carried out during the course, with an aim to develop students' analytical skills and capabilities to independently carry out fieldwork in the field of urban geography. Different pedagogic methods will be applied to combine individual exercises with teamwork, discussion seminars with lectures. During the course meetings will be organized with the key persons among Estonian urban and immigration policy implementors. In this way students will be able to combine theoretical knowldedge with the practical outputs. The course will partly be carried out in combination with a related course \"Demography and Urban Social Geography\" (4EAP, LOOM.02.341) within the Master programmes in the field of human geography. The mix of students with different backgrounds in both courses provides added value to the study outputs.\n\nOutcome:\nAfter completing the course the student will\r\n1) understand the development of global population trends in different regions of the globe;\r\n2) understand the relationship between migration, social inequalities and urban spatial segregation;\r\n3) know the main concepts in demography, migration and segregation\r\n4) obtain analytical skills in the field, including composing population forecast, measure segregation and evaluate life quality in urban neighbourhoods;\r\n5) reflect on the differences and common values shaping migrant integration across cultures and societies\r\n6) be able to place Estonia and Europe among the global framework of urbanization and migration trends;\r\n7) obtain practical knowledge on urban and migration policy." . . "Hybrid"@en . "TRUE" . . "Energy flows and material cycles"@en . . "3" . "The course introduces various approaches and methods used in landscape and climate change studies. The students practice the use of complex study and data analysis methods in physical geography.\n\nOutcome:\nThe student will\r\n1) understand the development patterns of natural features and their mutual relations;\r\n2) know the terminology of physical geography and landscape ecology and is able explain the principles of the functions of main natural complexes;\r\n3) know the main flows of matter in natural landscapes on local, regional, and global scale;\r\n4) know the development of contemporary landscapes and is able to characterize regional units of landscape;\r\n5) know the causes and effects of global environmental changes;\r\n6) be acquainted with the main datasets of physical geography and be able to analyse these;\r\n7) know the main methods of analysis in physical geography;\r\n8) know the evaluation methods of landscape structures and the methods of data analysis in this field." . . "Hybrid"@en . "TRUE" . . "Geography, communication and spatial mobility"@en . . "6" . "The course introduces theoretical and methodological aspects of spatial mobility and its relation to information and communication technologies (ICTs). Lectures and seminars concentrate on mobility studies and mobile data used in geography, tourism and urban studies. Ethical issues in the use of ICT-based big data and differences arising from culture and context are addressed.\r\n\r\nThe course consists of 7 lectures (2x45 min), 2 practical sessions (2x45 min), five assignments and 5 seminars. Each lecture and seminar has an additional text or slide material available in the Moodle.\n\nOutcome:\nBy the end of the course the student\r\n- understands terminology and concepts of spatial mobility;\r\n- is aware how spatial mobility, social mobility and activities of individuals are interrelated;\r\n- is aware of the impacts of information and communication technologies (ICT) on spatial mobility;\r\n- knows the data collection methods of spatial mobility;\r\n- has an overview of passive mobile positioning data;\r\n- has an overview of active positioning methods and smartphone based data;\r\n- is able to measure individuals' spatial mobility with mobile positioning;\r\n- is able to critically analyse the data and highlight the shortcomings of its use;\r\n- understands the concepts of information society and Smart City;\r\n- has an overview of social media data and research applications;\r\n- is able to use mobile phone and social media based information sources for urban studies and planning;\r\n- is aware of the ethical issues related to the use of big data;\r\n- understands how culture and context affect the availability and use of data;\r\n- has an overview of international initiatives in the use of big data;\r\n- has the ability to work in a group and clearly present the results of the assignments." . . "Hybrid"@en . "TRUE" . . "Introduction to programming"@en . . "3" . "Algorithms and programs. Representations of algorithms, flow-charts. Branching algorithms. Loops. Sub-algorithms. Developing algorithms for given text-based problems. Program structure. Names. Variables. Operations. Expressions. Boolean expressions, comparisons. Conditional statements. Loop statements. Lists. Functions. User input. Reading from a file. Writing to a file. Simple user interface.\n\nOutcome:\nAfter passing the course student\n- is motivated to use computers and to develop necessary programs for further studies;\n- can demonstrate basic programming constructs (branching, loops, subprogram) as programming sections;\n- can develop algorithms for simple text-based problems." . . "Hybrid"@en . "TRUE" . . "Spatial data analysis"@en . . "6" . "The course gives an overview of the technics of spatial data analysis in contemporary geoinformatics and includes several hands-on exercises. The course provides students with the skills necessary to investigate spatial patterns of social and environmental processes.\nIf the student has not taken any prerequisite courses but still wishes to participate in the course then please contact the lecturer.\n\nOutcome:\nA successful student has a systematic overview of the main ideas of spatial data analysis and main methods. Student has practical experience of solving spatial analysis tasks by means of the common GIS software." . . "Hybrid"@en . "TRUE" . . "Arcgis software"@en . . "3" . "A lecture on the modules and architecture of ESRI's ArcGIS. Six tutorials using ArcGIS Desktop and its extensions form the core of this course and should be completed as prerequisite for consideration.\n\nOutcome:\nAfter successful passing the student will be able to:\r\n- understand the basics of ArcGIS and coordinate systems;\r\n- understand the character of interoperability of geographic information;\r\n- create and manage a geodatabase, edit a spatial data;\r\n- query a GIS database;\r\n- present data clearly using maps, charts, and reports;\r\n- create programs in Model Builder;\r\n- continue with self-instruction according to one's own needs." . . "Hybrid"@en . "TRUE" . . "Estonian for beginners I, on the basis of english, level 0 > a1.1"@en . . "6" . "The Estonian course will give the basic knowledge of the Estonian grammar and vocabulary.\nThe main topics (vocabulary & conversation):\n* I;\n* Languages, Countries, Nations;\n* Favourites;\n* Numbers;\n* Time;\n* Food and Drink;\n* Family;\n* My day;\n* Tartu;\n\nThe main topics (grammar):\n* Cases: Main Cases of Singular, Local Cases of Singular, Comitative and Abessive of Singular. Nominative Plural;\n* Personal Pronouns, Adjectives, Cardinal Numbers;\n* Present Tense, Imperfect (Simple Past);\n* Imperative Mood;\n* ma- and da- infinitive.\n\nOutcome:\nOn completion of the course the students will be able\r\n* to understand and use Estonian cases, conjugate Estonian verbs in the present and past tenses, use the imperative, use adjectives and cardinal numbers.\r\n* to communicate in everyday situations in the street, in a shop, at a restaurant and socialize in a group, talk and write about her/himself, her/his family, home and eating habits, express (dis)approval.\r\n* to understand and create elementary-level oral and written texts." . . "Presential"@en . "TRUE" . . "How to build a startup company"@en . . "3" . "Learners gain practical, hands-on experience and knowledge about ideation, idea selection, assess their business potential, test their hypothesis in practice and develop appropriate business model. Formed teams gain understanding on entrepreneurship environment, communicate with potential users/clients and build prototypes. Workshops are integrated with individual work and practical tasks, which enable learners to develop their product/service, define value proposition, revenue model and marketing approach. The programme requires commitment, willigness to cooperate, learn teamwork, presentation skills, cope with challenges and stress associated with start-up founding and reflect learning experience.\r\nTeams get guidance from experienced start-up founders and mentors. The programme ends with business ideas presentation at Kaleidoskoop pre-selection from where TOP10 get to pitch at sTARTUp Day .\r\nTeams are enocuraged to execute their projects or business ideas and/or become founders.\n\nOutcome:\nSuccesful learner:\r\n- has gained knowledge about idea development process from ideation to idea selection, value proposal and business model\r\n- is able to test hypotheses related to execution and develop ideas (product/service) in accordance with customer needs,\r\n- is able to assess and analyze the potential market need,\r\n- has gained teamwork skills,\r\n- is able to present business or project idea to potential investors." . . "Hybrid"@en . "TRUE" . . "Work placement"@en . . "6" . "The student will pass the Work Placement course in two parts. In Part 1 (1 ETC), the student will find a position at an organisation or company of the field of speciality, and will design and present the work plan. The student, the organisation and the University of Tartu will sign a tripartite work placement contract. In Part 2 (5 ETC), the student will work at the position for a minimum of 120 hours solving practical tasks in teams. The student will keep a work placement diary and will compose a report that contains a progress report and a self-examination. After the work placement, the student will publicly defend the report evaluated by a committee.\n\nOutcome:\nThe student who has passed the work placement has the following skills (curriculum 2576:Geography):\r\n1) Understanding of work arrangement and team management in organisations or companies in the field of speciality;\r\n2) Knowledge of tools used in practice and overview of applications and skills in the field of speciality;\r\n3) Experience in teamwork with colleagues in the field of speciality, possibly in an international and multicultural team;\r\n4) Capacity to analyse and evaluate the skills and experience obtained from the work placement and defend the report evaluated by a committee:\r\n5) Ability to plan and manage her/his career.\r\nThe student who has passed the work placement has the following skills (curricula: 163917:Geoinformatics for Urbanised Society, and Geo-information Science and Earth Observation for Environmental Modelling and Management):\r\n1) Understanding of the use of spatial data in practice: the architecture and functions of spatial data sets and their applied values;\r\n2) Understanding of work arrangement and team management in organizations working with spatial data;\r\n3) Knowledge of the GIS tools used in practice and be able to solve some practical tasks concerning spatial processes;\r\n4) Experience in teamwork with colleagues in the field of speciality, possibly in an international and multicultural team;\r\n5) Capacity to analyse and evaluate the skills and experiences obtained from the work placement and to defend the report evaluated by a committee;\r\n6) Ability to plan and manage her/his career." . . "Hybrid"@en . "TRUE" . . "Visual geodata mining"@en . . "2" . "This course will be held by visiting professor Jukka Matthias Krisp from University of Augsburg (Germany). The course will be giving brief overview of visual geodata mining. During the course students will get reading materials which later on will follow with discussion. Course also contain exercises with visual data mining programme GeoVista/GeoViz which will be held in the computer room and supervised by prof. Krisp.\n\nOutcome:\nAfter successful passing the student:\r\n* understand applications and methods to \"visual data mining\"\r\n* assess visual data mining tools (anticipated \"GeoVista/GeoViz\")\r\n* understand the overall \"visual mining process\"\r\n* use methods and applications of \"visual spatial data mining\"\r\n* evaluate methods of \"visual spatial data mining" . . "Hybrid"@en . "FALSE" . . "Spatial databases"@en . . "6" . "As described in the course objectives you will build on general database theory and how spatial data is incorporated. You will be introduced to standards for encoding geometry and spatial reference systems in the database realm. This course is about designing a database and working with geospatial data. You will learn spatial functions that form the building blocks of more sophisticated analytical models. Accessing your database with desktop and web applications will be important part of your practical exercises.\n\nOutcome:\nAfter successful passing the student will be able to:\r\n* design and create databases using PostgreSQL/PostGIS;\r\n* manage data and spatial data in PostgreSQL/PostGIS databases;\r\n* perform geospatial analysis in the spatial database." . . "Presential"@en . "FALSE" . . "Spatial data infrastructures"@en . . "3" . "SDI is the infrastructure behind the scenes of modern online geoportals. We will learn how to work with SDI web services and understand their specifications.\n\nOutcome:\nAfter passing the course student\r\nAfter successful passing the student will be able:\r\n- to orient her-/ himself in components and standards that comprise SDI\r\n- to find, access, use different types of data and services within an SDI and spatial data on the web in general\r\n- to understand data specifications according to INSPIRE rules\r\n- to publish data via SDI services such as Web Map Service (WMS), Web Feature Service (WFS) and Web Coverage Service (WCS) using GeoServer software platforms\r\n- understand the need for metadata and catalogues services" . . "Hybrid"@en . "FALSE" . . "Data science in remote sensing"@en . . "6" . "In the beginning of the course students can select a topic which they start to solve in a smaller group. Every group has a supervisor. Course is based on a problem based learning method. Additionally lectures about various remote sensing applications will be held.\n\nOutcome:\nAfter the end of the course:\r\n- students have the overview about principles used in passive, radar and lidar remote sensing and their respective application fields;\r\n- knows the principles of spectral measurements (knows the terms spectrometer, radiance, irradiance, reflectance, atmospheric correction, calibration),\r\n- knows the principles in water remote sensing (bio-optical modelling, adjacency effect)\r\n- knows the principles in vegetation remote sensing (optical properties of the leaf, contribution of various features to the reflectance, leaf angles, various indices).\r\n- student knows how to download, process and analyse remote sensing and possibly ancillary data and apply this knowledge to solve various exercises.\r\n- understands the differences in remote sensing and field data, how to combine them and use for spatio-temporal analyses and supporting the sustainable development goals (SDG) and international environmental frameworks.\r\n- have gained experience how to plan and conduct groupwork, share responsibilities inside small group, present results." . . "Hybrid"@en . "FALSE" . . "Economic geography of urban systems"@en . . "2" . "The course deals with a number of relevant economic geography topics:\r\n-what is economic geography\r\n-the location problem analysed\r\n-location theories: classical, neo-classical and alternative approaches\r\n-location factors\r\n-demography of the enterprise\r\n-city and economics\r\n-urban economic development: competition and networks\r\n-internal urban differentiation: land use\r\n-production networks in a global economy\r\n-'new economic geography'\r\n-geography of the world economy\r\n-evolutionary economic geography\n\nOutcome:\nAfter attending the course, the student will be:\r\n* familiar with the basic concepts of economic geography and urban networks\r\n* able to understand how businesses deal with decisions concerning locational choice;\r\n* able to answer questions regarding urban geography\r\n* able to analyze the complex relationship between city and economy\r\n* able to understand how creative industries operate and what their contribution is to the urban economy" . . "Hybrid"@en . "FALSE" . . "3d modelling and analysis"@en . . "6" . "The course consists of combined theoretical and practical study. The topics are: creation and analysis of terrain and surface models, static and dynamic models and visualisations; visibility analysis; hydrological and flood analysis; 3D modelling, analysis and visualisation in city and landscape planning.\n\nOutcome:\nKnows primary principles of handling and presenting 3D data in terrain and surface, incl. city modelling.\r\nKnows primary data structures used in 3D modelling.\r\nUnderstands and is able to apply basic methods and techniques of 3D modelling and analysis of terrain and various surfaces.\r\nIs able to visualize modelling results in 3D scenes.\r\nKnows implementations of 3D modelling and analysis." . . "Hybrid"@en . "FALSE" . . "Master of Geoinformatics for Urbanised Society"@en . . "https://ut.ee/en/curriculum/geoinformatics-urbanised-society" . "120"^^ . "Hybrid"@en . "The 2-year master's programme in Geoinformatics for Urbanised Society prepares highly qualified specialists in handling and analysing spatial data to better understand the global environmental and urban processes and develop decision support systems for public, private, and non-governmental sectors.\r\n\r\nGovernance increasingly relies on sensors, BIG data, analysis, and fast decision-making in the global information society. Society needs experts who can handle geoinformatics tools to understand and find solutions to complex environmental and urban challenges related to climate and environmental change, growing social inequality, and increased spatial mobility. The master's programme focuses on building interdisciplinary competence by combining geography and IT. Particular emphasis is put on the problem-driven approach and development of students' practical skills.\r\n\r\n1. Learn modern techniques of analysing environmental and urban processes in the age of BIG data.\r\n2. Use spatial analysis tools to master the entire cycle of spatial data management, starting with fieldwork and data acquisition and ending with visualising planning solutions.\r\n3. Understand how to better plan contemporary urbanised societies at times of global warming, pollution concerns, increased global population mobility, ethnic integration, housing crises in the cities and urban poverty.\n\nOutcome:\nUpon graduating, the student\r\n\r\n1. has a comprehension of geoinformatics and geodatabases and can use GIS software to handle spatial data;\r\n2, knows the geographical, social and economic processes in urbanised society as well as the related geodatabases;\r\n3, knows the environmental problems in urbanised society, the environmental technology and spatial databases used to manage and mitigate the issues;\r\n4. can use the contemporary analytical methods of spatial data and the cartographic methods to visualise spatial data;\r\n5. knows the principles and methods of spatial planning;\r\n6. has the skills to compile planning projects with the help of GIS software;\r\n7. knows the concepts of the information society, smart city and integrated planning and can implement them in planning;\r\n8. has acquired experience in teamwork and can work in teams;\r\n9. can give consultation within the field of specialisation;\r\n10. can participate in scientific research and has skills for academic writing."@en . . . . . "2"@en . "FALSE" . . . "Master"@en . "Thesis" . "6000.00" . "Euro"@en . "6000.00" . "Mandatory" . "After graduation, young professionals can find employment in the public, private, or non-governmental sectors as spatial data managers, spatial analysts, GIS consultants, urban and regional planners. There are numerous further employment options in international organisations dealing with global processes, national, regional and local administrative offices responsible for environmental, urban, regional development and policy. Motivated students can continue their studies on the doctoral level and pursue an academic career.\n\nModern life relies increasingly on BIG data and digital work processes – geoinformatics helps manage and analyse historical and real-time spatial data to support decision-making and policy development.\r\n\r\nSuccessful completion of the master’s programme ‘Geoinformatics for Urbanised Society’ enables employment in all sectors as a spatial data manager, spatial analyst, or GIS consultant for planning and regional policy. The alumni work in several local, state, and EU institutions, consultancy companies for planning and environmental management, or companies that provide location-based analyses and IT services or cartographical solutions.\r\n\r\nThe following list of domestic and international companies and institutions shows where many of our alumni with GIS specialisation have found employment:\r\n\r\nRegio, ReachU, Positium LBS, CGI, TerraPro, Navionics, Affecto, Telia, Hendrikson&Ko, Estonian Land Board, Estonian Agricultural Registers and Information Board, Environmental Board, Environmental Agency, Estonian Defence Forces, Estonian Weather Service, Met Office, Tartu Observatory, Tartu City Government, Tallinn City Government, ESPON."@en . "no data" . "TRUE" . "Downstream"@en . . . . . . . . . . . . . . . . . . . "Estonian"@en . . "Faculty of Science and Technology"@en . .