. "Geographic Information Science"@en . . "Remote Sensing"@en . . "Faculty of GeoInformation Science and Earth Observation (ITC)"@en . . . "English"@en . . "Hydrological and environmental cycles"@en . . "7" . "no data" . . "Presential"@en . "TRUE" . . "Earth observation of water resources"@en . . "7" . "In the first week of this course we introduce the geospatial problem solving approach. For this we consider the differences between uses and users of geo-information for problem solving, and the needs for answering geospatial questions. Furthermore, we discuss the influence of societal differences in selecting approaches and priorities when managing natural resources. We will also discuss the role of geo-information in the context of the Sustainable Development Goals and other global challenges. In the last two weeks of the course you will carry out a project assignment, in which you apply elements of the geospatial problem solving approach to produce geo-information relevant for a specific geospatial problem issue." . . "Presential"@en . "TRUE" . . "Observing and modelling surface water in a changing world"@en . . "7" . "no data" . . "Presential"@en . "TRUE" . . "Shades-of-blue: earth observation of coastal and inland waters"@en . . "7" . "no data" . . "Presential"@en . "TRUE" . . "Planning sustainable cities"@en . . "7" . "no data" . . "Presential"@en . "TRUE" . . "Building inclusive and competitive cities"@en . . "7" . "no data" . . "Presential"@en . "TRUE" . . "The compact city"@en . . "7" . "no data" . . "Presential"@en . "TRUE" . . "Risk-sensitive urban planning studio"@en . . "7" . "no data" . . "Presential"@en . "TRUE" . . "Systems approach for management of natural resources"@en . . "7" . "no data" . . "Presential"@en . "TRUE" . . "From data to geo-information for natural resources management"@en . . "7" . "no data" . . "Presential"@en . "TRUE" . . "Earth observation for natural resources management"@en . . "7" . "no data" . . "Presential"@en . "TRUE" . . "Environmental modelling: causes and Impacts of changing resources"@en . . "7" . "no data" . . "Presential"@en . "TRUE" . . "Data-driven hazard modelling"@en . . "7" . "no data" . . "Presential"@en . "TRUE" . . "Ntroduction to hazard and risk"@en . . "7" . "no data" . . "Presential"@en . "TRUE" . . "Physically-based hazard modelling"@en . . "7" . "no data" . . "Presential"@en . "TRUE" . . "Disaster risk management"@en . . "7" . "no data" . . "Presential"@en . "TRUE" . . "Responsible land administration"@en . . "7" . "no data" . . "Presential"@en . "TRUE" . . "Land information systems and models"@en . . "7" . "no data" . . "Presential"@en . "TRUE" . . "Cadastral data acquisition technologies and dissemination methods"@en . . "7" . "no data" . . "Presential"@en . "TRUE" . . "Organizing land information"@en . . "7" . "no data" . . "Presential"@en . "TRUE" . . "Scientific geocomputing"@en . . "7" . "You specifically learn about solution strategies, high-level solution descriptions and translations of these into an implementation in some programming language. The course’s programming language will be Python, but throughout the Geoinformatics specialization, you will learn to implement your algorithms using also other programming/scripting languages/environments.\n\nDissemination of code output is important and so we will make an excursion into the visualization of scientific outputs such as charts and maps, and web programming also.\n\nWe will discuss the scientific side of programming by an introduction into literate programming, which emphasizes documentation of code and the FAIR principles of scientific data management, which apply to data and code. We emphasize the role of data in geospatial algorithms, as these are often data-intensive. By reviewing and developing (high-level) code, you will increase your understanding of basic concepts in Geo-information Science and Earth Observation.; \"You specifically learn about solution strategies, high-level solution descriptions and translations of these into an implementation in some programming language. The course’s programming language will be Python, but throughout the Geoinformatics specialization, you will learn to implement your algorithms using also other programming/scripting languages/environments.\n\nDissemination of code output is important and so we will make an excursion into the visualization of scientific outputs such as charts and maps, and web programming also.\n\nWe will discuss the scientific side of programming by an introduction into literate programming, which emphasizes documentation of code and the FAIR principles of scientific data management, which apply to data and code. We emphasize the role of data in geospatial algorithms, as these are often data-intensive. By reviewing and developing (high-level) code, you will increase your understanding of basic concepts in Geo-information Science and Earth Observation; LO 1 \nExplain mathematical notions in algorithmics and literate programming, and apply in code development.\n\nLO 2 \nUnderstand and apply the fundamentals of programming, and express programs in properly documented code. Use of geospatial data in algorithms, amongst others, through dedicated libraries.\n\nLO 3 \nCritically evaluate program logic and correctness through read, test and debug cycles.\n\nLO 4 \nProgrammatically manipulate data containers such as plain text files, vector data sets and raster images, and program-internal containers such as arrays.\n\nLO 5 \nUse spatial databases to load, curate and otherwise manipulate data in a vector database.\n\nLO 6 \nExplain and use in code the fundamental notions of scientific data visualization.\n\nLO 7 \nExplain and use principles of web programming.\n\nLO 8 \nDevelop independent learning, critical thinking through portfolio building." . . "Presential"@en . "TRUE" . . "Acquisition and exploration of geospatial data"@en . . "7" . "no data" . . "Presential"@en . "TRUE" . . "Extraction, analysis and dissemination of geospatial information"@en . . "7" . "no data" . . "Presential"@en . "TRUE" . . "Integrated geospatial workflows"@en . . "7" . "no data" . . "Presential"@en . "TRUE" . . "Image analysis"@en . . "7" . "no data" . . "Presential"@en . "TRUE" . . "Spectral geology"@en . . "7" . "no data" . . "Presential"@en . "TRUE" . . "Spectral data processing"@en . . "7" . "no data" . . "Presential"@en . "TRUE" . . "Geological remote sensing"@en . . "7" . "no data" . . "Presential"@en . "TRUE" . . "Field measurements and validation"@en . . "7" . "no data" . . "Presential"@en . "TRUE" . . "Geospatial analysis and interpretation"@en . . "5" . "no data" . . "Presential"@en . "TRUE" . . "Geospatial data: concepts, acquisition and management"@en . . "5" . "no data" . . "Presential"@en . "TRUE" . . "Gis & rs for geospatial solutions"@en . . "4" . "no data" . . "Presential"@en . "TRUE" . . "Academic skills"@en . . "4" . "no data" . . "Presential"@en . "TRUE" . . "Global challenges, local action"@en . . "7" . "no data" . . "Presential"@en . "TRUE" . . "Water, climate and cities"@en . . "5" . "no data" . . "Presential"@en . "FALSE" . . "Weather Impact analysis"@en . . "7" . "no data" . . "Presential"@en . "FALSE" . . "Water and carbon dynamics in ecosystems"@en . . "7" . "no data" . . "Presential"@en . "FALSE" . . "Forest monitoring and carbon stock estimation with multi-source remote sensing in the context of climate change"@en . . "7" . "no data" . . "Presential"@en . "FALSE" . . "Statistics for spatial and spatio-temporal data"@en . . "7" . "no data" . . "Presential"@en . "FALSE" . . "Species distribution and environmental niche modelling"@en . . "7" . "no data" . . "Presential"@en . "FALSE" . . "Spatio-temporal analytics and modelling"@en . . "7" . "no data" . . "Presential"@en . "FALSE" . . "Laser scanning"@en . . "7" . "no data" . . "Presential"@en . "FALSE" . . "Land use and transport interaction (luti)"@en . . "7" . "no data" . . "Presential"@en . "FALSE" . . "Land governance"@en . . "7" . "no data" . . "Presential"@en . "FALSE" . . "Land change modelling"@en . . "7" . "no data" . . "Presential"@en . "FALSE" . . "Intra urban spatial patterns and processes"@en . . "7" . "no data" . . "Presential"@en . "FALSE" . . "Geophysics - Imaging the unseen"@en . . "7" . "no data" . . "Presential"@en . "FALSE" . . "Geo-health_7ec"@en . . "7" . "no data" . . "Presential"@en . "FALSE" . . "Catchment hydrology and surface water"@en . . "7" . "no data" . . "Presential"@en . "FALSE" . . "Thermal infrared remote sensing: from theory to applications"@en . . "5" . "no data" . . "Presential"@en . "FALSE" . . "Spatial analyses of ecosystem services: nature’s benefits to people"@en . . "5" . "no data" . . "Presential"@en . "FALSE" . . "Scene understanding with unmanned aerial vehicles"@en . . "5" . "no data" . . "Presential"@en . "FALSE" . . "Radar remote sensing"@en . . "5" . "no data" . . "Presential"@en . "FALSE" . . "Quantitative remote sensing of vegetation parameters"@en . . "5" . "no data" . . "Presential"@en . "FALSE" . . "Participatory planning 2: theory and application of, and learning from, pss and serious games in planning and decision processes"@en . . "5" . "no data" . . "Presential"@en . "FALSE" . . "Participatory planning 1: theory and development of pss for decision rooms, web applications and serious games"@en . . "5" . "no data" . . "Presential"@en . "FALSE" . . "Modelling multi-hazards & risk"@en . . "5" . "no data" . . "Presential"@en . "FALSE" . . "Geodata visualization"@en . . "5" . "no data" . . "Presential"@en . "FALSE" . . "Earth observation with unmanned aerial vehicles"@en . . "5" . "no data" . . "Presential"@en . "FALSE" . . "Earth observation for wetland monitoring and management"@en . . "5" . "no data" . . "Presential"@en . "FALSE" . . "Big geodata processing"@en . . "5" . "no data" . . "Presential"@en . "FALSE" . . "Space for ethics"@en . . "5" . "no data" . . "Presential"@en . "FALSE" . . "Remote sensing and modelling of primary productivity and plant growth"@en . . "5" . "no data" . . "Presential"@en . "FALSE" . . "Python solutions"@en . . "5" . "no data" . . "Presential"@en . "FALSE" . . "Local climate change planning"@en . . "5" . "no data" . . "Presential"@en . "FALSE" . . "Geo-journalism"@en . . "5" . "no data" . . "Presential"@en . "FALSE" . . "Geo-health_5ec"@en . . "5" . "no data" . . "Presential"@en . "FALSE" . . "Environmental monitoring with satellite Image time series"@en . . "5" . "no data" . . "Presential"@en . "FALSE" . . "Environmental assessment using sdss and advanced eo tools"@en . . "5" . "no data" . . "Presential"@en . "FALSE" . . "Entrepreneurship: a bridge towards geospatial innovation"@en . . "5" . "no data" . . "Presential"@en . "FALSE" . . "Digital twin earth for water, energy, and food security"@en . . "5" . "no data" . . "Presential"@en . "FALSE" . . "3d modelling for city digital twins based on geospatial information"@en . . "5" . "no data" . . "Presential"@en . "FALSE" . . "Msc research proposal and thesis writing"@en . . "45" . "no data" . . "Presential"@en . "FALSE" . . "Master of Geo-Information Science and Earth Observation"@en . . "https://www.itc.nl/education/studyfinder/geo-information-science-earth-observation/" . "120"^^ . "Presential"@en . "In this two-year, English-taught Master’s, you will learn to address the growing range of global challenges - from climate change to resources depletion and pandemic diseases - that our society and vulnerable populations across the world are facing by using geo-information systems. You will acquire the theoretical knowledge, technical skills, and big data analytics competences to find the data you need, analyse the problem at hand, visualise the data, and design an innovative and sustainable solution. With your expertise, you will contribute to improvements in the domains of food and water security, natural resources management, geo-health, climate change adaptation, urban development and smart cities, disaster risk reduction, and responsible land administration.Identify and explain principles, concepts, methods and techniques relevant for geoinformation processing and earth observation.\n2. Analyse problems and cases from a (geo-)spatial perspective.\n3. Use and design models to simulate (or: study) processes in the system earth with a\nspatial component.\n4. Apply principles, concepts, methods and techniques in the context of system earth,\nthe user and an application domain to solve scientific and practical problems.\n5. Independently design and carry out research in the domain according to scientific\nquality standards.\nScientific\n6. Analyse issues in an academic manner and formulate judgments based on this.\n7. Analyse scientific and practical domain problems in a systematic manner and\ndevelop scientifically valid solutions for these problems in a societal context.\n8. Communicate both orally and in writing on findings of research work to specialists\nand non-specialists.\n9. Explore the temporal and social context of geo-information science and technology\nand be able to integrate these insights into scientific work.\nInternationalization\n10. Explain and contrast cultural and contextual differences that influence the collection,\nclassification and visualization of spatial information.\n11. Operate professionally and ethically in a multi-cultural environment.\nGeneral\n12. Critically reflect on own and other's work.\n13. Study in a manner that is largely self-directed and autonomous."@en . . . "2"@en . "FALSE" . . "Master"@en . "Thesis" . "17000.00" . "Euro"@en . "17000.00" . "Recommended" . "Experts in geo-information systems who can acquire, analyse, and visualise geo-information to develop innovative solutions are in high demand both in the private and pubic sectors. You can work as a policy advisor, geo-information consultant, GIS analyst, geospatial data scientist, environmental management consultant, remote sensing specialist, data engineer, and more. You can also opt for a career in academia and do a PhD at any university worldwide. Or you can start your own company!"@en . "7"^^ . "TRUE" . "Downstream"@en . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .