. . "201800280" . "GFM_001" . "7"^^ . "196"^^ . "10"^^ . "2023-02-02T23:00:00Z"^^ . "f2f" . "The student should expect a course that aims to bring professional and scientific skills in computational work with geospatial data. Short but intensive lectures bring the theoretical background, which is separately examined. Extensive practicals aim for the student to learn alone but also together and to share with peers in what is learned; students will be asked to explain their problems and solutions in the practical sessions. These practicals prepare for a batch of skills tests that each student executes individually during the course. A final skills test is executed at course end.\n\nIn the post-covid19 era, we may continue to see specific requirements and conditions for education. These may impact opportunities for face-to-face exchange, which appears especially relevant for practicals supervision. We will try find ways that allow optimal exchange and discussion between supervisors and students."@en . . . . . . . . . "The course is likely to see entrants with different levels of understanding and skills in the computational (scripting/coding) domain. Its design assumes no previous scripting/coding experience, but having such will generally help. ,Sufficient understanding of the spatial data models (simple vector features, raster images) and their elements and spatial data operations as covered in the Core courses Geo-information Science and Modelling, Earth Observation and Data Integration.\n\nThe course is likely to see entrants with different levels of understanding and skills in the computational (scripting/coding) domain. Its design assumes no previous scripting/coding experience, but having such will generally help."@en . . . "1"^^ . "2" . "1B" . . . "2022-11-13T23:00:00Z"^^ . "In this course, the student learns to develop algorithmic solutions to geospatial problems. Turn-key software systems for Geo-information Science and Earth Observation are functionally powerful but have no instant solution to each geospatial problem that may arise. The ability to construct custom solutions is an essential capability of the Geoinformatics specialist, who should have competence in addressing geospatial problems by algorithmic solutions.\n\nYou 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."@en . "Scientific Geocomputing"@en . . "Scientific Geocomputing"@en . "Scientific Geocomputing"@en . . "201800302" . "GFM_005" . "7"^^ . "196"^^ . "10"^^ . "2023-07-06T22:00:00Z"^^ . "f2f" . "Students will be confronted with problems from reality in which the integration of heterogeneous data sources is key to derive meaningful information.\nThe conceptual understanding will be built by the students by creating a concept map within the Living Textbook, based on selected literature.\nAfter learning the principles (through lectures and reading papers) and applying existing tools, they will use their coding experience to create a mini SDI as a proof of concept.\nStudents will need to critically reflect in a report and in a presentation on the tools which they used and identify their potential, limitations and scalability."@en . . . . . . "EO4GEO BoK concepts {Bloom level} \n\n[GC] Geocomputation \n\nhttps://bok.eo4geo.eu/GC {3: Apply} \n\n[GD2] Data Collection \n\nhttps://bok.eo4geo.eu/GD2 {2: Understand} \n\n[AM1] Foundations of analytical methods https://bok.eo4geo.eu/AM1 {2: Understand} \n\n[DA3-4] WebGIS, SDI services, map services https://bok.eo4geo.eu/DA3-4 {2: Understand} ,Knowledge and skills as covered in the courses Scientific Geocomputing, Acquisition and Exploration of Geospatial Data and the course Extraction, Analysis and Dissemination of Geospatial Information."@en . . . "5"^^ . "4" . "2B" . . . . . . "2023-04-23T22:00:00Z"^^ . "A crucial practical demand lies in converting geodata into usable and actionable geo-information that supports decision-making at various scales and that can be further processed to generate knowledge. As a consequence, scientific workflows, semantic models and effective infrastructures become more important for knowledge sharing and ensuring reproducibility.\nThis course covers the emerging methods for meaningfully integrating geospatial data through workflows in different application contexts and connect different types of data into a spatial data infrastucture (SDI) on the Web."@en . "Integrated Geospatial Workflows"@en . . "Integrated Geospatial Workflows"@en . "Integrated Geospatial Workflows"@en . . "201800281" . "GFM_002" . "7"^^ . "196"^^ . "10"^^ . "2023-02-02T23:00:00Z"^^ . "f2f" . "This course aims to bring both scientific background and practical skills with respect to the acquisition and exploration of geospatial data. Lectures bring the theoretical background and a series of tutorials prepare students for practical work and the course's individual assignment. Extensive practicals hold a big weight to this course and are intended to facilitate individual and peer learning. Students will be asked to share the findings of their practicals and solutions to problems. Finally, students will have to work on an assignment that will cover different steps of the process from data acquisition to its final visual exploration."@en . . . . . . "Basic knowledge and skills on Geo-Information Science and Modelling, Earth Observation and Data Integration: Principles, Approaches and User perspectives.\n\nStudents entering the course should have basic programming and GIS skills and be able to select, modify and apply solution strategies implemented in some programming language (e.g., Python, C++, Matlab, R and SpatialSQL)."@en . . . "7"^^ . "2" . "1B" . "2022-11-13T23:00:00Z"^^ . "The aim of this course is to equip students with theoretical and practical knowledge on methods for spatial data acquisition and exploration, while helping them to develop critical thinking for method selection. In this course, you will use algorithmic thinking and programming skills to find, retrieve, store, and explore various geospatial datasets. In scientific research, significant time and effort goes into acquiring, understanding, and cleaning the data before the actual analysis begins. Maps and diagrams are not only used to present the final results, but also to verify and explore the data during the whole data processing process phase. After this course, you will have a good overview of acquisition and exploration of geospatial data principles and methods and be able to select the most appropriate data acquisition and exploration methods as well as working environment (among R, Python, C++ etc)."@en . "Acquistion & Exploration of Geospatial Data"@en . . "Acquis. and Expl. of Geospatial Data/Acquistion & Exploration of Geo Data"@en . "Acquistion & Exploration of Geosptial Data"@en . . "201800301" . "GFM_004" . "7"^^ . "196"^^ . "10"^^ . "2023-07-06T22:00:00Z"^^ . "f2f" . "Image analysis requires a mixture of theoretical concepts and practical skills. The subjects will be introduced in lectures and applied in practical classes. As a preparation for lectures, reading textbook material will be recommended on some subjects. In addition, on some other subjects reading research articles will be recommended after the lecture to go deeper into the subject.\nPractical classes will consist of a mixture of a demo by an instructor, individual work following written instructions and summarizing the outcome of the exercise in a class. In practical class students are supposed to work with existing programming codes and modify these (to a limited degree). In this way the students can get insight in the intermediate stages of the image analysis algorithms and make decisions on the outcomes. In these summaries reflection on theoretical concepts will be done. In this way a solid integration of theory and practice will be achieved."@en . . . . . . . "Preferably subjects as covered in the courses Scientific Geocomputing, Acquisition and Exploration of Geospatial Data and the course Extraction, Analysis and Dissemination of Geospatial Information ,Knowledge and skills in programming, linear filters, basic image classification, basic photogrammetry.\n\nPreferably subjects as covered in the courses Scientific Geocomputing, Acquisition and Exploration of Geospatial Data and the course Extraction, Analysis and Dissemination of Geospatial Information."@en . . . "6"^^ . "4" . "2B" . "2023-04-23T22:00:00Z"^^ . "In this course, you will be introduced to more advanced image analysis methods enabling to enrich your geo-information problem solving abilities. Image processing methods treated in previous courses, such as linear filters, feature based DTM production and conventional hard pixel based classification, face limitations making them insufficient for reliable geo-information extraction in automatic settings. Non-linear filters will be introduced for reduction of noise while preserving the boundaries. In addition, interest operators will be introduced to detect stable structures in images that are invariant to scale and rotation transformation. Various methods for dealing with objects in images will be studied: mathematical morphology and segmentation. Fuzzy and sub-pixel classification will be introduced to deal with uncertainty and to increase the information content extracted from the imagery. For multisource classification decision trees will be introduced. To automatically detect corresponding image positions, the image matching techniques will be introduced. In particular, area-based matching and feature-based matching will be investigated in this course."@en . "Image Analysis"@en . . "Image Analysis"@en . "Image Analysis"@en . . "201800290" . "GFM_003" . "7"^^ . "196"^^ . "10"^^ . "2023-04-20T22:00:00Z"^^ . "f2f" . "This course deepens the theoretical knowledge and practical skills regarding the extraction, analysis, and dissemination of geospatial information. Theoretical lectures and flipped-classrooms will provide students with in-depth scientific knowledge of the methods and (ungraded) supervised practical sessions will let students practice these skills. An individual assignment will test the student’s practical knowledge on Geovisualization. Key to this course is a group assignment which integrates the various concepts taught in the lectures and promotes peer-learning. Teams will work together to combine the different processes of extraction, analysis and dissemination into a single practical project. Question hours and example exams will help students prepare for the final individual exam which tests the theoretical knowledge acquired during the course."@en . . . . . . . . . "Knowledge and skills as covered in the Core courses Geo-information Science and Modelling, Earth Observation and Data Integration: Principles, Approaches and User perspectives ,Knowledge and skills as covered in the Core courses Geo-information Science and Modelling, Earth Observation and Data Integration: Principles, Approaches and User perspectives.\n\nBeing able to develop solution strategies, high-level solution descriptions in pseudo-code, and translations of these into an implementation in some programming language as covered in the course Scientific Geocomputing.\n\nKnowledge and skills with respect to geodata curation, manipulation and transformation, transformational design, mathematics, spatial data quality and cartographic design principles as covered in course Acquisition and Exploration of Geospatial data."@en . . . "1"^^ . "3" . "2A" . "2023-02-05T23:00:00Z"^^ . "This course teaches the extraction, analysis, and dissemination of information from geospatial data in an iterative approach using concrete applications. Exemplary course topics are the creation of Digital Terrain Models using photogrammetric techniques, and the visualization of the results in a 3D environment using Virtual Reality. Furthermore, you will use different map representations to visualize time series results taking uncertainty of measurements and models into account. Lastly, the design and creation of geoservices and web mapping technology will be discussed."@en . "Extraction, analysis and dissemination of geospatial information"@en . . "Extraction, analysis and dissemination of geospatial information"@en . "Extraction, analysis and dissemination of geospatial information"@en . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . "The Master’s Programme Geo-Information Science and Earth Observation (M-GEO) is a two-year academic curriculum at MSc level, taught fully in English, dedicated to understanding the earth’s systems from a geographic and spatial perspective. The field of Geo-information Science and Earth Observation has, in recent years, witnessed fast scientific and technological developments. As a result, geographic information has become a vital asset to society and part of our daily life. The ubiquitous production and availability of spatial data require cloud computing and new technology to turn the increasing volume of ‘big data’ to good use. The growing range of global challenges, from climate change and resource depletion to environmental pollution and pandemic diseases, that our society and in particular the more vulnerable populations on our planet are facing, increases the demand for academic professionals who have the ability, attitudes and skills to design solutions that are sustainable, transdisciplinary and innovative with positive societal impacts. Our education focuses on addressing these global problems by means of advanced geo-information and earth observation applications."@en . "Master’s Programme Geo-Information Science and Earth Observation (M-GEO)"@en . . "Master’s Programme Geo-Information Science and Earth Observation (M-GEO)"@en . . . "Specialisation" . "Geoinformatics"@en .