. . "202001458" . "CORE_0003" . "5"^^ . "140"^^ . "4"^^ . "2022-11-10T23:00:00Z"^^ . "f2f" . "The course mainly consists of a mix of lectures, practicals and self-study time. Lectures are used to introduce concepts and theory. The practicals provide an illustration of the introduced concepts and also allow you the develop practical skills. They consist of a supervised part, to help you start up practical activities and to discuss the results, and an unsupervised part for self-directed learning and skills development. Topics are usually finalised with plenary wrap-up sessions in which conceptual and practical issues are dealt with.\n\nExercise instructions used in the practicals are task oriented, thus requiring a more active and self-supporting attitude from you. This also helps you to prepare for the planning and execution of project assignments that you will carry out later on in the course programme at ITC. In the year 2021 we will consider QGIS as the software of choice for majority of the practicals and assignments."@en . . . . "Open for students in the Master of Science degree programme in Geo-Information Science and Earth Observation. The suitability of other candidates will be assessed on an individual basis."@en . . "14"^^ . "1" . "1A" . . . . . . "2022-09-04T22:00:00Z"^^ . "Geo-Information Systems and Science (GIS) and Earth Observation by Remote Sensing (RS) are among the main focus areas of the Faculty ITC. We concentrate on the underlying geospatial concepts that contribute to the development of technological innovations. With the help of GIS and RS we also increase our understanding of aspects of system Earth. GIS and RS help us in making contributions to solutions for global challenges, such as the dealing with effects of climate change and rapid urbanisation, and the need for a more sustainable use of our resources.\n\nThis first quartile (entitled 'GIS and RS for Geospatial Problem Solving') of your study programme at ITC consists of three interrelated courses. In these courses we aim to provide you with a general understanding about GIS and RS principles, and with hands-on experience in using software tools for handling and processing geospatial data. Apart from the geo-technological focus, the courses also challenge you in developing an attitude of using GIS and RS in dealing with geospatial problems and answering geospatial questions related to real world problems and challenges. The three courses will take you through the main stages of a geospatial problem solving cycle: from the identification of a geospatial problem and associated questions, via the acquisition, management and exploration of maps, images and other geospatial data, to the analysis and processing of images and spatial data, and eventually to the generation and communication of geospatial information needed for answering the geospatial questions."@en . "Geospatial analysis and interpretation"@en . . "Geospatial analysis and interpretation"@en . "Geospatial analysis and interpretation"@en . "Core_0003" . . "201800317" . "CORE_005" . "7"^^ . "196"^^ . "10"^^ . "2023-04-20T22:00:00Z"^^ . "f2f" . "Lectures about global challenges (processes and trends, policy frameworks, use of geo- information and earth observation, examples of local impacts)\nWorking groups to further process the information provided by the lectures/reading material through the perspective of your own discipline/project group\nSupervised project group-work to work on a specific case study (4-6 students)\nTutorials, to acquire some specific methods that students aim to use in the elaboration of the projects\nSelf-study\nExcursion or discussion with invited experts (1 per case study project)"@en . . . . . . . "None,Successful completion of the ITC course 'GIS and RS for Geospatial Problem Solving' or equivalent."@en . . "40"^^ . "3" . "2A" . . . . . . . . "2023-02-05T23:00:00Z"^^ . "Global challenges of the 21st century, as caused by or related to climate change, rapid urbanization and increased resource use cannot be simply addressed at the global level within disciplinary boundaries but require careful consideration and detailed analysis at the regional and local level and an interdisciplinary lens. In this course, we aim to increase your awareness of the urgency to address global challenges of the 21st century at multiple scales and the added value of engaging with other disciplines. Besides learning about internationally recognized key global challenges, you will further strengthen the geo-spatial and domain knowledge and skills acquired in preceding courses. You will become aware of both the added value and challenges of crossing disciplinary boundaries and recognize the contribution of your own discipline in analysing global problems and designing actions at the local level.\n\nThe course consists of two elements, moving from a multi-disciplinary to an interdisciplinary approach. The first element introduces you to a set of key global challenges which have been recognized internationally and relate to selected research themes of ITC and the educational tracks of the Master Geo-Information Science and Earth Observation. This is done by means of keynote lectures and associated working groups. The second element is an interdisciplinary and project-based investigation in multi-disciplinary groups (i.e. a region-specific case study that reflects a mix of challenges and impacts). With the group, you will analyse a global issue more in-depth and collaboratively design a response (plan, strategy, policy recommendation, etc.) at the local level. For further details see the content section."@en . "Global Challenges, Local Action"@en . . "Global Challenges, Local Action"@en . "Global Challenges, Local Action"@en . . "Core_0001" . . "GIS & RS for Geospatial Solutions"@en . "202001419" . "CORE_0001" . "4"^^ . "112"^^ . "3"^^ . "2022-11-10T23:00:00Z"^^ . "f2f" . "The first week of the course (i.e. the first week of quartile 1) consists of a series of introductory presentations, group assignments and plenary discussions. In the last two weeks of the course (i.e. weeks 9 and 10 of quartile 1) you will carry out an individual project assignment."@en . . . . "Courses CORE_002 and CORE_003 are corequisite. Compulsory for students in the Master of Science degree programme in Geo-Information Science and Earth Observation. The suitability of other candidates is assessed on an individual basis. The main assessment of the course is dependent on skills obtained in courses 2 and 3 of the core. ,Open for students in the Master of Science degree programme in Geo-Information Science and Earth Observation. The suitability of other candidates will be assessed on an individual basis."@en . . . . . . . . "18"^^ . "1" . "1A" . . "2022-09-04T22:00:00Z"^^ . "Geo-Information Systems and Science (GIS) and Earth Observation by Remote Sensing (RS) are among the main focus areas of the Faculty ITC. We concentrate on the underlying geospatial concepts that contribute to the development of technological innovations. With the help of GIS and RS we also increase our understanding of aspects of system Earth. GIS and RS help us in making contributions to solutions for global challenges, such as the dealing with effects of climate change and rapid urbanisation, and the need for a more sustainable use of our resources.\n\nThis first quartile (entitled 'GIS and RS for Geospatial Problem Solving') of your study programme at ITC consists of three interrelated courses. In these courses we aim to provide you with a general understanding about GIS and RS principles, and with hands-on experience in using software tools for handling and processing geospatial data. Apart from the geo-technological focus, the courses also challenge you in developing an attitude of using GIS and RS in dealing with geospatial problems and answering geospatial questions related to real world problems and challenges. The three courses will take you through the main stages of a geospatial problem solving cycle: from the identification of a geospatial problem and associated questions, via the acquisition, management and exploration of maps, images and other geospatial data, to the analysis and processing of images and spatial data, and eventually to the generation and communication of geospatial information needed for answering the geospatial questions."@en . "GIS & RS for Geospatial Solutions"@en . "GIS & RS for Geospatial Solutions"@en . . "202001457" . "CORE_0002" . "5"^^ . "140"^^ . "3"^^ . "2022-11-10T23:00:00Z"^^ . "f2f" . "The course mainly consists of a mix of lectures, practicals and self-study time. Main topics' concepts and theory are briefly introduced through lectures which are usually scheduled in the morning. The subsequent practicals provide an illustration of the introduced concepts to increase understanding and also allow participants to develop practical skills. They consist of a supervised part, to help participants to start up practical activities and to discuss the intermediate results, and an unsupervised part for self-directed learning and skills development. Topics are usually finalised with plenary wrap-up sessions in the afternoon in which conceptual and practical issues that emerged from the lecture and practical are dealt with. Questions which arise at other later moments can be issued to the online discussion fora. Fellow students are encouraged to help solving the issues with moderation of the responsible lecturer.\n\nOver time the practical instructions become less instructive and more task oriented, thus requiring a more active and self-supporting attitude from participants. This also helps to prepare for the planning and execution of the project assignments that you will carry out later on in the programme at ITC. Most pratical exercises will have a generic nature with specific instructions for QGIS. Alternatives can be available for ArcGIS and ERDAS."@en . . . . . . "Compulsory course for students in the Master of Science degree programme in Geo-Information Science and Earth Observation. The suitability of other candidates will be assessed on an individual basis."@en . . . . . . . . . . "13"^^ . "1" . "1A" . "2022-09-04T22:00:00Z"^^ . "Geo-Information Systems and Science (GIS) and Earth Observation by Remote Sensing (RS) are among the main focus areas of the Faculty ITC. We concentrate on the underlying geospatial concepts that contribute to the development of technological innovations. With the help of GIS and RS we also increase our understanding of aspects of system Earth. GIS and RS help us in making contributions to solutions for global challenges, such as the dealing with effects of climate change and rapid urbanisation, and the need for a more sustainable use of our resources.\n\nThis first quartile (entitled 'GIS and RS for Geospatial Problem Solving') of your study programme at ITC consists of three interrelated courses. In these courses we aim to provide you with a general understanding about GIS and RS principles, and with hands-on experience in using software tools for handling and processing geospatial data. Apart from the geo-technological focus, the courses also challenge you in developing an attitude of using GIS and RS in dealing with geospatial problems and answering geospatial questions related to real world problems and challenges. The three courses will take you through the main stages of a geospatial problem solving cycle: from the identification of a geospatial problem and associated questions, via the acquisition, management and exploration of maps, images and other geospatial data, to the analysis and processing of images and spatial data, and eventually to the generation and communication of geospatial information needed for answering the geospatial questions."@en . "Geospatial data: concepts, acquisition and management"@en . . "Geospatial data: concepts, acquisition and management"@en . "Geospatial data: concepts, acquisition and management"@en . "Core_0002" . . "201800271" . "CORE_004" . "4"^^ . "112"^^ . "40"^^ . "2023-07-06T22:00:00Z"^^ . "f2f" . "Teaching and learning involves a mix of different types of activities, including plenary lectures, tutorials, peer-review sessions and self-study. Active participation and critical reflection are stimulated."@en . . . . . . "Open for students in the Master of Science degree programme in Geo-Information Science and Earth Observation. The suitability of other candidates will be assessed on an individual basis. ,As for entry to the programme."@en . . "1"^^ . "1-4" . "1A-2B" . . . . . . . "2022-09-04T22:00:00Z"^^ . "This course provides students with the foundational knowledge and skills required to undertake scientific research in their chosen domain within Geo-information Science and Earth Observation. The course combines an understanding of important conceptual issues in scientific research with skills for designing and executing an individual research project. A critical, scientific attitude and the ability to reflect upon their own work and that of others will be developed."@en . "Academic Skills"@en . . "Academic Skills"@en . "Academic Skills"@en . . "202001426" . "PGM_0007" . "5"^^ . "140"^^ . "10"^^ . "2023-02-02T23:00:00Z"^^ . "online" . "The students will work in a project-oriented style on their topic and in their case studies. This can include literature research, questionnaires, interviews with related case study staff. The findings will be presented in a mid-term presentation and summarized in a final report. The main and broad goal of the course is to develop comparative information on a particular topic within the broader realm of \"local climate planning for carbon neutrality\" and \"integrating western and indigenous knowledge systems in climate planning” in order to allow cities to learn from comparative cases and better plan for climate change. This can be based on best cases (or worse cases too).\n\nThis will include:\n\nLectures,\nWritten individual exam,\nWritten individual assignment,\nGroup report,\nGroup presentation,\nSelf-study."@en . . . . . . . . . "2"^^ . "2" . "1B " . . . "2022-11-13T23:00:00Z"^^ . "Climate Change is one of the greatest societal challenges of this century, as recently estimated by the nearly 1,000 experts interviewed for the World Risk Report. Urban areas are pivotal to global adaptation and mitigation efforts as cities are responsible for substantial amounts of greenhouse gases emissions and particularly vulnerable to climate hazards due to their high density of people, assets, and infrastructure. But how do cities currently perform? And, how can cities actually plan for successful climate change mitigation and adaptation?\n\nIn this year we look at two focal topics: 1) Mitigation: the 100 Climate Neutral and Smart Cities Initiative of the EU; 2) Adaptation: how cities across the world can integrate indigenous knowledge/ information/ land processes into the (more) formal Local Climate Change Planning procedures?\n\nThis course shortly highlights the main processes and agreements of climate policy and governance at the global level (Paris Agreement, etc.) and then introduces in brief the theory and practice of Local Climate Change Planning (along the book: https://islandpress.org/books/local-climate-action-planning). Michael Boswell, the author of the book, will be part of our staff in this course this year).\n\nStudents will then choose to either work more deeply on mitigation or adaptation.\n\nWhen choosing mitigation students will study the EU Climate-Neutral and Smart Cities by 2030 Initiative (https://ec.europa.eu/regional_policy/en/newsroom/news/2022/05/05-06-2022-discover-the-100-cities-selected-for-the-cities-mission) and study related information on carbon neutrality in the two recently published IPCC reports. They will then work on how to achieve carbon neutrality through better planning & its implementation.\n\nWhen choosing adaptation students will review indigenous knowledge literature including but limited to the two recently published IPCC reports & work on its integration with (more) formal western knowledge. \n\nStudents will choose 2 case studies to address their topic in the practical work."@en . "Local Climate Change Planning"@en . . "Local Climate Change Planning"@en . "Local Climate Change Planning"@en . . "201900059" . "GIP_0002" . "5"^^ . "140"^^ . "10"^^ . "2022-11-10T23:00:00Z"^^ . "f2f" . "The lectures provided seek to raise a theoretical and practical understanding of how to analyse, design, implement, and evaluate visualizations. The lectures are complemented by practicals, in which the participants work on group and individual assignments to consolidate what they have learned in practice."@en . . . . . . "No particular ones; this has already been announced in the official information provided to the students, Of course, it requires a permission to some study programme, interest in these topics, etc.,No formal ones."@en . . . . . . . . "3"^^ . "1" . "1A " . "2022-09-04T22:00:00Z"^^ . "This course Geodata Visualization covers aspects of geovisual analytics, in particular, with respect to time series of movement data of people, animals, and goods. The objective of this course is to learn how to prepare and integrate, transform, and visually analyse the data to reveal spatio-temporal patterns and trends. Participants will, based on the methods introduced, develop visual environments for answering questions related to a real-world scenario. These visual environments will combine interactive and dynamic map and diagram displays with a focus on user-centred design."@en . "Geodata Visualization"@en . . "Geodata Visualization"@en . "Geodata Visualization"@en . . "202100310" . "EOS_0002" . "7"^^ . "196"^^ . "10"^^ . "2023-07-06T22:00:00Z"^^ . "online" . "Readings: lecture notes and readings,\n\nWeekly quizzes, discussions and projects.\n\nInteractive peer-review\n\nIndividual term project where the student selects a topic and use what they learn during the course to the topic."@en . . . . . . . . . . . "Students should have some data science, statistics background. GIS and remote sensing background is a benefit. This course is currently an elective with the aim to be the first course in the geohealth specialization. ,All students in Geoinformatics specialization are accepted. Students following other specializations should have a background in one or more of the following: data science, epidemiology, statistics, health sciences or public health."@en . . . . . . . . . . . "4"^^ . "4" . "2B " . . . . . . . "2023-04-23T22:00:00Z"^^ . "Geohealth integrates epidemiology with spatial data science. During the course students will be introduced to different spatial analysis methods, spatial data science methods and spatial concepts useful for the analysis of health and disease. These include the collection and use of geographic information, mapping of disease incidence and understanding where, when, why and how disease incidences may be occurring."@en . "Geo-Health 2"@en . . "Geo-Health 2"@en . "Geo-Health 2"@en . "EOS_0001" . "GeoHealth Course"@en . . "201900069" . "AES_0005" . "5"^^ . "140"^^ . "10"^^ . "2023-02-02T23:00:00Z"^^ . "f2f" . "The course has an overall distance learning setup, supported by regular tutorial- and 'Question&Answer'-sessions. Students will spend most of the course on self-study of course materials and on individual project work. This project work will involve the planning, running and documenting of a scripting/programming assignment."@en . . . . . . . "Open for students with basic programming skills and affinity with handling large spatial-temporal data sets.\n\nGFM students are excluded from this course as GFM has its own courses in programming!"@en . . . "3"^^ . "2" . "1B " . "2022-11-13T23:00:00Z"^^ . "Standard geo-data processing can be done using standard functionality offered by standard software tools. But for the solving of complex spatial-temporal problems in earth and environmental research often the handling of (very) large and complex data sets is required. This typically asks for special geoprocessing solutions.\nThis course teaches students how to plan and carry out their own programming or scripting project, to support the processing, visualization and analysis of large and complex data sets in their MSc research phase. During the course, students will work on their own geoprocessing challenge, in their own application field and using their own research data\n\nEmphasis is on scientific computing using the programming (and scripting) language Python. Depending on student interest, other modern programming languages may be considered as well. In a similar manner, tools for the design of Graphical User-Interfaces (GUI) will be considered, which will allow building interactive windows containing buttons, text boxes, graphs, maps etc.\n\nSpecial attention will be given to available statistical and scientific packages for mathematics, science and engineering, such as array processing, linear algebra, regression, optimization, classification, clustering and machine learning.\n\nThe course intends to support individual students in programming solutions that they need during their MSc research. Therefore, certain flexibility is offered to students when to start the course."@en . "Python Solutions"@en . . "Python Solutions"@en . "Python Solutions"@en . . "201900048" . "LAB_0002" . "1"^^ . "28"^^ . "2"^^ . "f2f" . . . . . "Open for students who have successfully completed the ‘General Laboratory Skills’ training course."@en . . . "1"^^ . "This course can only be followed after the general lab skills training has been successfully completed.\n\nThis training course is provided when the student needs to use a range of techniques which are not offered in the other two supplementary laboratory analysis skills (mineral and organic analysis).\n\nThe student is welcome to bring a plan to support his/her MSc phase research. With the approval of the course coordinator we can make a custom made elective that covers all the techniques necessary to support or validate the student's research.\n\nAlso in this course, the student will learn how to perform statistical analysis on the results of lab experiments, and how to convert received data to the required concentrations. Throughout the course the student will be challenged to continuously monitor the quality of your experiments."@en . "Laboratory Skills: Custom made"@en . . "Laboratory Skills: Custom made"@en . "Laboratory Skills: Custom made"@en . . "201800313" . "WRS_0005" . "7"^^ . "196"^^ . "10"^^ . "2023-07-06T22:00:00Z"^^ . "f2f" . "Learning outcomes 1, 2, 3: Participatory teaching with targeted individual assignments\nLearning outcome 4: Tutorial training and supervised practical\nLearning outcome 5: Group work supervision, question & answer sessions"@en . . . . . . . . "4"^^ . "4" . "2B " . "2023-04-23T22:00:00Z"^^ . "This course will focus on the combined use of satellite and in-situ observations and models for environmental monitoring of terrestrial and aquatic ecosystems. Current satellite and data technology permit observation and quantification of energy and water cycle components. Carbon, primary productivity in ecosystems and greenhouse gas emissions can also be monitored from space. The course will address the challenge of understanding how energy, water and carbon cycles interact and are coupled in ecosystems and at the boundaries between land, water, and atmosphere. Methods for retrieval of radiation, water and biogeochemical variables from satellite data will be reviewed, and an introduction to the use and evaluation of currently available satellite data related to the water, energy and the biogeochemical (BGC) cycles will be given.\nSimulation models of soil - vegetation (e.g. agriculture) and aquatic systems (e.g., lakes, wetlands and coastal zones) will be used for analysis, interpretation and systems modelling of water, energy and biogeochemical processes. Field work and visits to one or more of ITC’s in-situ monitoring sites (in urban, forest, coastal estuarine, and marine locations) are foreseen."@en . "Water and Carbon Dynamics in Ecosystems"@en . . "Water and Carbon Dynamics in Ecosystems"@en . "Water and Carbon Dynamics in Ecosystems"@en . . "201900064" . "GIP_0001" . "5"^^ . "140"^^ . "10"^^ . "2022-11-10T23:00:00Z"^^ . "f2f" . "online" . "In this course, students will learn the fundamentals of big geodata processing. Then, they will be introduced (via lectures, demos and exercises) to various distributed big data solutions as well as the role of cloud computing. After that, they will work on a real-life problem involving a big geo-dataset. They will work in groups and create the necessary workflows to process the data. This requires programming skills and critical thinking to select the \"best\" algorithm and computational solution.\n\nIn this course, there will also be a strong emphasis on Open Science principles, with a focus on scientific reproducibility and triangulation. Lectures on archiving data and code will be provided too."@en . . . . . . . "Basic Programming skills ,The knowledge gained during the Scientific Geocomputing course is advantageous but not strictly necessary to follow this course. Some self-study material will be provided through Canvas for students that do not follow the Geoinformatics specialisation. You are advised to contact the course coordinator to discuss the materials' relevance for you."@en . . . . . . . . . "3"^^ . "1" . "1A " . . "2022-09-04T22:00:00Z"^^ . "Thanks to the digital, mobile and sensor revolutions, massive amounts of data are becoming available at unprecedented spatial, temporal, and thematic scales. This leads to the practical problem of transforming big geodatasets into actionable information that can support a variety of decision-making processes. In this respect, geodata science workflows are not only key to processing big geospatial datasets but also to sharing the extracted information and knowledge and to ensuring the reproducibility of the results.\n\nTo handle and analyse massive and potentially heterogeneous amounts of spatio-temporal data, scientists need to 1) understand the particular characteristics of big geodata, 2) learn to work with scalable data management and processing systems, and 3) develop scalable and robust data mining and machine learning workflows. Hence, this course presents theories, methods, and techniques to build scalable solutions for handling and analysing big geodata."@en . "Big Geodata Processing"@en . . "Big Geodata Processing"@en . "Big Geodata Processing"@en . . "201800319" . "NRS_0006" . "7"^^ . "196"^^ . "10"^^ . "2023-07-06T22:00:00Z"^^ . "f2f" . "The course will start with describing climate change and the role of forests to mitigate it. It will show how forest sequester carbon and control global warming. Students work on a small group project where they define a REDD+ project for a specific country. Then in lectures biomass/ carbon stock will be introduced as well as methods to assess that using various remotely sensed data such as optical satellite and airborne images, UAV, Lidar and Radar data. The students will practice on different types of real life case studies using various types of remotely sensed data to assess and map biomass and carbon stock in difference forest ecosystems. The course will also model carbon sequestration by using case studies dealing with multi-temporal remotely sensed data. Theory of fire and fire spreading will be explained in order to understand how fire behavior affects carbon emission and climate change and students practice during a case study\n\n \n\nThe course will end with a small group project where students evaluate different tools and techniques for the project they specified in the first week."@en . . . . . . . . "GIS and Remote sensing skills"@en . . . "3"^^ . "4" . "2B " . "2023-04-23T22:00:00Z"^^ . "The greenhouse effects and the carbon cycle, in particular carbon emissions and carbon sequestration, are at the heart of climate change, one of the most pressing challenges the earth is facing. Global institutions like the UNFCCC, and IPCC all address these challenges, resulting in initiatives to reduce carbon emissions, such as Kyoto protocol.\nThis establishes an explicit link with the International Environmental Agenda and Sustainable Development Goals.\n\n \n\nFor identification and development of policy instruments in order to handle the impacts of the foreseeable changes in the carbon cycle, accurate quantification of the various components in the carbon cycle forms a core need. Moreover, for the mitigation of adverse climate effects and, in the end, sustainability of livelihoods in many parts of the earth sound assessment and monitoring tools are required.\n\n \n\nWithin the carbon cycle, forestry in the broad sense forms the principal scientific area for research including, stocks emissions (sources) and sequestration (sinks). Afforestation, reforestation and deforestation are the current Kyoto focal areas, but sustainable forest management, including certification, and the assessment and prevention of forest degradation are also considered in the so-called post-Kyoto period. Due to size, inaccessibility of the forest resources, and international requirements for a uniform methodology of Monitoring, Reporting and Verification (MRV), quantification of the carbon cycle components in both space and time leans heavily on remote sensing, GIS modelling and related statistical tools."@en . "The Role of Forests in Climate Change Mitigation"@en . . "Role of Forests in Climate Change Mit."@en . "Role of Forests in Climate Change Mit."@en . . "201900142" . "PGM_0005" . "5"^^ . "140"^^ . "10"^^ . "2023-07-06T22:00:00Z"^^ . "f2f" . "Active participation, critical reflection, oral presentation. In addition to lectures and practical assignments, the learning of course concepts is complemented with paper discussion sessions, where students are expected to lead a paper discussion session, position their views about different research articles, and activate their peers with points for discussion. The staff act as observers."@en . . . . . "GIS, Ability to independently apply GIS software. Knowledge of GIS at the level of ITC Core courses or higher is preferred. At Q1 a course on \"GIS for transport\" is offered to CEM students and exchange students as an introductory course to GIS.,Ability to independently apply GIS software. Knowledge of GIS at the level of ITC Core courses or higher is preferred. At Q1 a course on \"GIS for transport\" is offered to CEM students and exchange students as an introductory course to GIS."@en . . . . . . . "5"^^ . "4" . "2B " . . "2023-04-23T22:00:00Z"^^ . "The interaction between land use and transport is complex, multifaceted, and dynamic. Land use development influences transport-related decisions/behavior and transport decisions influence where, when, and how land development takes place.\n\nIn this course, key theories that underlie land use transport interaction are discussed, along with their modeling foundations. Special attention is given to spatial interaction theory, which is of relevance to the study of optimal service locations, accessibility analysis at various levels of detail, simulation, and forecasting, and can also be used to optimize and manage network throughput.\n\nThis course covers important modeling foundations of networks and spatial interaction as a basis for accessibility analysis in GIS.\n\nStudents will conduct a scenario study and examine the land use, mobility, and accessibility impacts of land use and transport policy strategies, using GIS-based land-use/transport interaction measures for the Netherlands.\n\nThe course will be offered to ITC students and CEM students as part of a joint-teaching collaboration between Faculties ITC (UPM) and ET (CEM). Please note that all elective courses at ITC are 7 EC, while the elective courses at ET are 5 EC. "@en . "Land Use and Transport Interaction 1"@en . . "Land Use and Transport Interaction 1"@en . "Land Use and Transport Interaction 1"@en . . "201800315" . "EOS_0008" . "7"^^ . "196"^^ . "10"^^ . "2023-07-06T22:00:00Z"^^ . "online" . "The delivery of this course is partitioned into two: teaching, which embodies lectures, feedback, and Q&A sessions. There are feedback sessions 15 minutes before the start of every days’ lecture except day 1. These involve presentations delivered by students (in groups) followed by “questions” from their colleagues. The objective is to ensure students have control over the subject and also develop/encourage the skills to work in multinational groups. The groups are predefined (by myself) to avoid biases to ensure internationalization.\n\nThe Q&A sessions are ensured after each lecture. Here, the students are encouraged to ask questions or share their experiences pertaining to the topic. \n\nTutorial sessions are critical to this course as they offer the opportunity to practice the theory in the class. The tutorials for the first three topics are designed to be supervised; the remaining are unsupervised. The reason being that after the three supervised tutorials students would have gained enough skills and experience to advance student-centered learning.\n\nCritical to the design of this course is the mapping exercise and the mini-projects which take 10 and 40 percent of the assessment, respectively. The mapping exercise is to ensure that students can take basic instructions per the materials developed. The mini-project is designed to primarily ensure that students “gain experience and understanding to design and setup a space-time data modelling problem, identity measurable objectives, the modelling ideas in the R statistical software”."@en . . . . . . . . "In this course, students are required to have basic knowledge of descriptive and inferential statistics. Basic knowledge of the R statistical software will be an added advantage,In this course, students are required to have basic knowldge of descriptive and inferential statistics. Basic knowledge of the R statistical software will be an added advantage "@en . . . . . . . . . . . . . . "2"^^ . "4" . "2B " . . "2023-04-23T22:00:00Z"^^ . "The premise of the course is motivated by the recent advancements in geoinformation data acquisition and storage and their intended use for evidence-based planning and monitoring. The spatial references of geo-information data may be attributed to the exact locations of measurements or over a fixed set of contiguous regions or lattices. This course seeks to handle the three main classes of spatial data/processes: geostatistical data/spatially continuous process, lattice data/discrete process, and point pattern data/point process. Such data appear common in diverse application fields like environmental science, agriculture, natural resources, environmental epidemiology, and so on. The aim is to present methods that can be used to explore and model such data. Naturally, data vary in space and in time; hence data close to each other (either in space or time) are more similar than those farther. Geostatistical modeling based on the semivariance and/or covariances and interpolation (kriging) in space and time will therefore be introduced. The methods will be extended and applied to data aggregated over contagious regions. The uncertainty is quantified, and attention will be given to making maps showing the probabilities that thresholds are exceeded. Attention is also given to optimal sampling and monitoring. Further, data that arise out of the occurrences of events; thus point pattern data will be considered. The significance of exploring the first and second-order properties of point patterns in diverse application domains like environmental and disaster (like earthquakes) modeling will be explained and applied. The last focus will be on lattice data; in principle, this kind of data consists of observed values over a set of fixed contiguous regions. This kind of data is rather easy to acquire and is mostly applied in health studies where data aggregation is a standard form of protecting locational privacy."@en . "Statistics Spatial & Spatio-temporal Data"@en . . "Statistics Spatial&Spatio-temp. Data"@en . "Statistics Spatial&Spatio-temp. Data"@en . . "202100001" . "EOS_0001" . "5"^^ . "140"^^ . "10"^^ . "2023-02-02T23:00:00Z"^^ . "online" . "Readings: lecture notes and readings,\n\nWeekly quizzes, discussions and projects.\n\nInteractive peer-review\n\nIndividual term project where the student selects a topic and use what they learn during the course to the topic."@en . . . . . . . . . . . "Students should have some data science, statistics background. GIS and remote sensing background is a benefit. This course is currently an elective with the aim to be the first course in the geohealth specialization. ,All students in Geoinformatics specialization are accepted. Students following other specializations should have a background in one or more of the following: data science, epidemiology, statistics, health sciences or public health."@en . . . . . . . . . . "4"^^ . "2" . "1B " . . . . . . . "2022-11-13T23:00:00Z"^^ . "Geohealth integrates epidemiology with spatial data science. During the course students will be introduced to different spatial analysis methods, spatial data science methods and spatial concepts useful for the analysis of health and disease. These include the collection and use of geographic information, mapping of disease incidence and understanding where, when, why and how disease incidences may be occurring."@en . "Geo-Health 1"@en . . "Geo-Health 1"@en . "Geo-Health 1"@en . . "202200017" . "NRS_0002" . "5"^^ . "140"^^ . "10"^^ . "2022-11-10T23:00:00Z"^^ . "f2f" . "online" . "The course takes a student-centered (inquiry-based) approach to teaching and learning. Students assume an active/participatory role in their education, while teachers are facilitators who encourage interaction with new material presented and reflective thinking. The teacher uses class discussions, hands-on practicals and other experiential learning tools to track student comprehension, learning needs and academic progress over a teaching unit. Four summative assessments (writing assignment×2 + written test + final group project) measure how well the students achieve higher order thinking and learning outcomes."@en . . . . . "Geo-Information Science and Earth Observation: A Systems-Based Approach\nEarth Observation for Natural Resources Management (or equivalent)"@en . . . "4"^^ . "1" . "1B " . "2022-09-04T22:00:00Z"^^ . "The 21st century has witnessed an increase in the availability and use of satellite images to capture changes in landscape patterns through time. You may have already been exposed to classical change detection analysis, which is a type of monitoring in which changes in landscape patterns are quantified from satellite imagery between few snapshots in time. Change detection analysis in this way is insufficient however when the processes under investigation are highly dynamic, e.g., crop rotation and ecosystem disturbances/recovery. Such cases require continuous monitoring of satellite images at frequent intervals with time series analysis (TSA). Continuous satellite image data, referred to as Satellite Image Time Series (SITS) in this course, are used to monitor dynamic processes. Ecological indicators derived from SITS capture landscape patterns consistently at frequent intervals, which enable researchers and practioners alike to detect both abrupt or seasonal changes and gradual trends over time. In addition, SITS spanning long periods of time, provide insights into the “drivers of change” and underlying mechanisms governing change. Several satellite image archives are now publicly available with the emergence of relatively inexpensive high-performance cloud computing platforms. Each archive presents unique challenges in terms of acquisition and processing. At the same time, TSA encompasses an array of quantitative approaches to monitor and forecast ecological indicators derived from SITS. These include among others, autoregressive (AR), moving average (MA) and autoregressive moving average (ARMA) models.\n\nThe number of SITS and methods for TSA can make environmental monitoring with Earth observation data a daunting task. The overall goal of this course therefore is to provide participants with sufficient knowledge and tools to acquire and process SITS, perform TSA on ecological indicators derived from SITS and design a successful environmental monitoring solution.\n\nWe begin the course with a review of key terms and concepts in environmental monitoring with Earth observation. These include: landscape patterns, pattern-generating processes and process interactions. The course continues with the exploitation of SITS to identify eco-physiological traits (ecological indicators) that can be used to monitor landscape patterns through time. With this foundation, we enter the nuts and bolts of the course: how to acquire, process, analyze and evaluate SITS for environmental monitoring. We use the Google Earth Engine cloud computing platform, Breaks For Additive Season and Trend (BFAST) algorithm and Box–Jenkins method for TSA at these stages. Google Earth Engine is a freely-available, convenient and widely used platform to acquire and process SITS. BFAST is an intuitive and widely used algorithm to decompose ecological indicators derived from SITS based on trend, seasonality, cyclical irregularity and structural changes. Box–Jenkins is a classical and systematic method for constructing ARMA models for retrospective time series analysis and forecasting. The ARMA process consists of five stages: (i) model identification; (ii) model estimation; (iii) model validation; (iv) forecasting; and (v) forecasting evaluation. You will then apply your new knowledge and skills to two case studies. The first case study deals with ecosystem detecting tipping points with the time series segmentation tool Landtrendr. The second case study involves modelling and forecasting crop rotations with AR models. Each case study links a problem to an ecological indicator, SITS and method for TSA. For the remainder of the course, participants will form groups to design and execute their own small environmental monitoring solution. Each group will present their findings to the entire class at the end of the course."@en . "Environmental Monitoring with Satellite Image Time Serie"@en . . "Env Moni with Satellite Image Time Serie"@en . "Env Moni with Satellite Image Time Serie"@en . . "201900055" . "PGM_0008" . "5"^^ . "140"^^ . "10"^^ . "f2f" . . . . . "This course requires students from any university to have successfully completed the first year of their MSc degree including the GIS, geo-databases, and possibly Remote Sensing courses. \n\nNOTE: The minimum number of participants is 8 students and the maximum number of students is 18 due to a co-design group assignment."@en . . . "4"^^ . "Spatial planning and decision-making processes occur in any domain, be it urban or rural areas, management of natural and water resources, distribution of welfare, wellbeing and risk, adaptation to climate change, or energy transition. They involve stakeholders in civil society, private sector, public administration and government, which hold different interests, norms, values, and knowledge as well as different practices and strategies of dealing with planning, decision-making and conflicts. Information and information systems do not capture the normative and collaborative/participative aspects of these processes whereas Planning Support Systems (PSS) and Spatial Decision Support Systems (SDSS) do.\n\nYou can either study theory and methods about (participatory) development of geo-technologies for participatory planning or theory and methods about the use of these technologies in planning and decision-making processes. This course is the first of two courses and addresses the former study. It focuses on theory, methods and technologies that participatory development of PSS and SDSS to support spatial planning and decision-making. The second course focuses on theory and methods of processes of participation and learning while using spatial information and moderation of PSS and SDSS in spatial planning and decision-making."@en . "Participatory Planning 1: Theory and Development of PSS for Decision Rooms, Web Applications and Serious Games"@en . . "Participatory Planning 1"@en . "Participatory Planning 1"@en . . "201900002" . "INT_0001" . "10"^^ . "280"^^ . "10"^^ . "2023-07-06T22:00:00Z"^^ . "Active participation and critical reflection are embedded in a challenge-based learning approach.\n\nParticipation and attendance:\n\nDue to educational activities that require active involvement (e.g. group presentations), the lecturer may demand mandatory attendance during lectures or parts thereof.\nThe course coordinator will communicate this at the start of the course."@en . . . . . "Approved study plan for the second academic year\nMSc Research proposal has been approved\nApproved Internship Project Plan\nIPP & Internship Agreement signed by the student, the host organization and the faculty ITC\nIMPORTANT:\n\nWhether an internship is possible in a certain country could depend on scholarship conditions. As these are different for each scholarship provider, the internship coordinator should be consulted to provide clarity on this issue. "@en . . . "1-4" . "1A-2B " . "2022-09-04T22:00:00Z"^^ . "The internship is defined as a credit-bearing experiential activity in a professional work environment. Its main purpose is to integrate knowledge and theory with practical applications and skill development in a host organization.\n\nThe internship may be carried out within consultant companies, government agencies, research institutes, NGOs or intergovernmental organisations in the Netherlands or abroad. ITC has a working relation and has made agreements on the possible placement of interns with these organisations. The student will be able to apply for an internship topic based to interests and preferences, and will develop this topic into an internship project plan (IPP) prior to the start of the internship. During the internship, the student will receive guidance from a daily supervisor in the organisation concerned. A member of the ITC scientific staff who is an expert on the area of the internship topic will be assigned as ITC internship supervisor. At the end of the internship, the student will have to hand in several deliverables such as an internship report (IR) and an internship reflection report (IRR) report in which the results experiences will be discussed and highlight the learning that has been achieved during the internship. The supervisor of the host organization will give feedback on the professional skills using the Host Evaluation Form (HEF).\n\nStudents choosing to carry out internships will have the opportunity to:\n\nDevelop a working knowledge in the operationalization of geo-information science;\nLearn new practical skills and gain confidence in entrepreneurial and professional settings;\nPractice communication and teamwork skills;\nEstablish a network of professionals;\nBoost their career prospects;\nBecome a more motivated life-long learner."@en . "Internship"@en . . "Internship"@en . "Internship"@en . . "201900057" . "NRS_0009" . "5"^^ . "140"^^ . "10"^^ . "2022-11-10T23:00:00Z"^^ . "f2f" . "Concept, theories, models are introduced to the student with lectures. The lectures followed by (un)supervised practicals to gain hands-one experience. A day is closed with plenary question-and-answer and discussion sessions to share thoughts, insights and doubts. To gain and practice professional implementation of course topic a guest lecture is given by a practitioner, we go outside, and students will solve a real-life challenge. There is a lot of time for self-study to read and do the exercises, informal quizzes, and the assignment. "@en . . . . . . . "ITC-M-GEO students: Completion of core courses; strong interest in interdisciplinary work. Other students: Able to independently use GIS software; strong interest in interdisciplinary work.,ITC-M-GEO students: Completion of core courses; strong interest in interdisciplinary work\nOther students: Able to independently use GIS software; strong interest in interdisciplinary work"@en . . . . . . . . "4"^^ . "1" . "1A " . . . . . "2022-09-04T22:00:00Z"^^ . "This elective is given by NRM, UPM and GFM staff.\n\nEcosystem services i.e., the contributions of nature to human well-being, are increasingly used to describe human-nature interactions in an inclusive way. The ecosystem services concept addresses management objectives that go beyond natural resources or human practices alone, as it focuses on the interactions between nature and society. Geo-information (from earth observation, citizen science, to existing GIS maps) is inherent to ecosystem service assessments since the supply (from ecosystems) and demand (from society) for ecosystem services are spatially explicit. Understanding the ecosystem service concept, selecting and using mapping methods for specific management objectives is therefore essential for incorporating human-nature interactions into environmental management from cities to rural areas and hence the key objective of this course. Managing natural resources in a sustainable way by taking into account human well-being is also at the core of the Sustainable Development Goals as set by the United Nations. After completing this course, the student will have obtained knowledge in the theoretical aspects of the concept of ecosystem services. The student will also be able to select and apply mapping methods and data for ecosystem service assessments on real-life applications in the context of diverse management objectives."@en . "Spatial Analyses: Nature's Benefits to People"@en . . "Spt. Anlyses:nature’s benefits to people"@en . "Spt. Anlyses:nature’s benefits to people"@en . . "201900054" . "RES_0001" . "45"^^ . "1260"^^ . "40"^^ . "2023-07-06T22:00:00Z"^^ . "Academic skills training is offered to students in the first academic year. MSc research classes in the second academic year build on this first-year course. Each research theme can also offer additional research support activities (e.g. specific survey techniques). The research projects or research support activities can be inter-disciplinary.\n\nStudents are assigned a supervisor or team of supervisors to guide them during their individual research. Students will make individual arrangements with their supervisor(s) regarding the frequency of supervision meetings and the extent of the guidance they can expect. An elaborate explanation about MSc proposal and thesis writing supervision is available in Canvas."@en . . . . . . . "To present an MSc research proposal:\n\nAt least 46 EC worth of courses of year 1 (including 4EC academic skills) must have been successfully completed.\nStudents not meeting the above-mentioned entry requirements are allowed to attend the MSc research classes in the second academic year. Supervised MSc thesis writing can only start after a successful MSc proposal defence."@en . . . "1-4" . "1A-2B " . "2022-09-04T22:00:00Z"^^ . "The Faculty ITC Research Programme is formulated under the following interlinked research themes:\n\n4D-Earth\nAcquisition and quality of geo-spatial information (ACQUAL);\nForest Agriculture and Environment in the Spatial Sciences (FORAGES);\nPeople, Land and Urban Systems (PLUS);\nSpatio-temporal analytics, maps and processing (STAMP);\nWater Cycle and Climate (WCC).\nThese research themes and activities form the subject framework and organizational structure in which Master's students conduct their individual research. Students have to make a choice of the envisaged MSc research topic during the fourth quartile of the first year. For more information about the content and scope of the Faculty ITC Research Programme, please visit: http://www.itc.nl/research-themes\n\nThe purpose of the MSc research phase is; i) to deepen the knowledge and skills of the students within the research themes; ii) to help students to define their own MSc Research Proposal, and iii) to facilitate students to individually write a concise, logical and well-structured thesis.\nThe first stage of this course is spent on developing an MSc Research Proposal with support and feedback from staff and peers. Through the MSc Research Proposal, the students should demonstrate the ability to undertake independent research. The MSc Research Proposal will be assessed by a Proposal Assessment Board based on a written proposal, a presentation and an oral defence. The Proposal Assessment Board decides if the proposal is acceptable, as one of the conditions to continue with the MSc Research phase*.\n\nThe second stage of the course is dedicated to the execution of an individual research project. Each student works independently on the basis of an approved research proposal. Where relevant, students can with their supervisors apply for Research Support Activity budget ** to conduct for instance fieldwork for data collection.\n\nIn this final part of the course, the students further develop their research skills, interact with their fellow students, PhD researchers and staff members and, finally, demonstrate that they have achieved the learning outcomes of the Master's programme by research, on a satisfactory academic level.\n\n*) If the nature of the research requires a different timeframe for proposal writing and/or data collection, a tailored solution will be considered. Requests for a tailored solution should be addressed to the Programme Director.\n\n**) RSA budget is limited and only available upon motivated request, supported by the first supervisor and the MSc Research coordinator of the concerned research theme. Covid-19 restrictions might limit the possibilities to execute research support activities."@en . "MGEO: MSc Research Proposal and Thesis Writing"@en . . "MGEO: MSc Research"@en . "MGEO: MSc Research"@en . . "201900094" . "AES_0002" . "5"^^ . "140"^^ . "10"^^ . "f2f" . . . . . . . . "This course is open for short-course participants and MSc students with an affinity with disaster risk reduction challenges, combined with experience with GIS and spatial data.\n\nMSc students selecting this elective course must indicate their ability to participate full-time (i.e. 4 scheduled course days per week) in the first two weeks of the course. "@en . . . . "1"^^ . "This course provides an advanced understanding in the assessment of dynamic risk for multi-hazards from hydro-meteorological and geological origin (e.g. landslides, floods, earthquakes). The main focus of the course is on the quantitative analysis of how risk changes, and how information on changing risk is used in decision making for disaster risk reduction. Risk can change gradually due to changing land use, population growth, and climate change. Risk can also change abruptly due to the occurrence of disaster events, that change the environmental and socioeconomic conditions completely. We look at various methods for risk assessment, ranging from qualitative methods based on Spatial Multi-Criteria Evaluation, through semi-quantitative methods based on exposure modelling, to quantitative risk assessment using hazard intensity, frequency, exposure and physical vulnerability, depending on the data availability and objectives of the study. In order to evaluate changing risk we need to analyse also how hazard changes, and how elements-at-risk (buildings, population, transportation infrastructure etc.) change in terms of location and vulnerability. In order to evaluate optimal risk reduction alternatives (structural and non-structural) risk reduction is calculated and costs-and benefits are evaluated. Stakeholder views regarding the various alternatives are also considered using a Spatial Multi-Criteria Approach.\n\nThis course is offered both as elective course for second-year MSc students, and as short course, for external course participants."@en . "Analysing Changing Multi-hazard Risk 2"@en . . "Analysing Changing Multi-hazard Risk 2"@en . "Analysing Changing Multi-hazard Risk 2"@en . . "202100006" . "WRS_0006" . "5"^^ . "140"^^ . "10"^^ . "2022-11-10T23:00:00Z"^^ . "f2f" . "The course starts with a number of lectures setting the general framework and dealing with the governing equations determining the global climate and climate change. Thereafter we will look into the climate at a more local scale, with an emphasis on urban areas. This will take place through lectures which are followed by supervised practical exercises where we deal with the exploration and analysis of typical urban climate datasets. The exercise will be reported by each student and will count as the first individual assignment of this course.\n\nThe latter part of the course consists of regional climate modelling. Here the students will work with the Weather Research and Forecasting (WRF) model. The model will be introduced by lectures followed by supervised practical exercises where each student will set up the model, run it and analyze the output. This will be reported by each student and submitted as the second individual assignment of this course.\n\nThe course will be rounded off by a written test which will be open book, meaning that the lecture notes will be made available during the test."@en . . . . . . "Knowledge of Programming and skills to work on a computer server in LINUX environment are beneficial for the learning process, M-GEO WREM specialization courses, or \n\nMSc level background in meteorology or climatology ,All students in the M-GEO WREM specialization are accepted. Students following other specializations or programmes outside ITC faculty should have a BSc level background in meteorology or climatology."@en . . . . . . "2"^^ . "1" . "1A " . . "2022-09-04T22:00:00Z"^^ . "This course will explain the physical principles governing the (urban) climate and climate change, and offer a set of methods and techniques for its analysis and monitoring. This will encompass measuring and modelling approaches, and their applications for understanding water-energy cycles and their extremes (i.e. heatwaves, drought, and floods) with an emphasis on urban environments."@en . "Water, Climate and Cities"@en . . "Water, Climate and Cities"@en . "Water, Climate and Cities"@en . . "201900053" . "EOS_0004" . "5"^^ . "140"^^ . "10"^^ . "2022-11-10T23:00:00Z"^^ . "f2f" . "The course will be composed of lectures (with the use of flipped classrooms when necessary), practicals, supervised and unsupervised assignments and fieldwork for UAV image acquisitions. The student will learn how to correctly process the acquired images receiving both the theoretical and practical knowledge and gaining in self-confidence and independence during the course."@en . . . . . . . . "Participants do not need prior knowledge on the topics of the course.,All M-GEO and M-SE students are accepted.\n\nNote that we offer two UAV courses in Q5. GFM students should choose \"Scene understanding with UAVs\", while all the other M-GEO and M-SE students should join this course. In general, all students should have basic knowledge of remote sensing."@en . . . "5"^^ . "1" . "1A " . . . . "2022-09-04T22:00:00Z"^^ . "Image-based modelling (IBM) refers to the techniques of acquiring 3D object information from two or more images. This includes three traditional photogrammetric algorithms (feature extraction and matching, Bundle Block Adjustment and orthophoto generation) and new techniques from the Computer Vision community (such as structure from Motion, Visual Odometry and Semi-Global Matching) to derive 3D point information from an image sequence. These techniques can be used to process both terrestrial and airborne images.\nAmong the innovative platforms for data capture, Unmanned Aerial Vehicles (UAV, better known as drones) are becoming a valid alternative to traditional Geomatics acquisition systems, as they close the gap between higher resolution terrestrial images and the lower resolution airborne and satellite data. UAV can be remotely controlled helicopters, fixed wind airplanes or kites. Different sensors can be installed on-board to acquire data. Many applications ranging from 3D building modelling to crop and forest monitoring can profit from these data acquisition platforms.\n\nIn this course the advanced IBM techniques and, in general, the 3D geo-information processing will be explained, with focus on the use of data acquired by UAVs. The course is composed of two main parts. In the first part, the four main steps of the modern IBM process (image orientation, point cloud generation, orthophoto generation and quality assessment) to retrieve 3D information from images will be defined. The peculiarities of IBM process using UAV images will be discussed in detail, showing the differences with the traditional acquisition of airborne images. During the second part the participants will gain hands-on experience on the use of UAVs. In this period, the students will learn how to process images acquired with different sensors and for different applications.\n\nSpecifically, participants will learn the principle of IBM methods and they will design three simple solutions (feature extraction, feature matching and relative orientation) by adopting these methods in simple Matlab codes. Lectures will be always coupled with demonstrations and practical sessions on the theory delivered.\n\nThe second part of the course will allow the participants to experience the UAV data acquisition and processing workflow. They will understand how a UAV related project is planned and executed with their involvement to a real UAV acquisition project. Then, they will apply the learned IBM techniques using a commercial software (Pix4D – www.pix4d.com) to process the acquired data and extract 3D information. They will finally analyse and compare the data using the available ground truth and dedicated tools and software (Matlab scripts and CloudCompare) to evaluate their results. Multi-spectral and thermal image acquisitions from UAVs will be also part of the course topics. Participants will learn how to process these images and how to better use them for different applications. Additional presentations will be finally provided to describe the use of UAVs in six different domains covering different perspectives of ITC Departments: land administration, disaster mapping and management, natural resources and crop monitoring, water management and flood monitoring, maintenance of UAVs and real-time processing.\n\nParticipants do not need prior knowledge on the topics of the course."@en . "Earth Observation with Unmanned Aerial Vehicles"@en . . "Earth Observation with UAV's"@en . "Earth Observation with UAV's"@en . . "201900071" . "WRS_0002" . "5"^^ . "140"^^ . "10"^^ . "2023-02-02T23:00:00Z"^^ . "f2f" . "online" . "Lectures, practicals (workshops), tutorials, individual assignment and group work and written tests."@en . . . . . . "Knowledge of Programming and skills to work on a server in LINUX environment are beneficial for the learning process ,Successful completion of year 1 M-GEO WREM specialization courses, or equivalent."@en . . . . . . . . "4"^^ . "2" . "1B " . . . "2022-11-13T23:00:00Z"^^ . "Data assimilation is a standard practice in numerical weather prediction (e.g., as implemented in the European Centre for Medium-Range Weather Forecasts, ECMWF), and is increasingly used in many other areas of climate, atmosphere, ocean, land and environment modeling.\n\nData Assimilation is a process in which observations are assimilated into a dynamical numerical model in order to determine as accurately as possible the state of the physical system. This course will introduce the theoretical background, the state-of-the-art methods and practical systems, and examples of data assimilation."@en . "Data Assimilation "@en . . "Data Assimilation "@en . "Data Assimilation "@en . . "201900202" . "PGM_0003" . "7"^^ . "196"^^ . "10"^^ . "2023-07-06T22:00:00Z"^^ . "f2f" . "Lectures and guest lecture, supervised practicals to introduce modelling methods and tools, group assignment using methods and tools introduced in practicals, self study, plenary discussions."@en . . . . . . "Knowledge of GIS and remote sensing at level of M-GEO Core, i.e. ability to independently apply GIS software and basic concepts of image classification;Knowledge of basic statistical methods and tests (e.g. linear and logistic regression analysis).,Knowledge of GIS and remote sensing at level of M-GEO Core, i.e. ability to independently apply GIS software and basic concepts of image classification;\n\nKnowledge of basic statistical methods and tests (e.g. linear and logistic regression analysis)."@en . . . "4"^^ . "4" . "2B " . . . . . "2023-04-23T22:00:00Z"^^ . "Land use / cover change processes in less developed countries are typically rapid and extensive, and they often include a considerable proportion of unplanned or informal development. Land use / cover change models can help to understand, analyse and simulate the outcomes of such processes, providing information that can inform policy development. This course develops the student's conceptual understanding of three methods for modelling land use / cover change and their ability to select, develop and apply these methods in an appropriate manner. The methods to be examined are: spatial logistic regression for identifying drivers of land use / cover change, Cellular Automata (CA) models and Agent Based Models (ABMs). The course commences with introductory lectures, readings and discussions on the field of land use / cover change modelling. The three methods will be introduced with an urban case study using the modelling platform NetLogo. In the group work phase, students can choose their own application case and apply in depth one of the methods."@en . "Land Change Modelling"@en . . "Land Change Modelling"@en . "Land Change Modelling"@en . . "201900051" . "WRS_0004" . "5"^^ . "140"^^ . "10"^^ . "2023-02-02T23:00:00Z"^^ . "f2f" . . . . . "basic knowledge on remote sensing."@en . . . . . . "2"^^ . "2" . "1B " . "2022-11-13T23:00:00Z"^^ . "Plants play a crucial role in the history of the Earth. They have accelerated the water cycle, and have made soil formation possible, and provide Oxygen through photosynthesis. They are also the primary sink of carbon dioxide, and they are our food.\n\nOngoing changes in climate affect the functioning of plants, but also vice versa: Land cover changes affect the surface properties of the Earth which in turn affect the climate. For sustainable land cover, ecology and food production, we must be able to quantify the role of plants in the climate on Earth.\n\nThis course offers tools to quantify processes in terrestrial vegetation using contemporary remote sensing signals (reflectance, chlorophyll fluorescence, and thermal remote sensing) in combination with in situ data. There is attention for natural ecosystems as well as crops.The following topics will be covered:\n\nPlant physiological processes and their relation with satellite data\nThe use of radiative transfer models for scaling processes from the molecular to the satellite level\nThe retrieval of plant functional traits from satellite data, in particular Sentinel 1,2,3, and 5 (Tropomi), and airborne data collected in the frame of the ESA’s 8th Earth Explorer mission FLEX.\nThe use of these data in dynamic vegetation model\nThe participants will work on their own mini-project, such as: the effect of companion planting, the water productivity or water footprint, the effect of volcano eruptions, re- or deforestation."@en . "Remote Sensing and Modelling of Primary Productivity and Plant Growth"@en . . "RS & Mod. Primary Prod. & Plant Growth"@en . "RS & Mod. Primary Prod. & Plant Growth"@en . . "201900046" . "AES_0001" . "5"^^ . "140"^^ . "10"^^ . "f2f" . . . . . . "This course is open for short-course participants and MSc students with an affinity with disaster risk reduction challenges, combined with experience with GIS and spatial data.\n\nMSc students selecting this elective course must indicate their ability to participate full-time (i.e. 4 scheduled course days per week). "@en . . . . "1"^^ . "This two-week intensive course provides an advanced understanding in the assessment of dynamic risk for multi-hazards from hydro-meteorological and geological origin (e.g. landslides, floods, earthquakes). The main focus of the course is on the quantitative analysis of how risk changes, and how information on changing risk is used in decision making for disaster risk reduction. Risk can change gradually due to changing land use, population growth, and climate change. Risk can also change abruptly due to the occurrence of disaster events, that change the environmental and socioeconomic conditions completely. We look at various methods for risk assessment, ranging from qualitative methods based on Spatial Multi-Criteria Evaluation, through semi-quantitative methods based on exposure modelling, to quantitative risk assessment using hazard intensity, frequency, exposure and physical vulnerability, depending on the data availability and objectives of the study. In order to evaluate changing risk we need to analyse also how hazard changes, and how elements-at-risk (buildings, population, transportation infrastructure etc.) change in terms of location and vulnerability. In order to evaluate optimal risk reduction alternatives (structural and non-structural) risk reduction is calculated and costs-and benefits are evaluated. Stakeholder views regarding the various alternatives are also considered using a Spatial Multi-Criteria Approach.\n\nThis course is offered both as elective course for second-year MSc students, and as short course, for external course participants. "@en . "Analysing Changing Multi-hazard Risk 1"@en . . "Analysing Changing Multi-hazard Risk 1"@en . "Analysing Changing Multi-hazard Risk 1"@en . . "202001493" . "AES_0004" . "5"^^ . "140"^^ . "10"^^ . "2022-11-10T23:00:00Z"^^ . "hybrid" . "The course will consist of:\n\n(Online) Interactive lectures, where an introduction is given to the various topics. The lectures will also be available later as videos. The course is given in hybrid mode, as an online course, as well as face-to-face in ITC.\nSupervised practical. These will be organized in ITC, and a supervisor will be present to give support. Online participants are guided through Canvas. \nUnsupervised practical. The students can work at ITC in the practical room, or decide to work at home.\nReading assignments.\nFinal projects. Both components of the course contain a final project, in which the students analyze a particular problem.\nGroup assignments include a stakeholder simulation workshop, where students have to represent certain stakeholder"@en . . . . . . . "This course is open for short-course participants and MSc students with an affinity with disaster risk reduction challenges, combined with experience with GIS and spatial data."@en . . . . "4"^^ . "1" . "1A " . . . . "2022-09-04T22:00:00Z"^^ . "This course provides an advanced understanding in the assessment of dynamic risk for multi-hazards from hydro-meteorological and geological origin (e.g. landslides, floods, debris flows). This course presents approaches to evaluate how multi-hazard risk might change over time. Multi-hazard risk assessment (MHRA) is the quantitative estimation of the spatial distribution of potential losses for an area. These relate to multiple natural hazards with different hazard interactions, with multiple event probabilities, for multiple types of elements-at-risks, and multiple potential loss components. The course first discusses the various types of hazard interactions. An overview is given of the tools available for multi-hazard assessment, stressing the importance of developing integrated physically-based multi-hazard models. One of such models, OpenLISEM Hazard, is treated in detail, and the participants will get hands-on experience in the use of this integrated physically-based multi-hazard model, and the data requirements. After discussing problems involved in analyzing static MHR, the course addressed the analysis of changing multi-hazard risk as a basis for decision-making. These changes may be related to changes in triggering or conditional factors, increasing exposure of elements at risk, and their vulnerability and capacity. Dynamic risk can be evaluated in the long term because of changes in climate, land use, population density, economy, or social conditions. Changes in risk might also be occurring in a short time frame and assessed as a basis for Early Warning and impact based forecasting, and to analyze the consequences of hazard interactions after major events. "@en . "Modelling Multi-Hazards & Risk"@en . . "Modelling Multi-Hazards & Risk"@en . "Modelling Multi-Hazards & Risk"@en . . "201800300" . "NRS_0008" . "7"^^ . "196"^^ . "10"^^ . "2023-07-06T22:00:00Z"^^ . "f2f" . "The first part of the course (60%) will be face-to-face teaching and supervised practical’s to acquire knowledge on relevant theories and learn how to apply these in a practical way. This will be assessed in a written test, and partly by the individual project making up.\n\nIn the second part of the course, two small projects (one individual and one group) will train the student to place the learned techniques and theories into context. This will be student centered learning. The student has a choice of the type of species and or environment that wil be modellend. Also, the student has a choice in a type if (mini) research question that will be addressed in the mini project. The individual project (25%) tests the ability to create and evaluate ENM’s for a specific case study of interest for the student. In the group project (15%), the use of ENMs has to be placed in the context of Essential Biodiversity Variables (EBVs), sustainable agricultural, semi-natural and protected area landscapes, or information needs for policy applications (SDGs, Aichi targets). In the group, model outputs created in the individual project will be used as input for the evaluation how these can be used in either of these contexts."@en . . . . . . . . "GIS and Remote sensing skills Basic understanding of regressionBasic understanding of inferential statistics (ANOVA, T test etc),GIS and Remote sensing skills\nBasic understanding of regression\nBasic understanding of inferential statistics (ANOVA, T test etc)"@en . . . "6"^^ . "4" . "2B " . "2023-04-23T22:00:00Z"^^ . "Species distribution modelling and environmental niche modelling are types of modelling where the occurrence or absence of certain species or crops are linked to environmental conditions that are relevant. The type of organism that is modeled can be variable in nature, ranging from the presence of rare and endangered species, to the outbreak of pest species.\n\nIt is used to make interpolations of observations of species over space using relevant explanatory variables. These extrapolations can be used to assess how likely the occurrence of such an species is in unvisited areas. Also, it can provide insight to what extent the spatial distribution of a species will change as a result of changes in conditions, for example due to land cover change, or climate change.\nExtrapolations are based on fitting an empirical relation between the presence or absence of a species and the environmental conditions under which it occurs, it’s “niche”.\n\nIn this course students will learn hands on how to design, create and evaluate different kinds of environmental niche models (such as logistic regression, boosted regression trees and maximum entropy) and you will learn how you can use these models to make projections when conditions change.\n\nThe course is of interest to people that need statistical interpolation techniques. Also, the course will teach you to apply different types of software packages. Next to geo-information software you will be working with the R-software.\n\nThis course mainly aims at applications in the domain of natural resources, but when you have an interest in in other domains where this can be applied (e.g. disease outbreaks or rare events such as landslides) this course can also be very useful for you and there will be room to explore the application to your area of interest."@en . "Species Distribution & Environmental Niche Modelling"@en . . "Species Distribution&Env Niche Modelling"@en . "Species Distribution&Env Niche Modelling"@en . . "201900056" . "PGM_0009" . "5"^^ . "140"^^ . "10"^^ . "f2f" . . . . . "PP1, need to have taken PP1,This course requires students from any university to have successfully completed the first year of their MSc degree including the GIS, geo-databases, and possibly Remote Sensing courses. \n\nNOTE: The minimum number of participants is 8 students and the maximum number of students is 18 due to a game of spatial decision-making."@en . . . "3"^^ . "Spatial planning and decision-making processes occur in any domain, be it urban or rural areas, management of natural and water resources, distribution of welfare, wellbeing and risk, adaptation to climate change, or energy transition. They involve stakeholders in civil society, private sector, public administration and government which hold different interests, norms, values and knowledge as well as different practices and strategies of dealing with planning, decision-making and conflicts. Information and information systems do not capture the normative and collaborative/participative aspects of these processes whereas Planning Support Systems (PSS) and Spatial Decision Support Systems (SDSS) do.\n\nYou can either study theory and methods about participatory development of geo-technologies for participatory planning or theory and methods about the use of these technologies in planning and decision-making processes. This course is the second of two courses and addresses the latter study. It focuses on theory and methods of processes of participation and learning in the generation of spatial information and moderation of PSS and SDSS in planning and decision-making. The first course focuses on the theory, methods and technologies fo the participatory development of PSS and SDSS that support spatial planning and decision-making."@en . "Participatory Planning 2: Theory and Application of, and Learning from, PSS and Serious Games in Planning and Decision Processes"@en . . "Participatory Planning 2"@en . "Participatory Planning 2"@en . . "201900065" . "EOS_0003" . "5"^^ . "140"^^ . "10"^^ . "2022-11-10T23:00:00Z"^^ . "f2f" . "Image analysis requires theoretical concepts and practical skills. Lectures will be used to introduce the topics, followed by reading textbook material. Research articles will also be recommended for those students who are interested in learning more about a specific concept, method, algorithm etc. Practical classes will consist of a mixture of demos, individual work following written instructions, and presentations of the outcomes during feedback sessions. In the practical classes, students will work with existing program codes and modify them (to a limited degree). In this way, the students can get insight into the intermediate stages of the image analysis algorithms and make decisions on the outcomes. Furthermore, a reflection on theoretical concepts will be made. In this way, a solid integration of theory and practice will be achieved."@en . . . . . "Programming skills \n\nImage analysis knowledge ,All students in Geoinformatics specialization are accepted. Students following other specializations should have background in programming and image analysis."@en . . . . . . . . . "4"^^ . "1" . "1A " . . . . "2022-09-04T22:00:00Z"^^ . "In this course, the students will be introduced to advanced image analysis methods dedicated to enriching their geo-information problem-solving abilities. Image processing and analysis methods treated in previous courses, such as conventional hard pixel-based classification, do not take into account spatial correlations in images and, therefore, do not completely exploit the information contained in images. In this course, we aim to introduce more specialized image analysis methods. In particular, Support Vector Machine and Random Forest will be taught for multisource classification at the pixel level. Convolutional Neural Networks (CNNs) and Fully Convolutional Neural Networks (FCN) will be introduced for contextual classification. Advantages and challenges related to multi-temporal image analysis will also be discussed. The methods introduced in this course will be applied to real case studies. "@en . "Advanced Image Analysis"@en . . "Advanced Image Analysis"@en . "Advanced Image Analysis"@en . . "201900138" . "PGM_0006" . "7"^^ . "196"^^ . "10"^^ . "2023-07-06T22:00:00Z"^^ . "f2f" . "Active participation, critical reflection, oral presentation. In addition to lectures and practical assignments, the learning of course concepts is complemented with paper discussion sessions, where students are expected to lead a paper discussion session, position their views about different research articles, and activate their peers with points for discussion. The staff act as observers."@en . . . . . "GIS, Ability to independently apply GIS software. Knowledge of GIS at the level of ITC Core courses or higher is preferred. At Q1 a course on \"GIS for transport\" is offered to CEM students and exchange students as an introductory course to GIS.,Ability to independently apply GIS software. Knowledge of GIS at the level of ITC Core courses or higher is preferred. At Q1 a course on \"GIS for transport\" is offered to CEM students and exchange students as an introductory course to GIS."@en . . . . . . . "5"^^ . "4" . "2B " . . "2023-04-23T22:00:00Z"^^ . "The interaction between land use and transport is complex, multifaceted, and dynamic. Land use development influences transport-related decisions/behavior and transport decisions influence where, when, and how land development takes place.\n\nIn this course, key theories that underlie land use transport interaction are discussed, along with their modeling foundations. Special attention is given to spatial interaction theory, which is of relevance to the study of optimal service locations, accessibility analysis at various levels of detail, simulation, and forecasting, and can also be used to optimize and manage network throughput.\n\nThis course covers important modeling foundations of networks and spatial interaction as a basis for accessibility analysis in GIS.\n\nStudents will conduct a scenario study and examine the land use, mobility, and accessibility impacts of land use and transport policy strategies, using GIS-based land-use/transport interaction measures for the Netherlands.\n\nThe course will be offered to ITC students and CEM students as part of a joint-teaching collaboration between Faculties ITC (UPM) and ET (CEM). Please note that all elective courses at ITC are 7 EC, while the elective courses at ET are 5 EC. "@en . "Land Use and Transport Interaction 2"@en . . "Land Use and Transport Interaction 2"@en . "Land Use and Transport Interaction 2"@en . . "201800306" . "PGM_0002" . "7"^^ . "196"^^ . "10"^^ . "2023-07-06T22:00:00Z"^^ . "f2f" . . . . . . . "Knowledge of GIS at level of Core Courses or higher; Ability to independently apply GIS software; Knowledge of basic statistics.,Knowledge of GIS at level of Core Courses or higher;\nAbility to independently apply GIS software;\nKnowledge of basic statistics."@en . . . . . . . . "5"^^ . "4" . "2B " . . . . . "2023-04-23T22:00:00Z"^^ . "This elective explores issues of socio-spatial inequality, differentiation and fragmentation that impact the urban environment and the quality-of-life of urban residents. We concentrate on capturing and understanding diverse forms of knowledge regarding intra-urban variations of quality-of-life, including socioeconomic status and health. A better understanding of the resulting socio-spatial patterns is essential for targeting (multiple) deprived areas and implementing area-based and regeneration policies. Particular attention will be paid to different scales of analysis and categorisations.\n\nThe course follows a challenge-based learning approach where students Identify a learning path to solve socially relevant challenges related to urban quality of life and well-being. This course presents several methods under a mixed-methods approach. Through a combination of lectures, reading assignments, exercises, and group work, students learn to combine quantitatively derived patterns and measures with urban residents generated data and perceptions and interpret the complementary results acquired. Group collaboration: each student will carry a diary to report their work, observations, challenges, and strategies to methods used."@en . "Intra Urban Spatial Patterns and Processes"@en . . "Intra Urban Spatial Patterns and Processes"@en . "Intra Urban Spatial Patterns and Processes"@en . . "201900062" . "NRS_0005" . "5"^^ . "140"^^ . "10"^^ . "2022-11-10T23:00:00Z"^^ . "f2f" . "A series of lectures, tutorials in the forms of discussions and Q&A sessions, field and lab tutoring, supervised practicals, and the use of online and distance learning materials will be implemented."@en . . . . . . . "Remote sensing and GIS cores,GIS and remote sensing skills."@en . . . . . . . . . "2"^^ . "1" . "1A " . . . . . . "2022-09-04T22:00:00Z"^^ . "This course deals with the retrieval of quantitative information about vegetation canopies from remote sensing data. In particular, the focus will be on vegetation physiological parameters, namely leaf area index and phenology and how they can be estimated from remote sensing data.\n\nDefinitions and details about these parameters, how they are measured in the field, and how they are estimated using various remote sensing data will be provided during the course."@en . "Quantitative Remote Sensing of Vegetation Parameters "@en . . "Quantitative RS of Vegetation Parameters"@en . "Quantitative RS of Vegetation Parameters"@en . . "201900090" . "PGM_0010" . "5"^^ . "140"^^ . "10"^^ . "2023-02-02T23:00:00Z"^^ . "f2f" . "The course is revolving around the moderated discussion of selected literature, key (guest) lectures on geodata and ai ethics. The focus is on debating geoprivacy, cartographic ethics and broader concerns in geodata technology ethics with academic peers."@en . . . . . . . "There are no specific entry requirements for this course, but students should be open to engaging in critical thinking about the development and use of geodata technologies,There are no specific entry requirements for this course, but students should be open to engaging in critical thinking about the development and use of geodata technologies. The course is open to both MSc and PhD students."@en . . . "4"^^ . "2" . "1B " . . . . . . "2022-11-13T23:00:00Z"^^ . "Geodata ethics is becoming an ever more important topic in the field of geo-information science and earth observation. As information and communication technologies advance and everybody can be connected to everybody the volume, velocity, variety veracity and value of available data keeps on increasing. At the same time approaches to getting and linking data are evolving and more detailed models and approaches to studying spatial phenomena become feasible. But does feasibility also mean that we should build and implement all new geo-spatial data technologies? How invasive should we allow geo-data technologies to be? What ethical principles and moral considerations should guide how we build and assess technological innovations? What kinds of innovations might we need to counter the risks that an ever more datafied society brings with it? Answering these questions is not easy but more important than ever: It is high time that we secure a Space for Ethics!\n\nIn this course, we will cover some (but by no means all) current debates surrounding geodata technology ethics. Possible foci will be location privacy and machine learning (or AI) ethics. Information about an individual’s location is substantially different from other kinds of personally or demographically identifiable information which makes privacy a hot topic. We are also witnessing the increasing automation of geospatial processes. This will require astute engagement with Geo-AI ethics as regulation and debates on the topic are bound to increase in the coming decades. Students will engage with and sharpen their critical thinking and transdisciplinary competences in this course."@en . "Space for Ethics: Locating Information Privacy"@en . . "Space for Ethics: Locating Information Privacy"@en . "Space for Ethics: Locating Information Privacy"@en . . "201900061" . "EOS_0007" . "5"^^ . "140"^^ . "10"^^ . "2022-11-10T23:00:00Z"^^ . "f2f" . "hybrid" . "The course will be composed of lectures (with the use of flipped classrooms, or pre-recoreded videos when necessary), practical, assignments and/or fieldwork for UAV image acquisitions. The student will learn how to correctly process the acquired images receiving both the theoretical and practical knowledge and gaining in self-confidence and independence during the course."@en . . . . . . . "Specialization: GeoinformaticsStream course: Image AnalysisNote that we offer two UAV courses and that students from other specialisations/outside ITC should choose the Earth Observation with UAVs course,Specialization: Geoinformatics\nStream course: Image Analysis\n\n \n\nNote that we offer two UAV courses and that students from other specialisations/outside ITC should choose the Earth Observation with UAVs course in principle.\n\nIn case of any doubt, the students can contact course coordinator for clarification. "@en . . . . . . . . . "4"^^ . "1" . "1A " . . . . "2022-09-04T22:00:00Z"^^ . "Unmanned Aerial Vehicles (UAVs) are becoming a valid alternative to traditional Geomatics acquisition systems, as they close the gap between higher resolution terrestrial images and the lower resolution airborne and satellite data. UAVs can be remotely controlled helicopters, fixed wind airplanes or kites. This course deals with algorithms and techniques for scene information extraction from images. Both geometric (i.e. 3D reconstruction) and semantic (i.e. 2D image understanding) aspects are described in the course.\n\nIn this course the 2D and 3D scene analysis will be explained, with focus on the use of data acquired by UAVs. The course is composed of two main parts. In the first part, the participants will focus on 2D scene analysis (semantic segmentation, object detection and tracking, modern deep learning), while during the second part, the participants will gain hands-on experience on the use of UAVs. The second part of the course will be given together with the course on “Earth Observation with UAVs”.\n\nAt the end of the course the participants will submit the output of an assignment on the dealt topics, the quality of which will contribute to the course mark."@en . "Unmanned Aerial Vehicles for Scene Understanding"@en . . "Scene Understanding with UAV's"@en . "Scene Understanding with UAV's"@en . . "201900058" . "EOS_0006" . "5"^^ . "140"^^ . "10"^^ . "2022-11-10T23:00:00Z"^^ . "f2f" . "Lecture, flipped classroom, self-study, individual assignment, supervised practical and group assignment (oral presentation and individual report)."@en . . . . . . "All students in the M-GEO GFM specialization are accepted.Students following other specializations or programmes should have studied programming (Python, Matlab, or R) and basic image analysis knowledge.,All students in the M-GEO GFM specialization are accepted.\nStudents following other specializations or programmes should have studied programming (Python, Matlab, or R) and basic image analysis knowledge."@en . . . . . . . . "2"^^ . "1" . "1A " . . "2022-09-04T22:00:00Z"^^ . "Radar Remote Sensing is different from optical Remote Sensing and offers unique opportunities in observing and monitoring the Earth surface. This course provides an overview of technology and applications related to radar remote sensing. Specifically, Synthetic Aperture Radar (SAR) and advanced methods building on SAR are considered: InSAR (Interferometric Synthetic Aperture Radar), DInSAR (Differential InSAR), Time Series InSAR, PolSAR (Polarimetric SAR) and PolInSAR. The students will learn how to choose, handle and pre-process the SAR images and apply advanced methods for information extraction from these images. Various examples of applications will be provided. The quality of obtained results will be discussed in relation to the type of SAR data and choices made during the analysis. The course offers an opportunity to specialise in one of the advanced SAR methods during a practical project."@en . "Radar Remote Sensing"@en . . "Radar Remote Sensing"@en . "Radar Remote Sensing"@en . . "201900168" . "AES_0007" . "7"^^ . "196"^^ . "10"^^ . "2023-07-06T22:00:00Z"^^ . "f2f" . "The course starts with a small set of lectures combined with a number of supervised practicals/tutorials. A number of papers on weather impact analysis will be introduced by staff for self-study. A case-study will be introduced as an individual project; with limited guidance, students will on a self-defined, real-world challenge, where weather data will be collected and analyzed related to an application field of their interest. The project is based on Challenge-based learning approach. Frequently feedback/intervision sessions and formative evaluations will be implemented to ensure students reflect and communicate on their steps in the individual learning process with their peers and experts."@en . . . . . "Open for students with an interest in weather and weather data processing, with a background in earth sciences, physical geography, water resources, natural resources, natural hazards, soil science, engineering.,Open for students with an interest in weather and weather data processing, with a background in earth sciences, physical geography, water resources, natural resources, natural hazards, soil science, engineering. "@en . . . . . . . "5"^^ . "4" . "2B " . . "2023-04-23T22:00:00Z"^^ . "Weather is everywhere. The weather has an impact on the earth surface, but also on everything that is on that surface: vegetation, soil, water availability, humans, etc. Many natural hazards have extreme weather conditions as a trigger, like droughts, floods, heat-waves, and rainfall-induced landslides. Also, agricultural production is dependent on weather conditions, as extreme weather events might cause damage to crops or land, and lead to less harvest. Similarly, the extent and magnitude of the urban heat island effects are largest under hot, stable weather conditions. When analyzing and visualising this weather information with data on the earth systems under study, one gets insight into the impact of weather and can act accordingly to prevent or mitigate disasters.\n\nFortunately, the weather is continuously monitored worldwide, by satellites and ground stations at minute, daily or monthly scales. Many meteorological datasets are freely accessible, being an enormously rich source for weather information. \n\nThis course provides knowledge on weather data sources and tools to analyze the interaction between the weather and earth surface processes in time and space. The focus will be on analysing meteorological datasets to extract information on extreme weather events. The challenge will be to link this climatic information to non-meteorological data to learn more on the impact weather has on earth systems, such as natural hazards, hydrology, vegetation, urban environments, etc."@en . "Weather Impact Analysis"@en . . "Weather Impact Analysis"@en . "Weather Impact Analysis"@en . . "201800298" . "WRS_0001" . "7"^^ . "196"^^ . "10"^^ . "2023-07-06T22:00:00Z"^^ . "f2f" . "Combination of frontal and participatory teaching; Self-study, and Practical’s that serve submission of assignments."@en . . . . . . . . . . "The course is planned in parallel to the course on ‘Observing and modelling of surface water in a changing world’. ,Proven knowledge on hydrology, EO and hydrological modelling concepts."@en . . . . . . . "2"^^ . "4" . "2B " . "2023-04-23T22:00:00Z"^^ . "The course aims at various aspects of integrated water resource modelling for surface water assessments. Aspects of catchment system representation for integrated surface water – groundwater, rainfall-runoff, floods, Lakes and water allocation for food production will be addressed. Mechanisms on runoff production, model parameterization, model integration and coupling; multi-objective model calibration, effects of time-space scales, model error propagation and uncertainties will be addressed. An introduction to numerical 1d2d flood-modelling will be provided. A number of case studies with employing satellite data (DEM/Rain/ET/Floods/Moisture) will be discussed with emphasis on rainfall-runoff and flood modelling including stream flow modelling and water balance closure analysis. Use of earth observation data of DEMs, flood-events and water cycle variables such as rainfall and evapotranspiration will be shown, as well as use of data from climatic models for water resources impact assessments. Knowledge transfer is by lecturing and student participatory teaching. A number of assignments are available. Digital terrain modelling by flying drones and processing of collected terrain data will be practiced as well."@en . "Catchment Hydrology and Surface Water"@en . . "Catchment Hydrology and Surface Water"@en . "Catchment Hydrology and Surface Water"@en . . "201900045" . "NRS_0003" . "5"^^ . "140"^^ . "10"^^ . "2022-11-10T23:00:00Z"^^ . "f2f" . "The course will be 'problem-driven', based on learning by doing. Several real-life based case studies from different disciplines will be offered to gain hands-on experience in the environmental assessment for sustainable planning and decision-making. Teaching will be based on presentations, supervised and un-supervised practical, self-study, plenary discussions, self-tests, project work."@en . . . . . . . "GIS and Remote Sensing skillsBasic understanding of environmental issues, Basic knowledge of ecology and GIS,GIS and Remote Sensing skills\nBasic understanding of the environmental issues"@en . . . "2"^^ . "1" . "1B " . . . . . "2022-09-04T22:00:00Z"^^ . "How can spatial decision support (SDS) and advanced earth observation tools enhance the environmental assessment process in order to ensure sustainable planning and decision-making?\n\n Ad hoc and often uncontrolled development initiatives can have undesired social, economic and ecological consequences. Rapid population growth, pollution, climate change, exposure to hazards and disasters, and the loss of biodiversity and ecosystem services require effective assessment tools to assist sustainable planning and decision-making.\n\n \nEnvironmental Impact Assessment (EIA) and Strategic Environmental Assessment (SEA) are the basic procedures to support this process. The key principles of EIA and SEA are the involvement of relevant stakeholders, a transparent and adaptive planning process, consideration of alternatives, and using the best possible information for decision and policymaking. They, therefore, improve both the (spatial) planning process and the information used in this process. In addition, earth observation (EO) tools can provide the biophysical baseline in a given geographical area and monitor the proposed activity, making the environmental assessment process more efficient.\n\nIn this course, you will not only explore how to integrate SEA into the planning process to enhance sustainable decision-making but also will address how GIS, spatial decision support and advanced EO tools such as an unmanned aerial vehicle (UAV) and high-resolution space-borne imagery, can be used to help identify and structure the problem(s), as well as generate and compare possible solutions, and monitor and evaluate the proposed activities.\n\nHands-on experience with real EIA and SEA projects will be a major part of the course."@en . "Environmental assessment using SDS and advanced EO tools"@en . . "Env. Assessment using SSDS & EO tools"@en . "Env. Assessment using SSDS & EO tools"@en . . "201800308" . "PGM_0004" . "7"^^ . "196"^^ . "10"^^ . "2023-07-06T22:00:00Z"^^ . "f2f" . "online" . "Active learning approach will be applied to the lectures with more theory\nLectures are supported by PPT and references to reading material\nAssignment one and two have supporting reading materials and for this critical reading/writing abilities would be applied\n1-2 Flip-classroom approach lectures will be applied. Flip-classroom approach is an education method which activates students by changing the roles teacher - student."@en . . . . . "Experience and understanding of basic Land Administration concepts and definitions. Evaluate and apply basic principles of Good Governance to Good and Weak Land Governance.,Experience and understanding of basic Land Administration concepts and definitions.\nEvaluate and apply basic principles of Good Governance to Good and Weak Land Governance."@en . . . . . . . "3"^^ . "4" . "2B " . . "2023-04-23T22:00:00Z"^^ . "At the beginning of this course, governance in theory is introduced and different initiatives and tools promoting good governance are elaborated. There is a strong relationship between Land, Poverty and Governance. Subsequently, the characteristics of Good Land Governance are going to be introduced and relevant examples are going to be presented and explored. Comparative method is going to distinct effects from Good and Weak Land Governance. Specific attention in this course is put on the principles of good land governance; how were those principles developing through the last decades and their evaluation and assessment. International initiatives from FAO (Voluntary Guidelines on the Responsible Governance of Tenure - VGGT) and World Bank (Land Governance Assessment Framework – LGAF) are addressed from theoretical side and with practice implementation examples. Exercises and assignments with case studies from Africa, Asia and South-East Asia are going to enrich the theoretical framework of Land Governance course."@en . "Land Governance"@en . . "Land Governance"@en . "Land Governance"@en . . "201900050" . "LAB_0004" . "1"^^ . "28"^^ . "2"^^ . "f2f" . . . . . "Open for students who have successfully completed the ‘General Laboratory Skills’ training course."@en . . . "1"^^ . "This course can only be followed after the general lab skills training has been successfully completed.\n\nThis training course provides an opportunity to learn different techniques to determine organic matter, like biomass, leaves. The student will be introduced to CHN analysis, TGA, FTIR spectroscopy (or as the student wants to learn). These techniques are explained and the student will be trained in the technique implemented in their MSc research phase.\n\nThe student is welcome to bring samples for MSc research to practice and measure, so they can be ultimately used as data set for his/her MSc thesis.\n\nAlso in this course, the student will learn how to perform statistical analysis on the results of lab experiments, and how to convert received data to the required concentrations. Throughout the course the student will be challenged to continuously monitor the quality of his/her experiments."@en . "Laboratory Skills: Organic Analysis"@en . . "Laboratory Skills: Organic Analysis"@en . "Laboratory Skills: Organic Analysis"@en . . "201800320" . "AES_0003" . "7"^^ . "196"^^ . "10"^^ . "2023-07-06T22:00:00Z"^^ . "f2f" . "hybrid" . "Students can choose their own methods (2) to study, which are relevant for their study and/or work and will focus on these methods throughout the course. The teaching is therefore based on self-learning and application of geophysical methods through projects and fieldwork."@en . . . . . . . "Open for students with a background in earth sciences, physical geography, water resources, soil science, environmental science, engineering, applied physics/mathematics, with an interest in earth systems. Open for students with a background in earth sciences physical geography, water resources, soil science, environmental science, engineering, applied physics/mathematics, with an interest in earth systems. "@en . . . . "6"^^ . "4" . "2B " . "2023-04-23T22:00:00Z"^^ . "This course serves to deliver knowledge on tools for 3D characterization, visualization and modelling of the subsurface. The development of homogeneous 3D subsurface information systems is important for various fields such as for environmental monitoring, soil studies, groundwater, natural hazards, and earth resources.\nMany earth processes have a source or a component below the surface. Understanding of the spatial and temporal variation of physical parameters in the subsurface therefore gives additional insight in these processes and their extent. This could be the extent of pollution plumes, distribution of water, nutrients, mineral resources, or e.g. sliding planes of landslides.\nThe course offers possibility to specialize in two geophysical methods and study these in detail, and final project."@en . "Geophysics - Imaging the Unseen"@en . . "Geophysics - Imaging the Unseen"@en . "Geophysics - Imaging the Unseen"@en . . "201900068" . "NRS_0004" . "5"^^ . "140"^^ . "10"^^ . "2023-02-02T23:00:00Z"^^ . "f2f" . "This course integrates blended learning with storytelling teaching approach. Blended learning combines face-to-face lectures with flipped\nclassroom via online learning materials. Tutorials are self-learning online materials that stimulates learning by doing with some limited coaching. The students will work, hereafter, in multinational groups (consisting of 3-4 persons) on a article or story, combine and develop their skills in role-playing, and present in a “simulated” public hearing setup."@en . . . . . . . "Affinity with the use of geo-information science for data journalisms, infographics, and building an online presence."@en . . . "1"^^ . "2" . "1B " . "2022-11-13T23:00:00Z"^^ . "The objective of this course is to equip students with an interest in geo-journalism skills to deliver spatial products and thematic information in a condensed, easily understandable format addressing the appropriate level for broad societal uptake.\n\nStories about our Planet are broad by nature and it is the job of a journalist to help pin down the often interconnected reasons that drive environmental change. The growth of large, publicly accessible datasets presents the media community with new opportunities, but this also comes with the need for new skills to turn this trove of information into easy-to-understand, evidence-based stories. Simultaneously, ITC/UT has been teaching applied geo-information sciences for +60 years, but with increasing emphasis on academic skills in recent years. According to a recent survey, however, more than 80% of our alumni do not pursue an academic career. Therefore, an all-new MSc course on geo-journalism is presented which teaches students to combine geodata, data analytics, and various Bodies of Knowledge (BoK) in creating compelling (cartographic) infographics to support their storytelling. Using this knowledge and skill, students are enabled to create compelling (cartographic) infographics in minutes rather than days. These infographics are fully semantically enriched, allowing others to see and question the data sources and underlying analyses. With each course assignment, students gradually populate their online NEWSroom with blog articles annotated by these (cartographic) infographics. As portfolio of the student’s environmental storytelling efforts, this NEWSroom also helps improve their personal branding since their reporting is automatically indexed by Microsoft Bing and Google search because of the Semantic Web.\n\nThe skills taught in this course provide important ‘spill-overs’; the open-source technology stack used not only facilitates fact-checking of claims made in news and blog articles, but also those in scientific journal articles. Studies show that only 10~30% of published science articles are reproducible. Many argue this is a logical result of the publishing format as in most papers textual reference is made such as “this experiment was conducted as previously reported [insert reference here]” instead of a live reference to the online executable algorithm and workflow to recreate the results. Our hope is that it will enable those with an enthusiasm for storytelling to use these rapid geo-information pipelines to support their valorisation efforts in publishing (reviews) of scientific findings and how to stimulate viral spread across the Internet."@en . "Geo-journalism"@en . . "Geo-journalism"@en . "Geo-journalism"@en . . "201900060" . "PGM_0001" . "5"^^ . "140"^^ . "10"^^ . "2023-02-02T23:00:00Z"^^ . "f2f" . "An active learning approach will be applied to the lectures\nLectures are supported by PPT, videos, and references to reading material\nThe students will have practical sessions and an individual assignment to practice what they learned from the theory\nThe students will have the unique opportunity to select and practice the usage of a variety of open and closed-source geospatial and gaming solutions for 3D city/building model creation (e.g. FME, VR/AR apps, Blender, SketchUp, CityEngyne, Unity3D, Unreal Engine 5 and Twinmotion among other)"@en . . . . . . "Recommended knowledge on how to use ArcGIS/QGIS\n\nPreferable experience with the usage of geoformation data and simple modelling techniques"@en . . . "4"^^ . "2" . "1B" . "2022-11-13T23:00:00Z"^^ . "This course is suitable for all specializations of ITC and students from UT (e.g., Civil Engineering, Computer Science, or Creative Technology). It aims to provide the student with knowledge of different 3D city/building modelling methods (as a base for Digital Twins), based on geospatial information. The students will be given the opportunity to practice with a variety of applications (e.g., GIS, BIM, image-based, gaming, or Virtual reality and Augmented reality) to develop and interpret their own 3D city/building model. \n\nTo achieve this, theoretical and practical activities where the student can learn different 3D city/building modelling techniques and methods, used in a variety of applications, based on geospatial data are used. \n\nThe student will have the opportunity to work on a 3D modelling/Digital Twin assignment. "@en . "3D modelling for City Digital Twins"@en . . "3D modelling for City Digital Twins"@en . "3D modelling for City Digital Twins"@en . . "201900043" . "AES_0006" . "5"^^ . "140"^^ . "10"^^ . "2022-11-10T23:00:00Z"^^ . "f2f" . "The course contains lectures to introduce new theory, reading assignments followed by feedback sessions to deepen the theory and supervised and unsupervised practicals to put the theory into practice.\n\nThe course has a strong peer component, where the students will learn from each other’s experiences. TIR applications in various domains and will be introduced through finding, reading and discussing relevant literature in a peer-discussion context. Students will ask and answer questions based on paper presentations, to get accustomed to scientific scrutiny by their respective peers.\n\nThe course will be completed with a mini-project where students define a small research question that fits their background and interests, and they will design an experiment to answer that question using TIR data or instrumentation. It is possible to link this part of the course to the students’ own MSc topic if it is related to TIR remote sensing. Alternatively, students can choose from a list of possible topics and datasets to work on for this course based on their interest."@en . . . . . . "Open for students in the programmes ‘Geo-information Science and Earth Observation’ (M-GEO) and ‘Spatial Engineering’ (M-SE), with knowledge of earth materials (atmosphere, water, soil, rocks, vegetation). The suitability of other candidates will be assessed on an individual basis.M-SE students interested in following this course should consult with the course coordinator to resolve possible overlaps with the M-SE \"International Module\",Open for students in the programmes ‘Geo-information Science and Earth Observation’ (M-GEO) and ‘Spatial Engineering’ (M-SE), with knowledge of earth materials (atmosphere, water, soil, rocks, vegetation). The suitability of other candidates will be assessed on an individual basis.\n\nM-SE students interested in following this course should consult with the course coordinator to resolve possible overlaps with the M-SE \"International Module\""@en . . . . . . . . . . . . "2"^^ . "1" . "1A " . . "2022-09-04T22:00:00Z"^^ . "Remote sensing in the thermal infrared (TIR) spectral region is highly complementary to other remote sensing techniques, such as reflective remote sensing (VIS-SWIR) or microwave remote sensing (RADAR). TIR remote sensing measures the energy that is emitted by the studied objects themselves. By analysing the TIR data we can gain insight on the objects' temperature as well as composition. These parameters are crucial when studying phenomena such as land and sea surface temperature, (geo-) thermal heat fluxes, crop health, urban heat islands and mineralogic composition of soils, rocks and drill cores.\n\nIn this course we will take a multi-application look at thermal remote sensing. The students will learn how TIR remote sensing works in theory and practice. They will get instructed on several state-of-the-art TIR instruments in Faculty ITC's GeoScience Laboratory and will get the chance to experiment and practice with the instruments themselves.\n\nThe course contains a component where the students will define a small research question, and design an experiment to answer that question using TIR data or instruments. As this course runs parallel with research proposal writing of the M-GEO programme, a cross-fertilization between the two courses is possible and encouraged."@en . "Thermal Infrared Remote Sensing: from Theory to Applications"@en . . "Thermal Infrared Remote Sensing"@en . "Thermal Infrared Remote Sensing"@en . . "201900072" . "WRS_0003" . "5"^^ . "140"^^ . "10"^^ . "2022-11-10T23:00:00Z"^^ . "f2f" . "Lectures, case studies, cloud processing, group project."@en . . . . "Experience with programming would be helpful for the learning process ,Basic EO techniques (optical and SAR) and related software, statistics."@en . . . . . . . "4"^^ . "1" . "1A " . . . "2022-09-04T22:00:00Z"^^ . "Wetlands are very dynamic and very vulnerable environmental resources, providing a wide scale of ecosystem services but being threatened by various human activities.\nThe following EO challenges will be addressed in the course:\n\nSynergic use of optical and SAR image time series for monitoring\nDifferent aspects of wetland mapping (inventory, habitat mapping, hydrological cycles, conflicting land uses in and around wetlands, image time series processing in the Google Earth Engine environment, etc.)\nLinkage to socio-economic processes: ecosystem services"@en . "Earth Observation for wetland monitoring and management"@en . . "EO for Wetland Monitoring and Mgt."@en . "EO for Wetland Monitoring and Mgt."@en . . "201900047" . "LAB_0001" . "5"^^ . "140"^^ . "10"^^ . "f2f" . . . . . "Compulsory for students who will be using ITC’s GeoScience Laboratory as part of their MSc research, for sample preparation and/or chemical laboratory experiments."@en . . . "1"^^ . "This training course provides an opportunity to develop different abilities and skills to handle laboratory equipment in a safe and precise manner.\n\nEvery student who will be using ITC’s GeoScience Laboratory for their MSc Research phase, for sample preparation or for selected lab experiments (analytical), will be required to follow this course.\n\nIn general lab skills the student will learn how to keep a proper lab journal and how to operate according to health and safety rules. The student will know how to take representative samples and will be introduced to a wide range of analytical techniques necessary to validate remote sensing or geo-information data. The student will learn to look critically at the obtained results.\n\nAs part of this course, the student will also learn how to perform statistical analysis on the results of lab experiments, and how to convert received data to the required concentrations. Throughout the course the student will be challenged to continuously monitor the quality of his/her experiments. To help the student to do so, he/she will document all lab work results in a so called ‘lab journal’.\n\nAll the learned skills are directly applicable in the student's MSc research phase when lab facilities are implemented. More in depth electives can be chosen when certain techniques need to be mastered."@en . "General Laboratory Skills"@en . . "General Laboratory Skills"@en . "General Laboratory Skills"@en . . "201900049" . "LAB_0003" . "1"^^ . "28"^^ . "2"^^ . "f2f" . . . . . "Open for students who have successfully completed the ‘General Laboratory Skills’ training course."@en . . . "1"^^ . "This course can only be followed after the general lab skills training has been successfully completed.\n\nThis training course provides an opportunity to learn different techniques to determine inorganic matter, like minerals and soil compounds. The student will be introduced to XRD, XRF analysis, TGA, digestions, ICP/OES (or as the student wants to learn). These techniques are explained and the students will be trained in the technique implemented in his/her MSc research phase.\n\nThe students is welcome to bring samples for MSc research to practice and measure, so they can be ultimately used as data set for his/her MSc thesis.\n\nAlso in this course, the student will learn how to perform statistical analysis on the results of lab experiments, and how to convert received data to the required concentrations. Throughout the course you will be challenged to continuously monitor the quality of your experiments."@en . "Laboratory Skills: Mineral Analysis"@en . . "Laboratory Skills: Mineral Analysis"@en . "Laboratory Skills: Mineral Analysis"@en . . "201800311" . "NRS_0007" . "7"^^ . "196"^^ . "10"^^ . "2023-07-06T22:00:00Z"^^ . "f2f" . "The course gradually changes from acquiring a general overview of the use/functionality of RS-imagery (spatial-temporal) to address food/water security aspects, to commonly used indices to monitor and assess that, and to tools and skills developments to obtain-extract-derive-interpret specific spatial-temporal data. It concludes with an individual self-defined task. That task will be assessed. The task must connect to the participant's interests, to a food/water security issue, and to a probable MSc research topic that the participant contemplates pursuing. Ideally, the task consists of prior academic/analytical work as required to underpin an MSc-research proposal."@en . . . . . . "Gradually this course will move to the requirement that students have experience with Notebooks and Python script to assess and process data at different DIAS-systems. ,All participants must have passed successfully both M-GEO core-modules (RS and GIS), or do possess an equal level RS/GIS skills and knowledge."@en . . . . . . . . "6"^^ . "4" . "2B " . . . . . . "2023-04-23T22:00:00Z"^^ . "How will we meet the challenge of producing more food to feed a growing population while sustaining the natural resources that agriculture depends upon? Achieving this requires informed decision making, which will heavily depend upon spatial and temporal information derived through the use of remotely sensed data-streams.\n\nThis course provides students with the skills to select, use and interpret state of the art hyper-temporal remote sensing imagery, including both optical and SAR sensors. These skills will be applied to map, monitor, evaluate and explain the performance of the agro-ecosystems. Hyper-temporal remote sensing is also applicable for monitoring urban and natural environments, and to study/assess processes related to e.g. bio-diversity and disasters.\nStudents will learn when to use and how to process hyper-temporal remote sensing images (SPOT-Vegetation, MODIS, PROBA-V, Sentinel-1, 2, and 3, etc.), data mining and probability techniques to:\n\nmap and monitor different aspects of agro-ecosystems using remote sensing indices such as NDVI, LSWI and LAI, to address e.g. “what food or feed crops are produced where and when?”\ndetect anomalies and/or changes in land use and land cover over time, to address e.g. “where are changes in crop production happening and why?”\nfeed into early warning systems by detecting anomalies in vegetation, temperature, precipitation and soil moisture, to address e.g. “where and when do droughts, floods, heat/cold waves, fires and pest and diseases affect agriculture?”\nAfter completing this course, the student will have an additional/improved skill-set as required for a wide range of specialized advisory work, like:\n\nPreparation of inventories for land cover and land use mapping.\nCreation of maps and legends with info on crop calendars and crop management practiced, plus an analysis on production constraints and impacts by perils (yield gaps).\nProviding timely and accurate spatial information that feeds into early warning systems and index based insurance programs.\nQuantified yield gap assessments for land use planning, specifications of advice for extension services, work agenda specifications by research stations, and policy-making considerations."@en . "Spatio-temporal Analysis of Remote Sensing Data for Food and Water Security"@en . . "Spatio-temp. Analysis RS for food&water"@en . "Spatio-temp. Analysis RS for food&water"@en . . "201800314" . "GIP_0003" . "7"^^ . "196"^^ . "10"^^ . "2023-07-06T22:00:00Z"^^ . "f2f" . "During this course, students create a model in a step-by-step way. This model will be further developed and enhanced with additional functionality (using different geo-computational methods) throughout this course.\nThere is a strong emphasis on critical reflection (via sensitivity analyses, model verification, validation of models) and comparison of geo-computational techniques. The student is encouraged to identify the innovative parts of analysis and models."@en . . . . . . . . . "Basic Programming skills, Basic understanding of programming (e.g. Python) is recommended. Students that do not have any experience in programming are recommended to contact the course coordinator.,Basic understanding of programming (e.g. Python) is recommended. Students that do not have any experience in programming are recommended to contact the course coordinator."@en . . . "4"^^ . "4" . "2B " . . . "2023-04-23T22:00:00Z"^^ . "Processes relevant to system Earth, whether natural or man-affected, commonly display variations in space and over time, yet our understanding of their behavior remains limited. The increase in available monitoring data provides handles for a detailed study of these processes. Unravelling the way these processes function and having a mechanism to test hypotheses as well as the possible impacts of interventions is key to contribute to more sustainable development. At course end, the student will have learnt to make use of the available data in process studies, by a variety of computational techniques.\n\nIn this course, we present various geo-computational approaches that help to improve our understanding of geographic processes and/or to extract actionable geo-information. Special attention will be paid to agent-based modelling and to data mining and machine learning analytical methods, and to the integration of different methods.\n\nAgent-based models (ABMs) provide the opportunity to consider both natural and social components when modelling geographic phenomena.\nData mining and machine learning methods allow innovative uses of heterogeneous datasets and have proven their value to solving a variety of social, environmental and scientific problems that were deemed wicked or, even, intractable. Cloud computing is revolutionizing the way we perform spatiotemporal analysis. It allows scaling up our work and designing robust applications for real-life problems."@en . "Spatio-temporal Analytics and Modelling"@en . . "Spatio-temporal Analytics and Modelling"@en . "Spatio-temporal Analytics and Modelling"@en . . "201800310" . "EOS_0005" . "7"^^ . "196"^^ . "10"^^ . "2023-07-06T22:00:00Z"^^ . "f2f" . "Lectures, recorded mini-lectures, flipped classroom, supervised exercises, self-study. The lectures will focus on providing a first overview on the various topics as well as on the explanation of the more advanced point cloud processing methods. Not every topic will be addressed in the lectures. The students are expected to study five book chapters and selected articles independently. During the course several lecture hours will be used for discussion of the studied book chapter and articles."@en . . . . . . . "Completed Bachelor with some mathematics and physics. Basic remote sensing knowledge is an advantage, but not strictly required.,Completed Bachelor with some mathematics and physics. Basic remote sensing knowledge is an advantage, but not strictly required."@en . . . "5"^^ . "4" . "2B " . "2023-04-23T22:00:00Z"^^ . "Airborne, terrestrial and mobile laser scanning are modern technologies to acquire and monitor the geometry of the Earth's surface and objects above the surface like buildings, trees and road infrastructure. This course provides an overview on the state of the art of these techniques, potential applications, like digital terrain modelling and 3D city modelling, as well as methods to extract geo-information from the recorded point clouds."@en . "Laser Scanning"@en . . "Laser Scanning"@en . "Laser Scanning"@en . . "201900066" . "NRS_0001" . "5"^^ . "140"^^ . "10"^^ . "2022-11-10T23:00:00Z"^^ . "f2f" . "Acknowledging the strength and effectiveness of peer learning, this course has been designed to facilitate a strong social and learner-centered environment, meaning that learning is active and requires participation from all learners. You will be actively engaged in sharing, reading, reviewing, and commenting on your classmates' work they post to their learnings and through our discussion forums. Teaching is not something that can only be done by an instructor, you will also need to be involved and participate in the process."@en . . . . . . . "Affinity with the use of geo-information science and entrepreneurship"@en . . . "1"^^ . "1" . "1B " . "2022-09-04T22:00:00Z"^^ . "The objective of this course is to equip the students with entrepreneurial skills.\n\nEntrepreneurship is defined as the capacity and willingness to develop, organize and manage a business venture, along with any of its risks, in order to make a profit. Entrepreneurship can be as an owned company, or internal in a company. This course focuses on Entrepreneurial ‘spirit’ and is characterized by innovation and risk-taking; this is an essential part to succeed in an ever-changing and increasingly competitive global marketplace (from ‘Business dictionary’; 2013). However, entrepreneurship is much broader than the creation of a new business venture. It is also a mind-set – a way of thinking and acting. It is about imagining new ways to solve problems and create value. In the context of changing paradigms in development corporation, giving a mayor role to the private sector in the aid to trade agenda, this entrepreneurial mind-set will help our students to understand and effectively communicate with stakeholders in public-private partnerships and to be active in the private sector as well. Entrepreneurship is, not without a reason, one of the key 21th century skills.\n\nHence, the focus of this course lies on creating an entrepreneurial mind-set to identify and developed business cases from geo-information science that have economical, societal & environmental values."@en . "Entrepreneurship: a Bridge towards Geospatial Innovation"@en . . "Entrepreneurship: Geospatial Innovation"@en . "Entrepreneurship: Geospatial Innovation"@en . . . "Study in a manner that is largely self-directed and autonomous."@en . . "Study in a manner that is largely self-directed and autonomous."@en . . . "Explain and contrast cultural and contextual differences that influence the collection, classification and visualization of spatial information."@en . . "Explain and contrast cultural and contextual differences that influence the collection, classification and visualization of spatial information."@en . . . "Independently design and carry out research in the domain according to scientific quality standards."@en . . "Independently design and carry out research in the domain according to scientific quality standards."@en . . . "Operate professionally and ethically in a multi-cultural environment."@en . . "Operate professionally and ethically in a multi-cultural environment."@en . . . "Identify and explain principles, concepts, methods and techniques relevant for geoinformation processing and earth observation."@en . . "Identify and explain principles, concepts, methods and techniques relevant for geoinformation processing and earth observation."@en . . . "Analyse problems and cases from a (geo-)spatial perspective"@en . . "Analyse problems and cases from a (geo-)spatial perspective"@en . . . "Apply principles, concepts, methods and techniques in the context of system earth, the user and an application domain to solve scientific and practical problems."@en . . "Apply principles, concepts, methods and techniques in the context of system earth, the user and an application domain to solve scientific and practical problems."@en . . . "Analyse issues in an academic manner and formulate judgments based on this."@en . . "Analyse issues in an academic manner and formulate judgments based on this."@en . . . "Critically reflect on own and other's work."@en . . "Critically reflect on own and other's work."@en . . . "Explore the temporal and social context of geo-information science and technology and be able to integrate these insights into scientific work."@en . . "Explore the temporal and social context of geo-information science and technology and be able to integrate these insights into scientific work."@en . . . "Use and design models to simulate (or: study) processes in the system earth with a spatial component."@en . . "Use and design models to simulate (or: study) processes in the system earth with a spatial component."@en . . . "Communicate both orally and in writing on findings of research work to specialists and non-specialists."@en . . "Communicate both orally and in writing on findings of research work to specialists and non-specialists."@en . . . "Analyse scientific and practical domain problems in a systematic manner and develop scientifically valid solutions for these problems in a societal context."@en . . "Analyse scientific and practical domain problems in a systematic manner and develop scientifically valid solutions for these problems in a societal context."@en . . . . . . . . . . . . "Applied Remote Sensing for Earth Sciences"@en . "ARS"@en . . . . . . . . . . . . "Natural Hazards and Disaster Risk Reducation"@en . "NHR"@en . . . . . . . . . . . . "Geo-information Management for Land Administration"@en . "GIMLA"@en . . . . . . . . . . . . . . "Geoinformatics"@en . "GFM"@en . . . . . . . . . . . . "Water Resources and Environmental Management"@en . "WREM"@en . . . . . . . . . . . . "Urban Planning and Management"@en . "UPM"@en . . . . . . . . . . . . "Natural Resource Management"@en . "NRM"@en . . "201800303" . "WREM_004" . "7"^^ . "196"^^ . "10"^^ . "2023-07-06T22:00:00Z"^^ . "distance education" . "f2f" . "The course starts with a set of showcases from current research to illustrate the significance of the topic, and to highlight the role of climate change and human interactions and interventions. The course will provide a more in-depth understanding of the processes affecting surface waters, where it is interleaved with (Jupyter notebook) exercises, allowing students to link theory to more practical applications.\n\nIn week 7, student will perform a graded notebook exercise. Students will adapt a template Jupyter notebook exercise to process a dataset or modelling result related to surface water, and perform several experiments to answer questions related to the dataset and scientific problem.\n\nThe field excursion to the river Dinkel serves to illustrate how theory on discharge links to practical experiments, and to show the students the contrast between natural river courses versus man-made waterways.\n\nWeeks 8 and 9 are dedicated to a challenge, where groups of students will develop a small business case where they develop a case on how remote sensing data and/or modelling can be used to serve a customer need. The development of the business case and its pitching in front of a simulated set of entrepreneurs aims to make students learn about different stakeholder perspectives (users, scientist, inverstor), and link the material from the course to a non-academic setting. The contact hours will serve to explain the structure and steps to come to a business case."@en . . . . . . . "A necessary condition is to have attended the WREM courses Q2.1 & Q2.2.M-GEO WREM students, 2nd year M-GEO/M-SE students and short course participants "@en . . . "4"^^ . "4" . "2B" . . . . . . . . "2023-04-23T22:00:00Z"^^ . "Significance\n\nSurface waters such as lakes and rivers play a key role in water management and ecosystems in many countries. On the one hand, they offer direct access to water needed for agriculture, domestic uses, and industry. On the other hand, surface waters act as the interface between groundwater and the atmosphere, through processes such as evapotranspiration, runoff, and aquifer recharge.\n\nAt a geopolitical level, unsustainable anthropogenic use of surface water have a serious potential for conflicts. Many rivers cross international boundaries and upstream usage therefore can create shortages and pollution downstream.\n\nFurthermore, in light of climate change, it is expected that the water cycle will intensify at a global scale (“dry gets drier and wet gets wetter”) but there is still uncertainty on how this will manifests itself at a local and regional level. It is imaginable that some areas see little change in their climatic regime, while others will experience longer droughts more intense floodings and/or changes in the rain seasons.\n\nAims\n\nThis course aims to provide students with a foundation to (1) understand the geophysical processes which affect surface water changes in lakes and rivers, (2) explore various observation methods from space and in situ, and (3) explore ways of adding value to existing datasets. As such, the course will provide students with a skill-set allowing them to tackle surface water problems in various regions of the world, and make them aware of climatic and human factors which are modulating the water cycle with a dedicated focus on lakes and rivers.\n\nThe course offers content which is relevant to the United Nations sustainable development goals (SDG) 6 (Clean water and Sanitation). It furthermore has relevance to SDG 2 (Zero Hunger) through the water use issues of crops, and SDG 11 (Sustainable cities and communities) through water availability for urban areas."@en . "Observing and modelling of surface water in a changing world"@en . . "Observing and modelling of surface water in a changing world"@en . "Observing and modelling of surface water in a changing world"@en . . "201800299" . "NRM_004" . "7"^^ . "196"^^ . "10"^^ . "2023-07-06T22:00:00Z"^^ . "f2f" . "online" . "With lectures, we will introduce you to background knowledge, concepts and theory behind environmental models. Supervised and unsupervised practicals on the environmental models are scheduled throughout the course for hands-on experience. A day is typically closed with a plenary question and answer session. Knowledge is tested with one graded individual assignment and one written test."@en . . . . . . . "(NRM3 is not a prerequisite) Basic knowledge on and skills in remote sensing and GIS. ,Basic knowledge on and skills in remote sensing and GIS."@en . . . . . . . . . "7"^^ . "4" . "2B" . . . . "2023-04-23T22:00:00Z"^^ . "The previous Natural Resource Management (NRM) courses have focused on the inventory natural resources and to detect and assess changes in the environment such as loss of ecosystems and biodiversity, deforestation and forest degradation and threats to food security due to decreased crop yields. Different methods and techniques are available to guide NRM in its efforts to reverse resource degradation or alleviate its consequences. Proper understanding of cause and effect of changes in natural resources is crucial to achieve this. As these changes occur in the real-world, and not in a laboratory set-up, making statements about causal relations is a challenge.\n\nIn this course, students will study generic techniques and apply and evaluate environmental models that aim to estimate change in natural resources in response to environmental changes."@en . "Environmental modelling: causes and impacts of changing resources"@en . . "Environmental modelling: causes and impacts of changing resources"@en . "Env. Modelling: Changing Resources"@en . . "201800291" . "ARS_003" . "7"^^ . "196"^^ . "10"^^ . "2023-04-20T22:00:00Z"^^ . "f2f" . "online" . "The course has lectures to introduce background knowledge, concepts and case studies that include question-and-answer moments. Supervised practicals related to lectures are scheduled throughout the course. Assessed assignments will include submitting exercises, written test, and individual project work about geoscience map generation and interpretation case study, and a final individual examination. Significant time is reserved for self-study and unsupervised practical activity."@en . . . . . . "Students should have experience with GIS and Remote Sensing, and a background in infrared spectroscopy, imaging spectroscopy, and spectral modelling applied to earth resource exploration (spectral geology and spectral data processing courses or equivalent). ,Compulsory for the ‘Applied Remote Sensing for Earth Sciences’ (ARS) specialization of the ‘Geo-information Science and Earth Observation (M-GEO) programme.\nStudents from other specializations and programmes should have experience with GIS and Remote Sensing, and a background in infrared spectroscopy, imaging spectroscopy, and spectral modelling applied to earth resource exploration (spectral geology and spectral data processing courses or equivalent)."@en . . . "4"^^ . "3" . "2A" . . . . . "2023-02-05T23:00:00Z"^^ . "This course gives an introduction to geological remote sensing in the application of earth resources mapping. It includes the integration of regional geophysics and remote sensing imagery for geoscience interpretation and map generation. The course is designed for students with a background in earth sciences and an ability to operate remote sensing and GIS software.\n\nThe course covers descriptions and applications of regional geophysics, radar, and their integration with multi-spectral sensors for geological remote sensing. Background theory of regional geophysical techniques and radar are outlined, including their processing and filtering techniques. The integration of theses datasets with multi-spectral sensors is also outlined. Pre-processing and information extraction algorithms are covered for students to understand the steps involved in converting raw data and images' digital numbers into structural and compositional mapped products. The evaluation of the mapped products and their uncertainties will be also outlined.\n\nThe course includes the practical application and map generation by students of interpreted geological information from relevant geophysical, remote sensing, and geoscience datasets."@en . "Geological Remote Sensing"@en . . "Geological Remote Sensing"@en . "Geological Remote Sensing"@en . . "201800275" . "WREM_002" . "7"^^ . "196"^^ . "10"^^ . "2023-02-02T23:00:00Z"^^ . "f2f" . "The course lasts for 10 weeks, with a balance time between Q2.1 (Physical Processes, this course) and Q2.2 (Earth Observations, sibling course).\nLectures, usually during mornings, explain the physical process in the radiation, energy and water balance, its components and the application examples to Water Productivity and Droughts. Lectures are both in class and recorded.\nThe practice is both supervised and unsupervised, although the responsible staff is always available for consultation. Practical style are chosen to best suit the process under study: exercises using standard tools (Excel sheets, calculations) to grasp the main (1D) “vertical” processes. The extension to 2-3D is done in Q2.2 in a natural conjunction along the course.\nThe blending between the theory and the practical is done through the use of Jupyter NoteBooks (JNB) where complementary explanations and exercising are together. Python is slowly introduced in this routinely work that is part of the Centre of Expertise in Big Geodata Science (CRIB) at ITC.\nThe course counts on Question Hour, practice quizzes and exploration in Field measurement and devices from the new LILA experimental site of the UT."@en . . . . . . . "Core ITC (Q1). Physics and math background. ,To have completed the Core Course of ITC (Quartile 1).\nThe strongly advised conditions are good skills in physics and math, high marks in the Remote Sensing related topics of the Core (Q1), have previous exposure to hydrology and activities in the Water Sector."@en . . . . . . . . . . "13"^^ . "2" . "1B" . . . . . . . . . "2022-11-13T23:00:00Z"^^ . "The interrelated Water and Energy cycle ultimate control all water presence and climatic processes on Earth, and consequently, the life of all beings and its quality. To understand those cycles is foundational to any conservative and sustainable action we, as professionals, may attempt in our environment. This course digs into the most critical and delicate balance of nature. \n\nTo explain the importance of the components of the water and energy cycle, the course envisages two end practical examples: the calculation of Water Productivity (Crop per Drop) and the evaluation of droughts. Water Productivity estimates is obtained after the studies of the radiation balance and evapotranspiration and droughts is the end product of the previous learnings and the addition of the precipitation, soil moisture and groundwater concepts. Along the course physical processes and their Remote Sensing retrievals are fully integrated.\n\nIt is to note that this Q2.1 is designed being supplementary to the Q2.2, in a dual treatment manner, wherein Q2.1 focuses on the understanding of Physical Processes and Q2.2 on Earth Observation of the Water and Energy Cycles of Earth System."@en . "Hydrological and Environmental Cycles"@en . . "Hydrological and Environmental Cycles"@en . "Hydrological and Environmental Cycles"@en . . "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 . . "201800318" . "ARS_004" . "7"^^ . "196"^^ . "10"^^ . "2023-07-06T22:00:00Z"^^ . "f2f" . "Combination of self-directed learning in individual assignments, learning by joint work with colleagues in a group assignment during field data collection, and theory lectures in support of the practical work and operation of field equipment."@en . . . . . . "Compulsory for the ‘Applied Remote Sensing for Earth Sciences’ (ARS) specialization of the ‘Geo-information Science and Earth Observation (M-GEO) programme.\nStudents from other specializations and programmes should have a background in earth sciences, knowledge of GIS and Remote Sensing techniques for geological applications, and a basic understanding of chemical analytical methods"@en . . . "6"^^ . "4" . "2B" . . . . "2023-04-23T22:00:00Z"^^ . "Field methods play an important role in geological remote sensing studies for validation of remote sensing interpretations and characterization of rocks and geological environments.\n\nThis course introduces students to state-of-the-art methods for field validation and characterization of rock and outcrop. Methods include the acquisition of measurements of mineralogical and chemical rock composition and physical rock properties. Acquisition of field data is practiced with a variety of field instruments, including reflectance and gamma-ray spectrometers and portable XRF.\n\nThe preparation and execution of a field campaign is also practiced in this course. A remote sensing study is performed prior to field work and forms the basis for the preparation of detailed field data acquisition plans. Data collection using various sampling strategies and different instruments will be exercised in the field and includes assessment of data quality. Results of the field campaign are analysed, interpreted and integrated with the results of desk studies. Additional measurements may be performed in the ITC geoscience laboratory."@en . "Field measurements and validation"@en . . "Field measurements and validation"@en . "Field measurements and validation"@en . . "201800277" . "UPM_001" . "7"^^ . "196"^^ . "10"^^ . "2023-02-02T23:00:00Z"^^ . "f2f" . "A variety of approaches will be mixed. Introductory lectures (primarily dealing with theory and concepts), discussion sessions (in which particulars such as literature, videos or other materials are being discussed) practicals (in which concepts and methods that have been studied will be practiced by the students), tutorials (cook book style assignments to learn to apply methods and tools) and a local fieldwork to gather data in the field and integrate these in the assignment.\n\nParticipation and attendance:\n\nMandatory attendance for supervised practicals, fieldwork activities and seminars is required;\nDue to educational activities that require active involvement (e.g. group presentations), the lecturer may demand mandatory attendance during lectures or parts thereof.\n The course coordinator will communicate this at the start of the course."@en . . . . . . "M-Geo Core courses"@en . . . . . . . . . . "7"^^ . "2" . "1B" . . . . . . . "2022-11-13T23:00:00Z"^^ . "This course aims to develop a critical understanding of spatial planning based on academic discourses, the international development agenda and students' own experiences. Throughout the course the role of spatial data and information systems in urban planning and management will be highlighted and illustrated.\nStudents will develop a spatial understanding of specific urban issues in the students' home country by applying knowledge and skills in spatial information handling. Students are introduced to a set of both spatial and non-spatial methods relevant for the practice of urban planning and management. The concepts of Sustainability, Gentrification and Informality will be introduced and discussed. Available databases and data catalogues are explored to discuss different approaches to sustainability frameworks and assessments, and to understand the urban processes of gentrification and informality."@en . "Planning Sustainable Cities"@en . . "Planning Sustainable Cities"@en . "Planning Sustainable Cities"@en . . "201800286" . "GIMLA_002" . "7"^^ . "196"^^ . "10"^^ . "2023-02-02T23:00:00Z"^^ . "f2f" . "hybrid" . "This course is taught through lectures and hands-on activities presented as exercises. An individual assignment and a group assignment evaluate learning of practical skills and an exam assesses the students’ understanding of concepts introduced in the course. Exercises and assignments are performed using software introduced during lectures or supervised practical sessions and, where possible, real-world data-sets are used.\n\nThe group assignment is completed as part of the LIS Workshop during which student groups develop a software prototype that implements one or more land administration processes using the Scrum method. The Scrum approach, used in most modern software development projects, is introduced at the beginning of the course. Students have the opportunity to practice using the Scrum method in exercises."@en . . . . . . "GIMLA_001 (Responsible Land Information); MGEO-Core (core_001, core_002, core_003) ,Experience in Land Administration or motivated to work in this domain. It is an advantage to have:\n\nfollowed the course Responsible Land Administration, or\na basic understanding of Geographic information models, or\nexperience/background/knowledge in an ICT or IS field"@en . . . . "5"^^ . "2" . "1B" . . . . . . "2022-11-13T23:00:00Z"^^ . "Land information systems are systems for acquiring, processing, storing, and distributing information about land. They may contribute to secure land tenure or support land valuation, land use planning and land development. Despite contextual differences between countries, there are fundamental concepts that apply to all land information systems. The main objective of this course is to discover, apply, and assess these concepts and technologies – and inspire students to deploy them in the creation and maintenance of scalable real-world land information systems.\n\nThe course focuses on the modeling of data and processes for the implementation of Information Systems for Land Administration. It therefore has two integrated series of lectures: one focusing on data modeling and implementation in a spatially enabled database management systems; the other focusing on the identification and modeling/design of software functionalities that support land administration processes. These two parts are linked together by a practical LIS prototyping workshop."@en . "Land information systems and models "@en . . "Land information systems and models "@en . "Land information systems and models "@en . . "201800278" . "NRM_001" . "7"^^ . "196"^^ . "10"^^ . "2023-02-02T23:00:00Z"^^ . "We apply a mix of different activating teaching and learning approaches which includes interactive teaching, reflective teaching (learning by doing), e-learning, individual and group exercises and problem-based project work."@en . . . . . . . . "Core_001, Core_002, Core_003 ,A prerequisite is to have finished the core modules at ITC or to have a basic level in GIS and remote sensing."@en . . . "1"^^ . "2" . "1B" . "2022-11-13T23:00:00Z"^^ . "Natural resources management has a multi-disciplinary character. So does this course. Students will learn to unravel complex systems and to deal with different stakeholders and conflicting interests in Natural Resources Management. It will set a common basis for all sorts of research and other activities in the field of NRM. Particular attention is given to the spatial and temporal dynamics of natural systems and data needs for the management of these.\n\nConcepts of NRM are reviewed and discussed. Students are introduced to apply systems thinking and learn to apply analytical reasoning when translating complex real-world situations into conceptual diagrams. This enables them to describe and develop knowledge about how ecosystems work and how humans make an impact on natural systems. Students discover how essential this step is in identifying meaningful biophysical and socio-economic variables for scientifically sound decision making and management of natural resources. They also put themselves in the shoes of a stakeholder in an NRM conflict and apply remote sensing and GIS to help making claims or illustrate possible solutions. Conceptualising real-world situations helps students in identifying knowledge gaps and formulating research hypotheses.\n\nNatural Resources Management is a multiple-stakeholder effort per default. Therefore, part of the assignments will involve working in multi-disciplinary teams."@en . "Systems approach for management of natural resources"@en . . "Systems approach for management of natural resources"@en . "Systems Approach for Mgt of Nat. Resourc"@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 . . "201800273" . "ARS_001" . "7"^^ . "196"^^ . "10"^^ . "2023-02-02T23:00:00Z"^^ . "f2f" . "online" . "The course is designed for self-directed learning in an online (e-learning) setting. Independent of the COVID-19 situation, the majority of the course can be done online or at home. The course uses short lectures to introduce course components; interactive sessions for plenary question-and-answer moments as well as personalized feedback; and individual practical assignments. During the course is ample time for self-study and experimenting with scripting and data processing."@en . . . . . . "Students should have introductory-level experience with GIS and Remote Sensing and possess an affinity with earth sciences, physical geography or spatial sciences.An account with Google for accessing the EarthEngine ,Participants should have introductory-level experience with GIS and Remote Sensing and possess an affinity with earth sciences, physical geography or spatial sciences. Participants will need an account with Google and Google Earth Engine to follow the practicals."@en . . . "3"^^ . "2" . "1B" . . . . "2022-11-13T23:00:00Z"^^ . "Earth observation (EO) satellites generate large amounts of geospatial data that are freely available for society and researchers. Technologies such as cloud computing and distributed systems are modern solutions to access and process big Earth observation data. Examples of online platforms for big Earth observation data management and analysis are, just to name a few popular ones, the Google Earth Engine, the Sentinel Hub and the Open Data Cube.\n\nThis course is on processing remote sensing data from operational and historic missions in an online platform, with specific emphasis on earth science applications. The course first gives an introduction to scripting with a higher-level programming language, such as Python or JavaScript. Writing own scripts allows to create custom processing solutions, automate such processing chains, apply them to various remote sensing data and provide scalable solutions for handling small or large data sets. The application to Earth sciences will help you to recognize landforms in images, determine earth surface composition and derive various physical parameters from the Earth surface."@en . "Spectral Data Processing"@en . . "Spectral Data Processing"@en . "Spectral Data Processing"@en . . "NRM_002" . . . . . . . . . . . . . . . . . . . . . . "From Data to Geo-information for Natural Resources Management"@en . "201800284" . "7"^^ . "196"^^ . "10"^^ . "2023-02-02T23:00:00Z"^^ . "f2f" . "hybrid" . "The main component of the course is an NRM case study, which requires the definition of a prototype data processing chain adapted to the specific characteristics of the NRM problem under consideration.\n\nDuring the course, students will be guided in the development of this prototype data processing chain through lectures, tutorials and supervised practical. At the end of each week, students have to submit an individual assignment related to the definition of one component of the prototype (e.g., conceptual design, EO and GIS database, etc.). During the process, students can interact with their peers and course staff to define the processing chain and implement the prototype version in GEE."@en . . . . . . . "CORE_001, CORE_002, CORE_004, RS, GIS, concepts of NRM, and systems-based thinking. Students should have some GIS and remote sensing background. "@en . . . . . . . . . "5"^^ . "2" . "3" . "4" . "1B" . . . . . "2022-11-13T23:00:00Z"^^ . "Sound natural resource management requires adequate geoinformation describing the spatial and temporal dimensions of ecosystems. This involves - in most cases - large datasets from multiple sources and stakeholders from different disciplines and institutions. The collection of these data and the definition of ad-hoc automatic data processing chains are nowadays necessary to support planning or management activities of a forest, agricultural or ecological systems.\n\nDuring this course, the student will learn the basic concepts for the conceptual design and development of a prototype data processing chain based on Earth Observation (EO) and Geographic Information Systems (GIS) to support planning and decision-making in Natural Resource Management (NRM) situations. Upon completion, students will acquire the knowledge and skills necessary for the collection, preparation, processing and interpretation of spatial information provided by EO and GIS data to address a specific NRM problem.\n\nAt the end of the course, the student should be able to execute simple scripts, make minor modifications and search online for existing scripts to design a basic processing chain. The developed prototype must be presented, explained and justified in the final report."@en . "From data to geo-information for natural resources management"@en . "From Data to Geo-info for NRM"@en . . "201800283" . "UPM_002" . "7"^^ . "196"^^ . "10"^^ . "2023-02-02T23:00:00Z"^^ . "f2f" . "Lectures, supervised practicals, discussion sessions (literature seminars), individual assignment, group assignment.\n\nParticipation and attendance:\n\nSince many of the educational activities require active involvement attendance of supervised practicals, literature seminars & group presentations is highly advisable"@en . . . . . . . "Completion of ITC course GIS and RS for Geospatial Problem Solving, or equivalent."@en . . . . . . . . . . . "7"^^ . "2" . "1B" . . . . . . . . "2022-11-13T23:00:00Z"^^ . "Cities are unequal. Considerable parts of the urban population, especially in the Global South, are poor, whereas others are affluent. In part, poverty is associated with the influx of poor rural immigrants in need of jobs, shelter and basic services such as water, electricity, education and health care. Levels of access to these basic services can differ a lot between socio-economic groups and will also vary across urban spaces. To address such inequalities, contemporary urban development strategies and policies are directed toward the inclusion of socially and economically weaker groups. These groups need to benefit most from sustainable planning interventions. Here, inclusiveness and competitiveness need to be linked, as only inclusive cities can be truly competitive. Successful cities offer competitive locations and are centres of innovation, where liveability and inclusiveness are important factors. When analysing the economic performance of an urban region, the role of geography needs explicit consideration as urban competitiveness requires an understanding of spatial relationships inside cities (e.g., variations of locational factors and clustering of economic activities). Furthermore, the role of land use (planning) and land markets is essential for understanding competitiveness in all its dimensions for building competitive and inclusive cities."@en . "Building inclusive and competitive cities"@en . . "Building inclusive and competitive cities"@en . "Building inclusive and competitive cities"@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 . . "201800287" . "ARS_002" . "7"^^ . "196"^^ . "10"^^ . "2023-02-02T23:00:00Z"^^ . "f2f" . "flipped classroom" . "This research-informed course contains lectures to introduce new theory, reading assignments and other self-study exercises with associated feedback sessions to deepen the theory, and supervised and unsupervised practicals to put the theory into practice. The course furthermore contains hands-on introductions to some key GeoScience Laboratory instruments. Overall, the course has a very strong experiential learning component.\n\nThe course will be completed by a group assignment in which skills from the course will be applied to an authentic sample set to produce a useful dataset and relevant scientific results in, as much as possible, a real-world context."@en . . . . . . . "Students from other specializations and programmes should have introductory level experience with GIS and Remote Sensing, have an affinity with Earth sciences, and have a good background knowledge of rocks and minerals. ,Compulsory for the Applied Remote Sensing for Earth Sciences (ARS) specialization of the Geo-Information Science and Earth Observation (M-GEO) programme.\n\nStudents from other specializations and programmes should have introductory level experience with GIS and Remote Sensing, have an affinity with Earth sciences, and have a good background knowledge of rocks and minerals."@en . . . "6"^^ . "2" . "1B" . . "2022-11-13T23:00:00Z"^^ . "This course focuses on the use of spectroscopic methods to obtain geological information related to, for example, minerals and rocks, mineralised and geothermal systems, soils and other natural materials. It is designed for students with a solid understanding of Earth Sciences who wish to use state-of-the-art spectroscopic methods to analyse the mineral content and texture of samples.\n\nThe course will cover the interaction of matter with electromagnetic radiation of different wavelength ranges (e.g. visible, near- & short-wave infrared, as well as long-wave infrared). The students will be involved in laboratory measurements with various imaging and non-imaging spectroscopic instruments, and compare and contrast the results with those from other mineralogical and geochemical analytical methods. \n\nThe course further contains a component on statistical data processing and (semi-) quantitative spectral modelling techniques derived from current research. These analytical techniques will lead to information on the mineralogy and mineral chemistry of samples, as well as Earth surface parameters. The students will experiment with, validate and compare multiple approaches, investigate their assumptions and limitations, and critically evaluate their suitability to solve Earth science problems."@en . "Spectral Geology"@en . . "Spectral Geology"@en . "Spectral Geology"@en . . "201800312" . "UPM_004" . "7"^^ . "196"^^ . "10"^^ . "2023-07-06T22:00:00Z"^^ . "f2f" . "The students will work in a studio setting, i.e. they will work in teams pro-actively on a given case study project throughout the entire course. Project teams will need to develop a work plan that they then follow. Inputs in terms of lectures on certain topics, issues and methods as well as feedback and supervision by the team of lecturer will be provided as needed.\n\nImportant concepts, methods and techniques that have been addressed earlier in the curriculum can also be applied. Students need to demonstrate that they are able to describe, analyse and discuss a planning problem and come up with well-motivated plans that are risk sensitive. The emphasis will be on their ability to critically discuss and explain choices and to critically reflect on the proposed course of action.\n\nA link will be made with ESA course Q4. Lectures will be given partly to both student populations and some group assignments will be interdisciplinary in group composition and tasks.\n\nParticipation and attendance:\n\nCompulsory attendance for supervised practicals, fieldwork activities and seminars is required;\nDue to educational activities that require active involvement (e.g. group presentations), the lecturer may demand mandatory attendance during lectures or parts thereof.\n The course coordinator will communicate this at the start of the course."@en . . . . . . . "UPM1-3 ,All students in the UPM specialization are accepted. Students following other specializations or programmes should have a background in urban planning."@en . . . "5"^^ . "4" . "2B" . . . "2023-04-23T22:00:00Z"^^ . "Urban areas and their populations are often seriously affected by hazards (e.g. natural, biological, technological hazards or combinations of these). They also have to adapt to the impacts of climate change. Accordingly, city authorities, planners and other stakeholders are searching for ways to be more risk-sensitive in their plans and actions. Becoming resilient includes developing the capacities to meet such challenges.\n\nThis course addresses concepts of urban risk management and approaches to integrate risks associated with hazards and climate change into urban planning and management strategies and actions. GIS-based methods to conduct urban risk and vulnerability assessments and evaluate potential planning interventions will be learned and applied."@en . "Risk-sensitive Urban Planning Studio"@en . . "Risk-sensitive Urban Planning Studio"@en . "Risk-sensitive Urban Planning Studio"@en . . "201800276" . "NHR_001" . "7"^^ . "196"^^ . "10"^^ . "2023-02-02T23:00:00Z"^^ . "f2f" . "The course is based on student-centered learning principles, whereby students will be enabled to cut though the complexity of natural systems, risk situations and disaster scenarios in this case, and learn to identify relevant questions to understand complex systems. In a project-based setting students will work backwards from a disaster event to discover the genesis of the event through understanding of the conceptual elements. The aim is for students not only to learn about theoretical aspects of different hazard and disaster types, but to understand the conceptual links, and to gain the ability to apply the risk concepts to different contexts and scales. A further aim is to enable the students to identify relevant questions before sourcing answers, including from other ESA staff members. There will further be emphasis on presentations (including groups to each other) and critical discussion. At critical points students will receive lectures, but the course is more strongly aimed at self-discovery of relevant facts, concepts and methods. Select RS analysis methods will be taught in a practical setting, while others will be discovered as part of the group work. In addition, skills related to the use of different data acquisition techniques will be gained during a field excursion. With courses Q2.1 and 2.2 running in parallel, the teaching of different modelling techniques will be aligned with the introduction relevant key input data, and some classes will be done in a plenary setting, involving different NHR teachers. Research skills will also be incorporated into the course where appropriate, rather than taught in parallel."@en . . . . . . . . . "Compulsory for the ‘Natural Hazards and Disaster Risk Reduction’ (NHR) specialization of the ‘Geo- information Science and Earth Observation (M-GEO) programme. Students from other specializations and programmes should have introductory level experience with GIS and Remote Sensing, and a background in earth sciences, geography, environmental science, physics, data science, or civil engineering."@en . . . "1"^^ . "2" . "1B" . . . . . . . . . "2022-11-13T23:00:00Z"^^ . "This course will provide a fundamental introduction to natural hazards and the disaster risk concept, as well as the role of geomatics, in particular remote sensing (RS). It builds on the knowledge students gained in the core courses on basic RS and GIS principles, and expands it. The course aims at creating a knowledge base for the other hazard modelling and risk management courses and electives in the NHR specialization, by enabling the students to develop a solid understanding of the main geohazard types, and all relevant conceptual aspects of disaster risk. Students will learn how geo-information and geomatics tools are uniquely suited to study, monitor and quantify each aspect of risk and disasters. Following an introduction to the main hazard types and their core properties, students will dissect past disaster events to discover the nature and properties of the underlying hazards and vulnerabilities, and learn how in particular RS provides comprehensive and specifically tailored means to gain insights into the risk components for different hazards and environmental settings. The course runs in parallel to the Statistically-based Hazard Modelling course (Q2.2), and both are closely coupled. Particular attention will be given to the generation of input data for hazard modelling, including image-based indices and topographic derivatives. Relevant background information on soils, geology and landforms as drivers of hazards will also be provided. Academic skills will be taught together with this course in an integrated manner."@en . "Introduction to Hazard and Risk"@en . . "Introduction to Hazard and Risk"@en . "Introduction to Hazard and Risk"@en . . "201800292" . "NRM_003" . "7"^^ . "196"^^ . "10"^^ . "2023-04-20T22:00:00Z"^^ . "f2f" . "online" . "The course takes a student-centered (inquiry-based) approach to teaching and learning. Students assume an active/participatory role in their education, while teachers are facilitators who encourage interaction with new material presented and reflective thinking. The teacher uses class discussions, hands-on practicals and other experiential learning tools to track student comprehension, learning needs and academic progress over a teaching unit. Three summative assessments (written exam + individual assignment + final group project) measure how well the students achieve higher order thinking and learning outcomes."@en . . . . . . "NRM_001 and NRM_002 are not prerequisites. Basic knowledge on and skills in remote sensing and GIS. ,Geo-Information Science and Earth Observation: A Systems-Based Approach\n\nSystems Approach for Management of Natural Resources (NRM specialization 2.1)\n\nFrom Data to Geo-Information for Natural Resources Management (NRM specialization 2.2)\n\nNRM_001 and NRM_002 are preferred. "@en . . . . . . . . . . "9"^^ . "3" . "2A" . . "2023-02-05T23:00:00Z"^^ . "The 21st century has witnessed an increase in the availability of Earth observation (EO) data and their use in addressing critical problems in natural resources management (NRM). The myriad of datasets and stakeholder needs can make the selection of a specific sensor and analytical technique to address a problem a daunting task. At the heart of this dilemma is the scale of observation at which we can effectively address the problem. Biophysical processes, flows or interactions can occur at the plant, canopy or regional scale. Similarly, image-based map products have a specific purpose. For example, food security analysts may want to know the location of crop field boundaries in an agroecosystem, while foresters may want to assess forest stand biomass.\n\nThe guiding principle of this course, therefore, is to use the scale observation together with stakeholder needs to select and apply an appropriate EO dataset and analytical technique to solve problems within the three NRS Forest, Agriculture and Environment in the Spatial Sciences (FORAGES) themes (biodiversity conservation, forest management and food security analysis). In the end, students will be able to design a workflow to address these problems that includes the appropriate selection of EO data and analytical techniques."@en . "Mapping and monitoring for natural resources management"@en . . "Mapping and monitoring for natural resources management"@en . "Mapping & Monitoring for NRM/EO for Natural Resources Management"@en . . "201800285" . "WREM_001" . "7"^^ . "196"^^ . "10"^^ . "2023-02-02T23:00:00Z"^^ . "f2f" . "The course lasts for 10 weeks with 2 days a week, and the Q2.1 (Physical Processes) and Q2.2 (Earth Observations) of water and energy cycles in the Earth system are designed as such to be closely complementary to each other. The course is designed for a continuous flow and the student is mostly unaware of this partition, adding to the robustness of the teaching.\n\nIn this way, the 10 weeks are divided in topics covering Water and Energy Balance components, each of which could last between 1 to 2 weeks depending on the complexity. Each topic ends up with a Question Hour direct to the involved staff. A number of quizzes are designed along the way as formative assessments, able to correct misalignments in the studies.\n\nSome topics have field trips to the novel LILA site at the campus in the University of Twente, where students practice on equipment and measuring devices."@en . . . . . "Core ITC (Q1). Physics and math background. ,knowledge of geometry, goniometry, integration, differentiation"@en . . . . . . . . . . "13"^^ . "2" . "1B" . . . . . . "2022-11-13T23:00:00Z"^^ . "Water and energy are fundamental for life on Earth, their variations, trends, and extremes are sources for drought extremes, heat waves, heavy rains, floods, and intensive storms that are increasingly threatening our society to cause havoc as the climate changes. Better observations and analysis of these phenomena will help improve our ability to understand their physical processes (as introduced in Q2.1) and to model and predict them. Earth Observation technology is a unique tool to provide a global understanding of essential water and energy variables and monitor their evolution from global to basin scales. In this course, you will learn the physical principles of how electromagnetic signals were applied to monitor these essential variables by spaceborne sensors, and learn tools and methods to collect, process, and visualize Earth observation data of surface solar radiation, evapotranspiration, precipitation, soil moisture, and terrestrial water storage. Furthermore, students will learn how to retrieve the essential water/climate variable – soil moisture from Earth observation data, applying the radiative transfer theory."@en . "Earth Observation of Water Resources"@en . . "Earth Observation of Water Resources"@en . "Earth Observation of Water Resources"@en . . "201800293" . "UPM_003" . "7"^^ . "196"^^ . "10"^^ . "2023-04-20T22:00:00Z"^^ . "f2f" . "A variety of approaches will be used. Introductory lectures (primarily dealing with theory and concepts), discussion sessions (in which particulars such as specific literature, videos or other materials are being discussed), practicals (in which concepts and methods that have been studied will be practiced by the students), tutorials (cook book style assignments to learn to apply methods and tools), a local fieldwork to gather data in the field and integrate these in the assignment, guest lectures (of practitioners in transport and land use planning) and an excursion.\n\nParticipation and attendance:\n\nCompulsory attendance for supervised practicals, fieldwork activities and seminars is required;\nDue to educational activities that require active involvement (e.g. group presentations), the lecturer may demand mandatory attendance during lectures or parts thereof.\n The course coordinator will communicate this at the start of the course."@en . . . . . . . . "Basics in GIS equivalent to M-Geo core courses. Background in urban planning, geography, engineering or related is an advantage."@en . . . "5"^^ . "3" . "2A" . . . . "2023-02-05T23:00:00Z"^^ . "Cities are centres in which a variety of functions and activities are organised in a relatively compact space. People engage in these activities through spatial interaction. The way in which these activities are arranged spatially has a huge bearing on the amount of spatial interaction (and thus travel demand) generated and the infrastructure required to facilitate this interaction. The physical manifestation of this spatial arrangement is referred to as urban form, a concept which can help us understand the way cities function in terms of their spatial structure and pattern, at different scales. The processes of land use and infrastructure development that determine urban form are closely linked and are mutually influencing. In this course, we investigate urban form and are addressing urban spatial development concepts in terms of their spatial interaction. We look at the most important theoretical concepts that describe the relation between land use and transportation. We make use of a variety of modelling tools and techniques to help analyse and understand this mutual relation and come up with better spatial planning policies."@en . "The Compact City"@en . . "The Compact City"@en . "The Compact City"@en . . "201800289" . "NHR_003" . "7"^^ . "196"^^ . "10"^^ . "2023-04-20T22:00:00Z"^^ . "f2f" . "The students will focus on the principles and modelling of selected natural hazards through a combination of theory, practicals, and hazard assessment project. Interactive lectures and tutorials in the form of group discussions are planned to facilitate the introduction and comprehension of critical scientific and engineering concepts. The flipped classroom technique will be used as a self-paced educational method to promote the personal involvement of the student in the learning process and to enhance independent thinking. The educational aim of this course is twofold: on one hand, to provide the students with a range of modelling tools in order to develop their practical and technical skills; and on the other, to promote their ability to reason well and to encourage their disposition to do so, at the moment of discussing modelling assumptions, suitability and limitations. These aims are planned to be achieved through supervised practicals and short individual or group assignments, in an initially guided and, later on, more independent environment. Sensitivity analysis of the models and comparison and interpretation of their results, (e.g. using different datasets, modelling techniques and parameters) are intended to trigger active exploration of and reasoning on the physical processes and simulations. Students are further encouraged to deepen into theory and practice with supplementary material to independently explore during the group projects."@en . . . . . . "core courses. This is an elective as part of track NHR,Compulsory for the ‘Natural Hazards and Disaster Risk Reduction’ (NHR) specialization of the ‘Geo-information Science and Earth Observation (M-GEO) programme.\nStudents from other specializations and programmes should have experience with GIS and Remote Sensing, and a background in earth sciences, geography, environmental science or civil engineering."@en . . . "5"^^ . "3" . "2A" . . . "2023-02-05T23:00:00Z"^^ . "The aim of this course is to enhance the student’s understanding of the physical processes that cause natural hazards, the methods and the physically-based modelling approaches for hazard analysis, to the point at which students are able to use them with their own data. As the processes of selected natural hazards, including flooding, landslides and earthquakes, are explained, the students will be introduced to fundamentals of the underpinning science and engineering. Model data requirements and data collection will be treated, as well as the evaluation of uncertainty of input data on simulation outputs. Modelling principles and assumptions, possibilities and limitations will be discussed with the aim that students can make a proper selection of models for a given situation and critically reflect on the results, in order to support hazard analysis as input to risk management and mitigation."@en . "Physically-based Hazard Modelling"@en . . "Physically-based Hazard Modelling"@en . "Physically-based Hazard Modelling"@en . . "201800304" . "NHR_004" . "7"^^ . "196"^^ . "10"^^ . "2023-07-06T22:00:00Z"^^ . "f2f" . "hybrid" . "Students will be encouraged to find creative solutions in the use of models, data, and concepts taught as well as state-of-the-art literature and consultation of in-house experts. Introductory lectures are given by teachers that give an overview of the particular topic and guide students with respect to main methods and techniques. For most of the topics treated, an accompanying GIS exercise is offered, in which students can apply what was taught. The exercises contain also advanced sections, where students are further challenged to come up with new solutions. Answer sheets are provided for each of the exercises. Most of the exercises relate to RiskCity, a (partly) hypothetical case study city in a developing country that is exposed to multiple hazards (earthquakes, floods, landslides, technological hazards). Several larger case studies are included where students work in small groups on a particular problem in a real case study related to risk assessment. Students build up a portfolio of assignments. \n\nThe teaching approach contains:\n\n1 - Keynote lectures to introduce key concepts and principles\n\n2 - Supervised practicals to bring the knowledge into practice using a range of tools\n\n3 - Tutorials for personalized and plenary feedback and to explore more independently the use of knowledge and tools\n\n4 - Project work, either individual or group projects"@en . . . . . . "Compulsory for the ‘Natural Hazards and Disaster Risk Reduction’ (NHR) specialization of the ‘Geo-information Science and Earth Observation (M-GEO) programme.\nStudents from other specializations and programmes should have introductory level experience with GIS and Remote Sensing, and a background in earth sciences, geography, environmental science or civil engineering."@en . . . . . . . . . "9"^^ . "4" . "2B" . "2023-04-23T22:00:00Z"^^ . "The knowledge of hazardous processes and the ability to predict their occurrence in terms of intensity and frequency and their interaction are important requirements to quantify their impact on society. This module focuses on the analysis of the risk, its evaluation, and its use in decision making for different disaster management phases.\n\nThe assessment of risk is a very multi-disciplinary field, that requires knowledge on hazards (types, frequency, intensity, modeling methods), elements-at-risk (types, classification, data collection, quantification), vulnerabilities (physical, social, environmental, institutional), capacities (to predict, cope, and recover) and resilience. Risk could be expressed as qualitative classes, risk matrices, or quantified as expected losses (e.g. monetary values, population). \n\nQualitative and/or quantitative risk assessment is used as a basis for different types of decision-making by various stakeholders, with different objectives: evaluating different risk reduction planning alternatives; link meteorological forecasts with loss estimation in impact-based forecasting; analyze post-disaster reconstruction alternatives in order to “build-back-better”, and increase the resilience. From the perspective of a continuously changing world, driving forces such as climate change, socio-economic development, population growth, and land-use change will put pressure on society, and require that risk is analyzed for future scenarios in order to plan wisely."@en . "Disaster Risk Management"@en . . "Hazard and Risk Studio/Disaster Risk Management"@en . "Disaster Risk Management"@en . . "201800294" . "GIMLA_003" . "7"^^ . "196"^^ . "10"^^ . "2023-04-20T22:00:00Z"^^ . "f2f" . "online" . "Active learning approach will be applied to the lectures with more theory\nLectures are supported by PPT and references to reading material\nThe students are asked to write a project proposal for a tender applying the theoretical knowledge obtained from the lectures in a group assignment"@en . . . . . . . "Basic land surveying skills and knowledge, and operational knowledge of ESRI ArcGIS, ERDAS, and Microsoft Office. Intermediate knowledge of cadastres, land registration, land information systems. Basic notions of conceptual modelling."@en . . . . . . . . . "8"^^ . "3" . "2A" . "2023-02-05T23:00:00Z"^^ . "Land Informatics is the science and technology that deals with the creation, maintenance, and dissemination of land information. It uses the existing structures of geoinformatics to design fit-for-purpose land administration systems. 3D Cadastres are land administration concepts, technologies, and systems that deal with the height dimension. Moreover, the use of ICT, open source, proprietary and web-based services, have seen an emergence of innovative cadastres. They can efficiently support unconventional land administration through documentation and management of land rights.\nThis course aims to provide contemporary knowledge, hands-on experience, and implementation know-how in land informatics and 3D Cadastre using innovative tools. Through practical sessions, students obtain experience and a better understanding of the possible innovations and their applications. Their relevance for different country contexts and scenarios are evaluated."@en . "Cadastral data acquisition technologies and dissemination methods"@en . . "Cadastral data acquisition technologies and dissemination methods"@en . "Cadastral data acquisition technologies and dissemination methods"@en . . "201800305" . "GIMLA_004" . "7"^^ . "196"^^ . "10"^^ . "2023-07-06T22:00:00Z"^^ . "f2f" . "In this course the socio-technical processes involved in organizational change are addressed from social science and from applied technology angles as stated in the introduction. Social science focuses on insights from organization and management studies critical data studies and geodata ethics . To grasp these insights and their relevance to practice lectures are complemented by student-led activities, including the analysis of relevant literature and discussions, and application of organizational assessment and strategy building frameworks. The applied technology angle of the course is addressed through two extensive practical periods with assignments (ca. 1/2 of the allocated time of the course), during which students will acquire and apply technological skills to manage organizational workflows and to analyse web services for spatial data provision. Through the incorporation of literature analysis activities, focus group and interview methods into activities and assignments the course also provides opportunity to learn and practice these research skills that are applicable beyond the specific course content."@en . . . . . . "Understanding and knowledge of basic land administration concepts and principles\nBasic critical reading/writing ability and analytical skills\nFluency in using computers and online data searches\nAffinity with and/or openness towards learning the techniques of workflow digitalization\nDesire to understand both institutional and technical dimensions of the organizational processes"@en . . . "4"^^ . "4" . "2B" . . . . . "2023-04-23T22:00:00Z"^^ . "Land administration has long been executed through state-based agencies such as cadastral departments, land registry offices, ministries of land, or local governments with their own analogue or digital data repositories. These organizations do not act in a vacuum, but within larger institutional fields and forces. The broader environment of land governance, in which public organizations operate, is characterized by the interactions of multiple state and non-state actors, formal and informal practices, a multitude of regulatory frameworks and increasing global interconnectivity. This environment has been witnessing public sector reforms and increased adoption of (geo)Information and Communication Technologies (ICT), including automatization techniques, mobile device generated data, crowdsourcing and advanced remote sensing technologies. In many places more established forms of organizing meet latest technological developments. While some organizations are beginning to digitize paper-based workflows, others may function through highly automated and digitized processes. At the same time information technologies and digital data are not merely neutral tools, but they reflect, transport and transform the practices and values of organizations and institutional fields.\n\nIt is important therefore to understand and learn how to describe, explain, and assess organizational change in response to changing environments, (geo-)ICT implementation, and related forms of data sharing, uses and dissemination. In this course, these socio-technical processes are addressed from social science and from applied technology angles"@en . "Organizing Land Information"@en . . "Organizing Land Information"@en . "Organizing Land Information"@en . . "201800303" . "WREM_003" . "7"^^ . "196"^^ . "10"^^ . "2023-04-20T22:00:00Z"^^ . "distance education" . "f2f" . "The course SHADES-OF-BLUE will be offered as part of the M-GEO programme and will therefore be delivered in a hybrid setup (face-to-face and online) in the teaching rooms of the University of Twente. The lectures will be recorded and shared with the students. During the lectures, students are exposed to new concepts followed by hands-on practical exercises. A field excursion is organized to provide the students with practical skills to collect in-situ data for calibration and validation purposes. The students are requested to be physically present during the field excursion to improve their learning gain.\n\nDuring the assignment, the students will be coached while they are working on developing the specific application of the assignment. The students are requested to work in groups and prepare a case study from the selected challenge and provide the details of the application developed as well as the results obtained in a report supported by a poster presentation.\n\n \n\nThe main sub-courses forming this course (namely, Ocean-climate nexus, Coastal systems and sea-level rise, Water pollution and Blue productivity) with their corresponding challenges will also be offered as distance education courses."@en . . . . . . "M-GEO core & preferably WREM specialization track courses from Quartile 2. ,Basic knowledge in remote sensing and spatial data analysis\nBackground in physics, biology, earth sciences and/or applied mathematics\nAffinity of working with EO data and natural resources"@en . . . . . . . . . "4"^^ . "3" . "2A" . . "2023-02-05T23:00:00Z"^^ . "This teaching course SHADES-OF-BLUE aims at providing the students with the competence to use Earth Observation (EO) data and products to leverage the management of coastal and inland aquatic resources and policymaking.\n\nThe main objective is to deepen and broaden the knowledge and practical skills of students in using EO products and applications for the integrated management of aquatic resources in deltas. The course includes technical skills and know-how about EO data, products, and applications and, more importantly, global phenomena related to ocean-land-atmosphere interactions. EO products and applications are fundamental components of the planned course and form the backbone of the teaching from the start to the end. Therefore, the course will not only focus on the more generic building stones of remote sensing of aquatic resources but also on the wider scope of applications that addresses the water-atmosphere-land nexus with a deeper analysis and evaluation phase. During this course, the students will acquire competencies needed to address the national (Dutch Research Agenda, routes nr. 1, 4, 9, 13, 23, and 25) and the international research agenda (UN’s Sustainable Development Goals nr. 6, 13, 14, 15)."@en . "SHADES-OF-BLUE: Earth Observation of coastal and inland waters"@en . . "SHADES-OF-BLUE: Earth Observation of coastal and inland waters"@en . "SHADES-OF-BLUE: Earth Observation of coastal and inland waters"@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 . . "201800282" . "NHR_002" . "7"^^ . "196"^^ . "10"^^ . "2023-02-02T23:00:00Z"^^ . "f2f" . "online" . "This course focuses on building the required understanding of natural hazards and the available approaches to map them and further predict their occurrence in space and time. This knowledge will be systematically acquired through short theoretical lectures followed by supervised practicals and tutorials that will expose students to the whole conceptual and modeling pipeline, from cloud-based inventory-making to data acquisition and ultimately to susceptibility and hazard assessment. To promote and make a constructive use of the diversity in the background of the students, each step of the course will also feature a peer-learning process where students with different training will share their knowledge to mutually benefit from each respective understanding of the lessons. At the end of each day, interactive quiz will be provided to monitor the growth of each student and provide support where needed. The learning process will be further supported by a group project assignment that will link together the content of the course. In fact, the automated mapping and the modelling techniques will be implemented and critically assessed in terms of their specific limitations and with respect to the final goal (inventory generation and susceptibility/hazard mapping)."@en . . . . . . ",Compulsory for the “Natural Hazards and Disaster Risk Reduction” (NHR) specialization of the “Geoinformation Science and Earth Observation” (M-GEO) programme. Students from other specializations and programmes should have introductory level experience with GIS and Remote Sensing, and a background in earth sciences, geography, environmental science or civil engineering.\n"@en . . . "3"^^ . "2" . "1B" . "2022-11-13T23:00:00Z"^^ . "The identification and assessment of natural hazards is a crucial component of disaster risk management. This course will focus on the modelling of natural hazards, with an emphasis on hydro-meteorological hazards (floods, landslides and erosion). Starting from the relevant natural phenomena and their causes, the generation of historical inventories of hazardous phenomena will be discussed. From the cloud-based generation of the hazard inventories and their interpretation, the course will expand on the main methods and tools to assess the susceptibility and hazard at different scales. The course will provide the foundation for predictive approaches with a particular focus given to statistical models of multivariate nature. The latter will combine the spatial and temporal dimensions. The use of empirical models will further investigate runout patterns to estimate areas under threat.\n\nThe course runs in parallel to the \"Introduction to Hazard and Risk\" course (Q2.1) where data input for hazard modelling are explained. The two course are closely coupled and part of the necessary knowledge for the \"Data-Driven Hazard modeling\" course will be gained in parallel through lessons and concepts explained in Q2.1."@en . "Data-driven Hazard Modelling"@en . . "Data-driven Hazard Modelling"@en . "Data-driven Hazard Modelling"@en . . "201800279" . "GIMLA_001" . "7"^^ . "196"^^ . "10"^^ . "2023-02-02T23:00:00Z"^^ . "f2f" . "online" . "The educational approach applied in the course is based on the principles of experience-based learning. Students' experiences and tacit knowledge are an important source of learning. Systematic analysis of these experiences will be combined with scientific knowledge and critical reflection.\nThe course is characterized by a blend of lectures, guest lectures, videos, games and individual and group exercises (reading assignments, poster development, presentations and discussions)."@en . . . . . . "Experience in land administration or motivation to work in land administration."@en . . . . . . . . "8"^^ . "2" . "1B" . . . . . . . "2022-11-13T23:00:00Z"^^ . "This course introduces land administration in the context of land policy and sustainable development using the land management paradigm as an initial guiding framework.\n\nThe land management paradigm stresses the relationship between land policy and land administration functions – land tenure, land value, land use and land development – and the wider societal goals.\n\nThe economic, environmental, and social drivers underpinning land policy development are examined, with an emphasis on the need for securing land rights for all.\n\nBased on the core notion of the people-to-land relationship, land tenure, land rights, land law, security of tenure, and systems of land registration and cadastre are addressed.\n\nNew insights in acknowledging and securing land rights, new societal drivers and innovative technical solutions challenges conventional forms of land administration. The course therefore addresses both conventional and innovative ways of securing land rights, promoting a paradigm shift towards responsible land administration.\n\nThe course relates state-of-the-art scientific knowledge to students' experiences, perceptions and country context."@en . "Responsible land administration"@en . . "Responsible land administration"@en . "Responsible land administration"@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 . . . "Programme" . "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