. . "EOS_0001" . . "GeoHealth Course"@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 . . "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 . . "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 . . "5.0" . "140.0" . "10.0" . . . . . . . . "F2F" . . . . . . . . . . . . . . . . . . "Statistics, calculus, linear algebra, analytics geometry, programming (Python)"@en . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . "4.0" . "3.0" . "CONCEPT (not yet confirmed by all GEO-AI staff):\nThis course is designed to guide you through the intersection of machine learning and geospatial sciences, providing you with the expertise to address pressing societal and environmental challenges. You will be introduced to the foundations of supervised and unsupervised learning algorithms, exploring their applications in the geospatial domain. You will learn popular learning algorithms to address various inference tasks, such as clustering, regression and classification.\nFrom satellite imagery to GIS datasets you'll master the tools and methodologies required to preprocess, analyze, integrate and visualize them. You will gain the skills needed to extract meaningful patterns and insights from these geospatial datasets.\nFeature extraction and engineering are critical steps in building effective machine learning models. You will explore techniques to transform raw geospatial data into relevant features enabling your models to learn and predict more effectively.\nClustering techniques, for exploratory spatial data analysis, will be introduced to help you to discover hidden structures and trends within geospatial datasets.\nClassification and regression methods like decision trees, random forests, support vector machines and neural networks are pivotal machine learning tasks that you'll apply to a wide array of geospatial problems. Whether it's land use classification, predicting environmental changes, or estimating spatial variables like temperature or population density, you'll develop models that provide precise and actionable insights.\nThroughout the course real-world case studies will demonstrate the transformative impact of machine learning on geospatial sciences. You'll work on projects that tackle contemporary issues such as urban planning, environmental monitoring, and disaster management.\nBy the end of this course, you will be adept at applying machine learning techniques to geospatial sciences."@en . "Machine Learning for Geospatial Sciences"@en . . "Machine Learning for Geospatial Sciences"@en . "Machine Learning for Geospatial Sciences"@en . . "5.0" . "140.0" . "10.0" . . . . . . . . "Open for students in the Master of Science degree programme in Geo-Information Science and Earth Observation. As first Foundational course, the pre-requisites align to those of acceptance to the M-GEO program, consequently there are no other specifcs needed. For other cases, the candidates will be assessed on an individual basis."@en . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . "1.0" . "This 5 ECTS course is designed for students aiming to acquire foundational knowledge and skills in these critical geospatial technologies. The course provides a comprehensive introduction to the principles, techniques, and applications of remote sensing (RS) and Geographic Information Systems (GIS), emphasizing their integration to solve real-world problems.\nCourse Structure and Content\n1. Introduction to RS and GIS: The course begins with an overview of RS and GIS, exploring their, core concepts, and significance in various fields such as environmental monitoring, urban planning, agriculture, and disaster management.\n2. RS Fundamentals: Students will learn about different types of RS systems, focusing on optical passive sensors included in satellite and airborne platforms, as well as the electromagnetic spectrum's role in data acquisition. Participants are exposed to key preprocessing steps such as radiometric and geometric corrections ensuring data quality.\n3. GIS Basics and Data Handling: Interlinked with RS, comes the introduction of GIS principles, spatial data models, and database management. Students will engage in hands-on exercises to collect, input, and manage spatial data, learning essential techniques like digitizing, GPS, and attribute data collection.\n4. Image Interpretation and Classification: Students will gain skills in interpreting RS imagery, performing both visual analysis and supervised image classification, and assessing classification accuracy.\n5. Spatial Analysis and Integration: The course integrates RS data with GIS to enhance spatial analysis capabilities. Students will practice GIS analytical techniques, such as buffer and overlay analysis, combining data acquire from geoportals and processing flows.\n6. Practical Applications and Project Work: Along the course there is a “cumulative” project-based learning of choice, where students are exposed to RS and GIS techniques of at least one learning path, while practicing the instructed methodology. Collaborative projects and specific case studies will reinforce theoretical knowledge and practical skills, preparing students for professional applications."@en . "GIS & EO foundation"@en . . "GIS & EO foundation"@en . "GIS & EO foundation"@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 . . . . . . . . . . . . "Foundations of GIS and Earth Observation (Part 1) (M-T-W)"@en . "GIS & EO foundation: LU1"@en . . . . "ITC Bok"@en . "https://ltb.itc.utwente.nl/page/792/concept/152728" . . "GIS"@