. . "5.0" . "140.0" . "10.0" . . . . . . "blended" . . . . . . . . . . . . . . . . "Basic statistical analyses, Spatial statistics"@en . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . "3.0" . "3.0" . "Understanding urban dynamics and urban growth is crucial for strategic long-term planning of infrastructure, economic development, environmental sustainability, social equity and overall urban resilience. At its core, the interaction between land use and transportation plays a pivotal role in shaping urban dynamics, and such interactions and dynamics can be most efficiently understood by modelling.\nModelling urban dynamics and growth involves the use of various theoretical frameworks that captures transportation infrastructure affects land use patterns and vice versa. In this course, the students will not only be introduced with theories about land use and transportation interactions, but also knowledges and techniques of implementing models that encodes the interactions quantitatively. Several modelling frameworks (to be specified) will be introduced to simulate travel decisions and behaviours, mobility and accessibility, land use land cover changes. On top of developing the modelling capacity, the students will also be trained to assess and interpret the modelled scenarios, so that to link the modelling into the practical context of urban planning and policy making."@en . "Urban Futures Modelling"@en . . "Urban Futures Modelling"@en . "Urban Futures Modelling"@en . . "5.0" . "140.0" . "10.0" . . . . . . "F2F" . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . "6.0" . "3.0" . "Both hazard types and frequency, as well as built-up areas and cities are dynamically changing, resulting from climate and global changes. In April 2024, displacing 600.000 people in Brazil due to floods, having hottest day records already in Europe and in Asia are clear examples to the shifting hazard patterns. In such dynamic environments, the interdependency among the risk components amplifies the impact of disasters. In such an environment, disaster risk is constantly changing, and there is a definite limit to our capacity to foresee the failures resulting from unexpected interactions between interdependent components. Indeed, the intensity and extent of the challenges make clear that achieving resilient cities is everybody’s business. Scientists, stakeholders and citizens are faced with the challenge to adapt their disaster risk reduction plans but lack the understanding and tools to account for the cross-sectoral impacts and dynamic nature of the risks involved. In this course, we follow the socio-technical approach in complex city systems and investigate the ways to contribute to cities’ resilience. The main problem in disaster risk management is providing static measures to a dynamically changing system. In this course you will learn looking at the nature of risk as a 'dynamic' concept rather than a static one. You will focus on multi-hazard risk assessment and dynamic risk reduction measures on various sectors."@en . "Planning for Resilient Cities"@en . . "Planning for Resilient Cities"@en . "Planning for Resilient Cities"@en . . "2.5" . "70.0" . "5.0" . . . . . . . "blended" . . . . . . . "operational GIS skills"@en . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . "1.0" . "3.0" . "Geospatial database engineering is the professional suite of activities that is needed to\ndevelop, realize and maintain a usually large database system that holds geospatial data\nsources that service usually a sizeable user community.\nWherever large geospatial datasets, especially comprising vector data, are shared between\nprofessional users the technology to apply is a geospatially enabled database management\nsystem (sdbms). Its purpose is to serve as a reliable data store for its community of users,\nand provide a resource of agreed upon and documented quality.\nThis course teaches how to initiate such a database system, bring in external data, curate\nthe data, and put in place guards against data incorrectness, invalidity, incompleteness\nand inconsistency.\nIt next addresses how conceptual descriptions of functions that must become part of the\nsystem's application programming interface can be implemented using the programming\nfacilities that the sdbms offers. We look into the coding paradigm of set-based\nprogramming, and make use of mathematical logic and comprehension schemes, which are\ntypical of SQL.\nSpecific attention will be paid in this course to computing with geospatial vector data.\nThis also requires understanding of the OGC Simple Feature model, ISO 19125. Various\ntechniques will be introduced to test and validate, correct and improve vector data, and\nwe discuss a number of typical problem situations and template solutions to them.\nThe course will bring to the student understanding of how to approach these challenges and\nskills to resolve them."@en . "Geospatial Database Engineering"@en . . "Geospatial Database Engineering"@en . "Geospatial Database Engineering"@en . . "2.5" . "70.0" . "5.0" . . . . . "blended" . . . . . . . . . . . . . . . "None"@en . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . "2.0" . "2.0" . "The management of space is one of the big challenges that human societies have to deal with. Competing claims over the use of finite resources have pushed human societies to develop institutions, technologies and paradigms that help manage these competing usages. Challenges like increasing urbanization, the depletion of land and other natural resources, and climate change make this management of space ever more urgent.\nThe governance of land and urban development is essential when considering development approaches to support sustainable futures. As a concept, governance encapsules (1) Multi level co-ordination and multi-faceted problems; (2) Multi actor networks, and (3) Multi-instrumental steering mechanisms. This implies that an understanding of problems, actors and steering mechanisms involved in the governance of land and urban development is necessarily focused on the context in which a certain problem is placed and how it can be addressed by the governance settings available.\nIn this course we focus on key concepts of land and urban governance. The aim is for the student to gain a background in (challenges of) governance of land and urban development, that will influence how individuals, organizations and institutions work towards land and urban futures. An additional challenge in the course is inviting the students to reflect, discuss and imagine different land and urban futures. "@en . "Land and Urban Futures"@en . . "Land and Urban Futures"@en . "Land and Urban Futures"@en . . "5.0" . "140.0" . "10.0" . . . . . . . . . . . . . . . . . . . . . . . . . "1.0" . "Geospatial problem solving for addressing societal challenges employs a wide variety of theories, methods, and tools, each applicable to a specific type or aspect of the problem solving process. All approaches, however, involve the acquisition, processing, and dissemination of data in one form or another. The Geoinformation and Earth Observation specialist must, therefore, be equipped with the necessary skills to find, use, preserve, and disseminate geospatial data. This course introduces conceptual models, analysis tools, and infrastructure for representing and analysing geographic phenomena in computer systems. The course covers both spatial and temporal aspects of the observed phenomena. Fundamental concepts of spatial representation including geometric primitives, topology, multidimensionality, spatial autocorrelation, graphs and networks, will be introduced in the context spatial data management. By the end of the course students should be able to interact with local or remote data resources using a variety of technologies including SQL and common web service APIs (e.g OGC WMS, WFS, WCS, REST). The student should therefore become familiar with common of data formats used in GIS and EO. Students will also learn to apply elementary data transformations (analysis) to obtain data in the appropriate structure for dissemination and presentation in both static and dynamic spatiotemporal visualizations. Applications in urban and land futures planning will be used in examples and exercises throughout this course. Learning units are organized so that concepts and methods from various knowledge categories are combined into a wholistic skill set that a student can use to solve a specific geoapstial problem."@en . "Spatial Methods & Data Management"@en . . "Spatial Methods & Data Management"@en . "Spatial Methods & Data Management"@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 . . "2.5" . "70.0" . "5.0" . . . . . . "blended" . . . . . . . . . . . . . . . . "Basic land and urban futures concepts (course ULF 1), Spatial data handling (courses FC 1 and FC2), basic programming concepts (course FC3)"@en . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . "4.0" . "3.0" . "With expanding urban settlements, increasing demand for resources, and exacerbating environmental challenges, the complexity of future urban and regional systems is expected to increase. Information systems for planning and managing land use policy implementation will therefore become indispensable tools in the urban planning and land administration toolboxes. In this course students learn to think in systems terms and use systems analysis and design methods to not only describe the functionality of an information system but, perhaps more importantly, to describe the data, information structures, processes, states, and state evolutions of interest within the urban and/or regional system under consideration. The course introduces the software process as a project implementation methodology. Analysis and design approaches are introduced in the context of this overarching structure. First students will learn to analyse requirements documents to conceptualize a system's purpose and boundary. Additional information from the domain and requirements documents will be used to develop a conceptual model of the domain and identify user actions and processes within the domain. UML class diagrams will be used to structure concepts. UML use case diagrams and activity diagrams will be used to analyse user intentions, actions, and the information system's responses. Finally UML state machines will allow student to describe the set of states that can be occupied by all or part of the system being modelled. The modeling constructs introduced are applicable to both the information system and the real world domain. Examples will help clarify how to apply the tool in both contexts. "@en . "Designing Urban & Land Information Systems"@en . . "Designing Urban & Land Information Systems"@en . "Designing Urban & Land Information Systems"@en . . "5.0" . "140.0" . "10.0" . . . . . . . . . . . . . . . . . . . . . "previous ULF courses or similar knowledge and experiences"@en . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . "5.0" . "4.0" . "Addressing current and future societal challenges or urban areas around the world requires integrating thinking and insights where space, society and technology intersect. This new geo-socio-technical approach to of solving urban and land problem demands a new way of working and indeed re-conceiving of the tools and methods that inform our solutions to these challenges. Advancements in planning support and decision making technologies have enabled evidence-based scenario planning but failed in engaging a broad range of non-experts in future-oriented planning practice that accounts for deep uncertainty and complexity of societal challenges.\nIn this studio course, student groups engage in challenge-based learning of a real-world spatial problem setting. Geospatial and participatory technologies for systematic analysis of locational phenomena and spatial characteristics will be applied in combination with methods for eliciting local experiential knowledge of residents and other societal actors to disentangle wicked problem settings and underlying root causes and to develop visions of a sustainable urban and land future. Goal of studio-based learning approach is to provide a policy making authority with integrated insights and inspiration for new methods for producing sage, and to co-design together with them future-oriented strategies and interventions in an inclusive manner.\nIn this course students are exposed to various lab facilities of ITC and learn how to make use of them for data collection, stakeholder interaction and collaborative planning and decision making. "@en . "Urban and Land Futures Studio"@en . . "Urban and Land Futures Studio"@en . "Urban and Land Futures Studio"@en . . "5.0" . "140.0" . "10.0" . . . . . "blended" . . . . . . . . . . . . . . . "Foundational courses (basic GIS knowledge and basic statistics)"@en . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . "3.0" . "2.0" . "“Planning for Liveable Cities” critically addresses inequalities within urban areas by analysing concerns about social equity, quality of life, health and well-being and urban competitiveness in light of urban development patterns and strategies. Tensions and trends in planning for these visions and ideals is discussed. Different tools are introduced and applied to analyse these patterns. Students will engage with various scales of analysis, applying geospatial solutions to develop people-centric and digitally-informed strategies that support the transition towards more equitable, healthy, and just urban futures. By capturing and understanding diverse forms of knowledge related to intra-urban variations in quality of life, the curriculum aims to create a deeper understanding of these patterns. This is crucial for targeting deprived areas and formulating effective area-based and people-based policies. "@en . "Planning for Liveable Cities"@en . . "Planning for Liveable Cities"@en . "Planning for Liveable Cities"@en . . "2.5" . "70.0" . "5.0" . . . . . . "blended" . . . . . . . . . . . . . . . . "Foundation courses M-Geo"@en . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . "4.0" . "2.0" . "The concept of (public) participation in geospatial research has a long tradition. However, the adoption of Web 2.0 technologies facilitates the generation and sharing of and collaboration on digital content with a geospatial component, and has therefore expanded possibilities and practice. This course gives an overview of its history and new developments, on examples of successful and unsuccessful projects to identify criteria for sustainable crowdsourcing or volunteering, including issues of privacy and ethical research. It is particularly relevant for eliciting and arguing the needs, interests, and positions of any stakeholder that incorporates or directly works with the public. A main focus lies on the technologies that enable new forms of participatory sensing, and techniques to assess and improve the quality of such data. "@en . "Volunteered Geographic Information and Geo Citizen Science"@en . . "Volunteered Geographic Information and Geo Citizen Science"@en . "Volunteered Geographic Information and Geo Citizen Science"@en . . "5.0" . "140.0" . "10.0" . . . . . . . . . . . . . . . . . . . . . . . . . "1.0" . "Visualisation and Communication"@en . . "Visualisation and Communication"@en . "Visualisation and Communication"@en . . "5.0" . "140.0" . "10.0" . . . . . . . . . . . . . . . . . . . . . . . . . "1.0" . "From Statistics to Programming and Machine Learning"@en . . "From Statistics to Programming and Machine Learning"@en . "From Statistics to Programming and Machine Learning"@en . . . . . . . . . . . . . . . . . . . . . . "Urban Land & Futures"@en . . "Making Cities and Land