Search result: Catalogue data in Autumn Semester 2023
Geomatics Master  | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
 Master Studies (Programme Regulations 2013) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Major Courses | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Major in Engineering Geodesy and Photogrammetry | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Number | Title | Type | ECTS | Hours | Lecturers | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 103-0287-00L | Image-based Mapping | O | 6 credits | 2G | K. Schindler | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Application of photogrammetry and remote sensing methods for mapping and Earth observation. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Learn how to apply photogrammetry, image analysis and machine learning to mapping tasks; hands-on experience in implementing automatic image analysis methods, and in judging their results. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Preprocessing of satellite images, atmospheric correction; extraction of features (radiometric indices, texture descriptors, etc.) from raw image intensities; semantic image segmentation (e.g., cloud masking); physical parameter estimation (e.g., vegetation height); practical deployment of geometric and semantic computer vision and image analysis methods for mapping; assessment of prediction results | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | basic knowledge of photogrammetry, image processing and machine learning | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competencies |
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| 103-0787-00L | Project Parameter Estimation | W | 3 credits | 2P | J. A. Butt, T. Medic | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Solving engineering problems with modern methods of parameter estimation for network adjustment in a real-world scenario; choosing adequate mathematical models, implementation and assessment of the solutions. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Learn to solve engineering problems with modern methods of parameter estimation in a real-world scenario. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Analysis of given problems, selection of appropriate mathematical modells, implementation and testing using Matlab: Kriging; system calibration of a terrestrial laser scanner. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | The task assignments and selected documentation will be provided as PDF. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Prerequisite: Statistics and Probability Theory, Geoprocessing and Parameterestimation, Geodetic Reference Systems and Networks | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 102-0617-00L | Basics and Principles of Radar Remote Sensing for Environmental Applications | W | 3 credits | 2G | I. Hajnsek | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | The course will provide the basics and principles of Radar Remote Sensing (specifically Synthetic Aperture Radar (SAR)) and its imaging techniques for the use of environmental parameter estimation. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | The course should provide an understanding of SAR techniques and the use of the imaging tools for bio/geophysical parameter estimation. At the end of the course the student has the understanding of 1. SAR basics and principles, 2. SAR polarimetry, 3. SAR interferometry and 4. environmental parameter estimation from multi-parametric SAR data | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | The course is giving an introduction into SAR techniques, the interpretation of SAR imaging responses and the use of SAR for different environmental applications. The outline of the course is the following: 1. Introduction into SAR basics and principles 2. Introduction into electromagnetic wave theory 3. Introduction into scattering theory and decomposition techniques 4. Introduction into SAR interferometry 5. Introduction into polarimetric SAR interferometry 6. Introduction into bio/geophysical parameter estimation (classification/segmentation, soil moisture estimation, earth quake and volcano monitoring, forest height inversion, wood biomass estimation etc.) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Handouts for each topic will be provided | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | First readings for the course: Woodhouse, I. H., Introduction into Microwave Remote Sensing, CRC Press, Taylor & Francis Group, 2006. Lee, J.-S., Pottier, E., Polarimetric Radar Imaging: From Basics to Applications, CRC Press, Taylor & Francis Group, 2009. Complete literature listing will be provided during the course. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 103-0687-00L | Cadastral Systems | W | 2 credits | 2G | J. Lüthy | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Conception, structure and impact of cadastral systems such as property cadastre, PLR-cadastre and related spatial data infrastructures (SDI) as well as their importance for civil society. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Students will get an understanding of the conception, structure and impact of cadastral systems and related concepts such as land administration, land registry, PLR-cadastre, spatial data infrastructures and Digital Twins. The link between cadastral systems, gender equality, economic prosperity and the contribution of property cadastre to achieving the United Nation Sustainable Development Goals (UN SDG) is discussed. The Swiss cadastral system ("Amtliche Vermessung") as well as a number of international systems in developed as well as in developing countries are discussed. The importance of the data from the property cadastre for the National Spatial Data Infrastructure (NSDI) and digital transformation will be investigated using various examples. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Origin and purpose of cadastral systems Importance of documentation of property information as a basis for economic development Basic concepts of cadastral systems (legal basis, conceptual principles, types of property, real estate types) Importance of cadastral systems for societal prosperity due to the impact on the economy, society and the environment. Contribution of the cadastre to the achievement of the UN SDGs on gender equality, poverty and food security. Swiss cadastral system - legal basis - organisation - Technical implementation - Quality and integrity assurance - profession - Embedding cadastral data in the national spatial data infrastructure Contribution of cadastral systems to the Digital Transformation of the society. Benchmarking and evaluations International trends (like blockchain), developments and initiatives to strengthen property rights, 3D cadastral system (above and below ground) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Larsson, G. (1991). Land Registration and Cadastral Systems: Tools for Land Dale, P., & McLaughlin, J. (1999). Land administration. Oxford University Press Yomralioglu, T., & McLaughlin, J. (Eds.). (2017). Cadastre: geo-information innovations in land administration (Vol. 335). Cham, Switzerland: Springer. UN-GGIM (2020), Integrated Geospatial Information Framework, Link | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competencies |
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| 263-5902-00L | Computer Vision | W | 8 credits | 3V + 1U + 3A | M. Pollefeys, S. Tang, F. Yu | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | The goal of this course is to provide students with a good understanding of computer vision and image analysis techniques. The main concepts and techniques will be studied in depth and practical algorithms and approaches will be discussed and explored through the exercises. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | The objectives of this course are: 1. To introduce the fundamental problems of computer vision. 2. To introduce the main concepts and techniques used to solve those. 3. To enable participants to implement solutions for reasonably complex problems. 4. To enable participants to make sense of the computer vision literature. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Camera models and calibration, invariant features, Multiple-view geometry, Model fitting, Stereo Matching, Segmentation, 2D Shape matching, Shape from Silhouettes, Optical flow, Structure from motion, Tracking, Object recognition, Object category recognition | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | It is recommended that students have taken the Visual Computing lecture or a similar course introducing basic image processing concepts before taking this course. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 851-0724-01L | Real Estate Property Law  Particularly suitable for students of D-ARCH, D-BAUG, D-USYS. | W | 3 credits | 3V | S. Stucki, R. Müller-Wyss | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Real estate property law (esp. content, acquisition, restrictions under private and public law, transmission and loss). Legal presentation: land register, surveying, cadastre. Basic questions of contract and tax law. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | The legal principles of real estate property law can be correctly interpreted and applied in daily life. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Real estate property law (esp. content, acquisition, restrictions under private and public law, transmission and loss). Legal presentation: land register, surveying, cadastre. Basic questions of contract and tax law. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Abgegebene Unterlagen: Skript in digitaler Form | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | - Adrian Mühlematter / Stephan Stucki: Grundbuchrecht für die Praxis, Zürich 2016 - Wolfgang Ernst / Samuel Zogg: Sachenrecht in a nutshell, Zürich 2020 - Jörg Schmid / Bettina Hürlimann-Kaup: Sachenrecht, Zürich 2017 - Meinrad Huser, Schweizerisches Vermessungsrecht, unter besonderer Berücksichtigung des Geoinformationsrecht und des Grundbuchrechts, Zürich 2014 - Meinrad Huser, Geo-Informationsrecht, Rechtlicher Rahmen für Geographische Informationssyteme, Zürich 2005 - Meinrad Huser, Darstellung von Grenzen zur Sicherung dinglicher Rechte, in ZBGR 2013, 238 ff. - Meinrad Huser, Baubeschränkungen und Grundbuch, in BR/DC 4/2016, 197 ff. - Meinrad Huser, Publikation von Eigentumsbeschränkungen - neue Regeln, in Baurecht 4/2010, S. 169 - Meinrad Huser, Der Aufteilungsplan im Stockwerkeigentum: Neue Darstellung – grössere Rechtsverbindlichkeit, in ZBGR 2020, S. 203 ff. - Meinrad Huser, Datenschutz bei Geodaten, in: Passadelis/Rosenthal/Thür, Datenschutzrecht, Basel 2015, S. 513 ff. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competencies |
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| 102-0627-00L | Applied Radar Remote Sensing | W | 3 credits | 2G | O. Frey | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This course provides an introduction to processing and interpreting radar and synthetic aperture radar (SAR) remote sensing data. The primary topics of the course are interferometric techniques and related applications such as topography mapping and mapping of surface displacements, with a strong emphasis on solving practical problems using MATLAB. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Understand the concepts and techniques required to process and to adequately interpret interferometric radar/SAR data for topographic mapping and surface displacement applications. At the end of the course the student is able to read, display, process, and interpret interferometric radar/SAR using MATLAB. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | The rationale behind the structure of the course follows the idea that radar imaging and radar/SAR interferometry are closely related and that a basic understanding of the radar imaging concept is helpful to understand and interpret interferometric radar data for various applications. The course starts with the real-aperture radar case and a first introduction to the concept of radar interferometry with applications to topographic mapping and mapping of surface displacements. Based on that, the 2-D imaging concept used in synthetic aperture radar imaging is treated. Then, we expand further on radar and SAR interferometric (InSAR) concepts and processing steps for single interferograms and stacks of interferograms also using persistent scatterer interferometry (PSI) to measure deformation based on time series of interferometric SAR data. Finally, the 3-D radar imaging case (SAR tomography) is put into context with PSI/InSAR time series as an extension of the more classical interferometric approaches thereby closing the circle around the strongly related concepts of SAR imaging and interferometry. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Lecture notes/handouts for each topic will be provided online. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Additional reading material: Hanssen, R. F., Radar interferometry: data interpretation and error analysis, Kluwer Academic Publishers, 2001. ISBN: 978-0-306-47633-4 https://doi.org/10.1007/0-306-47633-9 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | It is highly recommended that the student has previously taken the following courses: 102-0617-00L: Basics and Principles of Radar Remote Sensing and 102-0617-01L: Methodologies for Image Processing of Remote Sensing Data | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 363-0790-00L | Technology Entrepreneurship | W | 2 credits | 2V | F. Hacklin | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Technology ventures are significantly changing the global economic picture. Technological skills increasingly need to be complemented by entrepreneurial understanding. This course offers the fundamentals in theory and practice of entrepreneurship in new technology ventures. Main topics covered are success factors in the creation of new firms, including founding, financing and growing a venture. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | This course provides theory-grounded knowledge and practice-driven skills for founding, financing, and growing new technology ventures. A critical understanding of dos and don'ts is provided through highlighting and discussing real life examples and cases. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Weekly sessions - recorded. 10+ sessions carried out by guest lecturers: experts in the broad field of technology entrepreneurship (e.g., serial entrepreneurs, venture capitalists, (E)MBA professors, company builders, patent experts, scale-up executives, …). Final session: multiple choice semester assignment (100% of grade). Typical lecture format (2h): 15': Introduction 60': Guest testimonial 15': Discussion related to topic (in groups) 10': Plenary discussion 20': Q&A with (guest) lecturer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Lecture slides and case material | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competencies |
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| 103-0249-00L | Geospatial Reference Systems | W | 4 credits | 4G | A. Wieser, M. Varga | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This course is an advanced introduction to spatial and temporal reference systems for acquisition, analysis and communication of geospatial data. The course covers definitions, conventions and comprehensive real world examples of coordinate reference systems, time reference systems, their respective practical realization, and operations for changing data between them. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | After this course the students should be able to describe the most important established national and international spatial and temporal reference systems; describe the techniques, processes, and institutions needed to establish and maintain reference frames; select appropriate reference systems and frames for specific geospatial modeling/analysis tasks; carry out coordinate transformations, conversions, and time operations on geospatial data, taking into account and quantifying the uncertainties; combine geospatial data originally referring to different reference frames into a single reference frame. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | The course requires familiarity with linear algebra and analysis at the level of a BSc program in engineering or natural sciences. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 103-0820-00L | Introduction to Scientific Computation | W | 3 credits | 2G | M. Usvyatsov | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Introduction to tools, techniques, and methods for data processing and analysis. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Get ready to work with data of different origin. Learn Python and tools to the level which allows attacking data related problems. Basic introduction to numerical algorithms for efficient problem solving | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Python for scientific programming, fast numerical computations and data visualisation. Libraries for data processing. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Basic probability theory and statistics, linear algebra, basic programming skills | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Major in Space Geodesy and Navigation | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Number | Title | Type | ECTS | Hours | Lecturers | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 103-0187-01L | Space Geodesy | O | 6 credits | 4G | B. Soja | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | GNSS, VLBI, SLR/LLR and satellite altimetry: Principles, instrumentation and observation equation. Modelling and estimation of station coordinates and station motion. Ionospheric and tropospheric refraction and estimation of atmospheric parameters. Equation of motion of the unperturbed and perturbed satellite orbit. Perturbation theory and orbit determination. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | After this course, the students should be able to • Describe the major observation techniques in space geodesy • Describe the necessary modeling and analysis approaches to derive geodetic products of highest quality • Select the appropriate space geodetic data for scientific investigations • Analyze the space geodetic data for scientific purposes • Interpret the scientific results | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Overview of GNSS, Very Long Baseline Interferometry (VLBI), Satellite and Lunar Laser Ranging (SLR/LLR), Satellite Radar Altimetry with the basic principles, the instruments and observation equations. Modelling of the station motions and the estimation of station coordinates. Basics of wave propagation in the atmosphere. Signal propagation in the ionosphere and troposphere for the different observation techniques and the determination of atmospheric parameters. Equation of motion of the unperturbed and perturbed satellite orbit. Osculating and mean orbital elements. General and special perturbation theory and the determination of satellite orbits. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Script M. Rothacher "Space Geodesy" | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competencies |
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| 103-0787-00L | Project Parameter Estimation | W | 3 credits | 2P | J. A. Butt, T. Medic | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Solving engineering problems with modern methods of parameter estimation for network adjustment in a real-world scenario; choosing adequate mathematical models, implementation and assessment of the solutions. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Learn to solve engineering problems with modern methods of parameter estimation in a real-world scenario. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Analysis of given problems, selection of appropriate mathematical modells, implementation and testing using Matlab: Kriging; system calibration of a terrestrial laser scanner. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | The task assignments and selected documentation will be provided as PDF. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Prerequisite: Statistics and Probability Theory, Geoprocessing and Parameterestimation, Geodetic Reference Systems and Networks | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 102-0617-00L | Basics and Principles of Radar Remote Sensing for Environmental Applications | W | 3 credits | 2G | I. Hajnsek | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | The course will provide the basics and principles of Radar Remote Sensing (specifically Synthetic Aperture Radar (SAR)) and its imaging techniques for the use of environmental parameter estimation. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | The course should provide an understanding of SAR techniques and the use of the imaging tools for bio/geophysical parameter estimation. At the end of the course the student has the understanding of 1. SAR basics and principles, 2. SAR polarimetry, 3. SAR interferometry and 4. environmental parameter estimation from multi-parametric SAR data | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | The course is giving an introduction into SAR techniques, the interpretation of SAR imaging responses and the use of SAR for different environmental applications. The outline of the course is the following: 1. Introduction into SAR basics and principles 2. Introduction into electromagnetic wave theory 3. Introduction into scattering theory and decomposition techniques 4. Introduction into SAR interferometry 5. Introduction into polarimetric SAR interferometry 6. Introduction into bio/geophysical parameter estimation (classification/segmentation, soil moisture estimation, earth quake and volcano monitoring, forest height inversion, wood biomass estimation etc.) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Handouts for each topic will be provided | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | First readings for the course: Woodhouse, I. H., Introduction into Microwave Remote Sensing, CRC Press, Taylor & Francis Group, 2006. Lee, J.-S., Pottier, E., Polarimetric Radar Imaging: From Basics to Applications, CRC Press, Taylor & Francis Group, 2009. Complete literature listing will be provided during the course. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 103-0687-00L | Cadastral Systems | W | 2 credits | 2G | J. Lüthy | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Conception, structure and impact of cadastral systems such as property cadastre, PLR-cadastre and related spatial data infrastructures (SDI) as well as their importance for civil society. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Students will get an understanding of the conception, structure and impact of cadastral systems and related concepts such as land administration, land registry, PLR-cadastre, spatial data infrastructures and Digital Twins. The link between cadastral systems, gender equality, economic prosperity and the contribution of property cadastre to achieving the United Nation Sustainable Development Goals (UN SDG) is discussed. The Swiss cadastral system ("Amtliche Vermessung") as well as a number of international systems in developed as well as in developing countries are discussed. The importance of the data from the property cadastre for the National Spatial Data Infrastructure (NSDI) and digital transformation will be investigated using various examples. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Origin and purpose of cadastral systems Importance of documentation of property information as a basis for economic development Basic concepts of cadastral systems (legal basis, conceptual principles, types of property, real estate types) Importance of cadastral systems for societal prosperity due to the impact on the economy, society and the environment. Contribution of the cadastre to the achievement of the UN SDGs on gender equality, poverty and food security. Swiss cadastral system - legal basis - organisation - Technical implementation - Quality and integrity assurance - profession - Embedding cadastral data in the national spatial data infrastructure Contribution of cadastral systems to the Digital Transformation of the society. Benchmarking and evaluations International trends (like blockchain), developments and initiatives to strengthen property rights, 3D cadastral system (above and below ground) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Larsson, G. (1991). Land Registration and Cadastral Systems: Tools for Land Dale, P., & McLaughlin, J. (1999). Land administration. Oxford University Press Yomralioglu, T., & McLaughlin, J. (Eds.). (2017). Cadastre: geo-information innovations in land administration (Vol. 335). Cham, Switzerland: Springer. UN-GGIM (2020), Integrated Geospatial Information Framework, Link | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competencies |
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| 851-0724-01L | Real Estate Property Law Particularly suitable for students of D-ARCH, D-BAUG, D-USYS. | W | 3 credits | 3V | S. Stucki, R. Müller-Wyss | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Real estate property law (esp. content, acquisition, restrictions under private and public law, transmission and loss). Legal presentation: land register, surveying, cadastre. Basic questions of contract and tax law. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | The legal principles of real estate property law can be correctly interpreted and applied in daily life. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Real estate property law (esp. content, acquisition, restrictions under private and public law, transmission and loss). Legal presentation: land register, surveying, cadastre. Basic questions of contract and tax law. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Abgegebene Unterlagen: Skript in digitaler Form | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | - Adrian Mühlematter / Stephan Stucki: Grundbuchrecht für die Praxis, Zürich 2016 - Wolfgang Ernst / Samuel Zogg: Sachenrecht in a nutshell, Zürich 2020 - Jörg Schmid / Bettina Hürlimann-Kaup: Sachenrecht, Zürich 2017 - Meinrad Huser, Schweizerisches Vermessungsrecht, unter besonderer Berücksichtigung des Geoinformationsrecht und des Grundbuchrechts, Zürich 2014 - Meinrad Huser, Geo-Informationsrecht, Rechtlicher Rahmen für Geographische Informationssyteme, Zürich 2005 - Meinrad Huser, Darstellung von Grenzen zur Sicherung dinglicher Rechte, in ZBGR 2013, 238 ff. - Meinrad Huser, Baubeschränkungen und Grundbuch, in BR/DC 4/2016, 197 ff. - Meinrad Huser, Publikation von Eigentumsbeschränkungen - neue Regeln, in Baurecht 4/2010, S. 169 - Meinrad Huser, Der Aufteilungsplan im Stockwerkeigentum: Neue Darstellung – grössere Rechtsverbindlichkeit, in ZBGR 2020, S. 203 ff. - Meinrad Huser, Datenschutz bei Geodaten, in: Passadelis/Rosenthal/Thür, Datenschutzrecht, Basel 2015, S. 513 ff. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competencies |
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| 103-0249-00L | Geospatial Reference Systems | W | 4 credits | 4G | A. Wieser, M. Varga | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This course is an advanced introduction to spatial and temporal reference systems for acquisition, analysis and communication of geospatial data. The course covers definitions, conventions and comprehensive real world examples of coordinate reference systems, time reference systems, their respective practical realization, and operations for changing data between them. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | After this course the students should be able to describe the most important established national and international spatial and temporal reference systems; describe the techniques, processes, and institutions needed to establish and maintain reference frames; select appropriate reference systems and frames for specific geospatial modeling/analysis tasks; carry out coordinate transformations, conversions, and time operations on geospatial data, taking into account and quantifying the uncertainties; combine geospatial data originally referring to different reference frames into a single reference frame. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | The course requires familiarity with linear algebra and analysis at the level of a BSc program in engineering or natural sciences. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competencies |
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| 363-0790-00L | Technology Entrepreneurship | W | 2 credits | 2V | F. Hacklin | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Technology ventures are significantly changing the global economic picture. Technological skills increasingly need to be complemented by entrepreneurial understanding. This course offers the fundamentals in theory and practice of entrepreneurship in new technology ventures. Main topics covered are success factors in the creation of new firms, including founding, financing and growing a venture. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | This course provides theory-grounded knowledge and practice-driven skills for founding, financing, and growing new technology ventures. A critical understanding of dos and don'ts is provided through highlighting and discussing real life examples and cases. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Weekly sessions - recorded. 10+ sessions carried out by guest lecturers: experts in the broad field of technology entrepreneurship (e.g., serial entrepreneurs, venture capitalists, (E)MBA professors, company builders, patent experts, scale-up executives, …). Final session: multiple choice semester assignment (100% of grade). Typical lecture format (2h): 15': Introduction 60': Guest testimonial 15': Discussion related to topic (in groups) 10': Plenary discussion 20': Q&A with (guest) lecturer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Lecture slides and case material | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competencies |
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| Major in GIS and Cartography | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Number | Title | Type | ECTS | Hours | Lecturers | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 103-0227-00L | Application Development in Cartography | O | 6 credits | 4G | L. Hurni | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This course introduces concepts and techniques in 3D cartography and web application development. Practical experience will be gained in a map project. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Students acquire general knowledge about the foundations and best practices in 3D cartography and modern web application development. They learn to plan, design and implement an interactive and animated 3D web map. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | - 3D cartography - Web mapping - Data processing - Animations and interactions - Map and UI design - Web application development - Programming (JavaScript). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Handouts of the lectures and exercise documents are available on Moodle. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Cartography II or Introduction to Web Cartography Part 1+2 (MOOC) or similar knowledge in mapping with JavaScript. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competencies |
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| 103-0747-00L | Cartography Lab | W | 6 credits | 13A | L. Hurni | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Independent semester work in cartography | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Independent semester work in cartography | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Choice of theme upon individual agreement | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Cartography III Multimedia Cartography Further information at http://www.karto.ethz.ch/studium/lehrangebot.html | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 103-0687-00L | Cadastral Systems | W | 2 credits | 2G | J. Lüthy | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Conception, structure and impact of cadastral systems such as property cadastre, PLR-cadastre and related spatial data infrastructures (SDI) as well as their importance for civil society. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Students will get an understanding of the conception, structure and impact of cadastral systems and related concepts such as land administration, land registry, PLR-cadastre, spatial data infrastructures and Digital Twins. The link between cadastral systems, gender equality, economic prosperity and the contribution of property cadastre to achieving the United Nation Sustainable Development Goals (UN SDG) is discussed. The Swiss cadastral system ("Amtliche Vermessung") as well as a number of international systems in developed as well as in developing countries are discussed. The importance of the data from the property cadastre for the National Spatial Data Infrastructure (NSDI) and digital transformation will be investigated using various examples. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Origin and purpose of cadastral systems Importance of documentation of property information as a basis for economic development Basic concepts of cadastral systems (legal basis, conceptual principles, types of property, real estate types) Importance of cadastral systems for societal prosperity due to the impact on the economy, society and the environment. Contribution of the cadastre to the achievement of the UN SDGs on gender equality, poverty and food security. Swiss cadastral system - legal basis - organisation - Technical implementation - Quality and integrity assurance - profession - Embedding cadastral data in the national spatial data infrastructure Contribution of cadastral systems to the Digital Transformation of the society. Benchmarking and evaluations International trends (like blockchain), developments and initiatives to strengthen property rights, 3D cadastral system (above and below ground) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Larsson, G. (1991). Land Registration and Cadastral Systems: Tools for Land Dale, P., & McLaughlin, J. (1999). Land administration. Oxford University Press Yomralioglu, T., & McLaughlin, J. (Eds.). (2017). Cadastre: geo-information innovations in land administration (Vol. 335). Cham, Switzerland: Springer. UN-GGIM (2020), Integrated Geospatial Information Framework, Link | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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