Search result: Catalogue data in Autumn Semester 2021

Spatial Development and Infrastructure Systems Master Information
Master Studies (Programme Regulations 2021)
Compulsory Courses
NumberTitleTypeECTSHoursLecturers
101-0467-01LTransport Systems
Only for master students, otherwise a special permisson by the lecturers is required.
O6 credits4GK. W. Axhausen, A. Kouvelas, Y. Zhu
AbstractHistory, impact and principles of the design and operation of
transport systems
ObjectiveIntroduction of the basic principles of the design and operation of
transport systems (road, rail, air) and of the essential pathways of their
impacts (investment, generalised costs, accessibilities, external effects), referring to relatively constant, and factors with substantial future uncertainty, in the past and expected evolution of transport systems.
ContentTransport systems and land use; network design; fundamental model of mobility behaviour; costs and benefits of mobility; transport history

Classification of public transport systems; Characteristics of rail systems, bus systems, cable cars and funiculars, unconventional systems; introduction to logistics; fundamentals of rail freight transports; freight transport systems; intermodal transportation

Network layout and its impact on road traffic. Traffic control systems for urban and inter-urban areas. Fundamentals of road safety and infrastructure maintenance.
Lecture notesLecturer notes and slides as well as hints to further literature will be given during the course.
Prerequisites / NoticeObligatory lecture for students of the first semester of MSc Spatial development and Infrastructure Systems.
103-0317-00LIntroduction to Spatial Development and Transformation
Only for master students, otherwise a special permisson by the lecturer is required.
O3 credits2GM. Nollert, D. Kaufmann
AbstractThe course deals with important theoretical, material and methodical foundations for action and decision-making of spatial relevance. This course discusses central tasks and possible solutions for current and future challenges of spatial development in Switzerland and Europe.
ObjectiveSpatial development deals with the development, formation and arrangement of our environment. In order to be able to mediate between the different demands, interests and projects of multiple actors, a forward-looking, action-oriented and robust planning is necessary. It is committed - in the sense of a sustainable spatial development - to the economical handling of resources, in particular of the non-replicable resource soil.
The lecture introduces necessary basic knowledge and is based on the following main topics:
– Inward development and challenges of spatial transformation
– Planning approaches and The (political) steering of spatial development
– Interplay of formal and informal processes and processes across different scales of spatial development
– Methods of action-oriented planning in situations of insecurity
– Integrated space and infrastructure development
– Different types of participation in spatial development
By taking up the lecture, the students are able to recognize cross-scale, complex tasks of spatial development and transformation and to use their theoretical, methodical and professional knowledge to clarify them.
Content- Planning approaches and political organization in Switzerland
- Tasks of spatial relevance
- Key figures and ratios
- Drivers of spatial development
- Steering spatial development I: Policy
- Steering spatial development II : Formal and informal instruments
- Organizing spatial development I: Governance
- Organizing spatial development II: 
Processes and organization
- Methods in spatial planning I
- Methods in spatial planning II
- Planning in complex situations
- Participation in spatial development
- Present and future core tasks of spatial development
Lecture notesFurther information and the documents for the lecture can be found on the homepage of IRL/STL
CompetenciesCompetencies
Subject-specific CompetenciesConcepts and Theoriesassessed
Techniques and Technologiesassessed
Method-specific CompetenciesAnalytical Competenciesassessed
Decision-makingassessed
Problem-solvingassessed
Project Managementfostered
Social CompetenciesCooperation and Teamworkfostered
Personal CompetenciesCreative Thinkingassessed
Critical Thinkingassessed
Self-direction and Self-management fostered
103-0347-00LLandscape Planning and Environmental Systems Restricted registration - show details O3 credits2VA. Grêt-Regamey
AbstractIn the course, students learn about methods for the identification and measurement of landscape characteristics, as well as measures and policies for landscape planning. Landscape planning is put into the context of environmental systems (soil, water, air, climate, flora and fauna) and discussed with regard to socio-political questions of the future.
ObjectiveThe aims of this course are:
1) To illustrate the concept of landscape planning, the economic relevance of landscape and nature in the context of the environmental systems (soil, water, air, climate, flora and fauna).
2) To show landscape planning as an integral information system for the coordination of different instruments by illustrating the aims, methods, instruments and their functions in landscape planning.
3) To show the importance of ecosystem services.
4) To learn basics about nature and landscape: Analysis and assessment of the complex interactions between landscape elements, effects of current and future land use (ecosystem goods and services, landscape functions).
5) To identify and measure the characteristics of landscape.
6) Learn how to use spatial data in landscape planning.
ContentIn this course, the following topics are discussed:
- Definition of the concept of landscape
- Relevance of landscape planning
- Landscape metrics
- Landscape change
- Methods, instruments and aims of landscape planning (policy)
- Socio-political questions of the future
- Environmental systems, ecological connectivity
- Ecosystem services
- Urban landscape services
- Practice of landscape planning
- Use of GIS in landscape planning
Lecture notesNo script. The documentation, consisting of presentation slides are partly handed out and are provided for download on Moodle.
Prerequisites / NoticeThe contents of the course will be illustrated in the associated course 103-0347-01 U (Landscape Planning and Environmental Systems (GIS Exercises)) or in Project LAND within the Experimental and Computer Lab (for Environmental Engineers). A combination of courses is recommended.
CompetenciesCompetencies
Subject-specific CompetenciesConcepts and Theoriesassessed
Techniques and Technologiesassessed
Method-specific CompetenciesAnalytical Competenciesassessed
Decision-makingassessed
Media and Digital Technologiesassessed
Problem-solvingassessed
Project Managementassessed
Social CompetenciesCommunicationassessed
Cooperation and Teamworkfostered
Customer Orientationfostered
Leadership and Responsibilityfostered
Self-presentation and Social Influence fostered
Sensitivity to Diversityfostered
Negotiationfostered
Personal CompetenciesAdaptability and Flexibilityfostered
Creative Thinkingassessed
Critical Thinkingassessed
Integrity and Work Ethicsfostered
Self-awareness and Self-reflection fostered
Self-direction and Self-management fostered
103-0377-10LBasics of RE&IS Restricted registration - show details
Only for Spatial Development and Infrastructure Systems MSc.
O3 credits2GK. W. Axhausen, B. T. Adey, A. Grêt-Regamey, C. Sailer
AbstractThe course Basics of RE&IS provides essential basic knowledge for the Master's degree program in Spatial Development & Infrastructure Systems and is divided into the three main topics of technical-scientific working, writing & presenting. The students deepen and apply the learned knowledge in the context of three performance elements and one ungraded semester performance.
Objective- Students will be able to identify, name, and be able to define the content taught.
- The students can assess, discuss and explain the necessity, significance and application of the standards in scientific work.
- Students will be able to apply the content, implement it in different examples and use it to solve the exercises and the semester assignment.
- With the techniques learned in the course, students will be able to analyze and differentiate scientific sources and apply them in their work in a structured way.
- The knowledge learned will help students to be able to assess, decide, evaluate and critically evaluate in the context of the semester assignment.
-Students are able to systematically compare and present their results in an argumentative manner.
-Students are able to produce their results in collaboration with their group and are able to develop, formulate and design a scientific and technical report to complete the assignment.
-The students are able to present their results in an engaging presentation together with their project group and use attractive and formally correct visualizations, maps or diagrams for this purpose.
-The students thus develop a common understanding with regard to their methodological knowledge and can henceforth work scientifically at an appropriate level.
ContentStudents will learn the basics of scientific work and practice their skills within the framework of three performance elements as well as an ungraded semester work, which will be worked out in groups of two to three students.

In the first half of the semester, students will learn the theoretical basics and apply and understand these in the context of the exercises (=performance elements) in groups of maximum of two. The final ungraded semester exercise in the second part of the course, students will work in groups of maximum two on an assignment, which they will document and communicate in the form of a written report and a final presentation at the end of the course.

-Exercise 1: Citations & Referencing 20%
-Exercise 2: Searching, Reading and Summarizing 20%
-Exercise 3: Maps, Graphs & Visualizations 20%
-Exercise 4: Review 20%
-Presentation of review 20%

Students will be supervised by at least three assistants and one professor throughout the course. The main course lead changes periodically between the following RE&IS chairs: Infrastructure Management (IM), Transportation Systems (TS), Traffic Engineering (SVT), Transport Planning (VPL), Spatial Development and Urban Policy (SPUR), Planning of Landscape and Urban Systems (PLUS) and Spatial Transformation Laboratories (STL).
Lecture notesAll documents relevant for the course (slides, literature, further links, etc.) are provided centrally via the moddle platform.
LiteratureAmerican Psychological Association (APA) (2010) Publication Manual of the American Psychological Association, 6th edition, APA, Washington, D.C.
Axhausen, K.W. (2016) Style Guide for Student Dissertations, IVT, ETH Zürich, Zürich (available as download under learning materials)
Backhaus, N. and R. Tuor (2008): Leitfaden für wissenschaftliches Arbeiten, 7. überarbeitete und ergänzte Auflage. Schriftenreihe Humangeographie 18, Geographisches Institut der Universität Zürich, Zürich.
ZürichChapman, M. and C. Wykes (1996) Plain Figures, HM Stationary Office, London.
ETH (2017) Citation etiquette: How to handle the intellectual property of others, ETH, ETH Zürich, Zürich (last retrieved 29.11.2017)
Modern Language Association of America (MLA) (2016) MLA Handbook, 8th edition, MLA, New York.
Monmonier, M. (1991) How to lie with maps, University of Chicago Press, Chicago.
Tufte, E. R. (2001) The Visual Display of Quantitative Information, Graphics Press USA
Wilkinson, L. (1999) The Grammar of Graphics, Springer, Berlin.
101-0509-10LNetwork Infrastructure 1 Restricted registration - show details
Only for Spatial Development and Infrastructure Systems MSc.
O3 credits2GB. T. Adey, C. Martani
AbstractSpatial planners ensure our built environment optimally meets our future needs. This course explains how spatial planners can evaluate proposed modifications to network infrastructure when there is substantial future uncertainty with respect to requirements, and how to develop implementation plans taking into consideration asset life cycles.
ObjectiveSpatial planners ensure our built environment optimally meets our future needs. This is challenging, as the built environment is a large and complex system, which interacts extensively with the natural environment. Additionally, there is considerable uncertainty with respect to the expectations of the built environment in the future, due to the uncertain environment in which we live, e.g. changing technologies and the changing climate. It is in the face of this complexity and uncertainty that spatial planners need to propose potential improvements and defend them convincingly to a large and diverse set of stakeholders.

The objective of this course is to provide spatial planners with an introduction to two essential tools in this regard. The first tool is a methodology to systematically take into consideration the future uncertainty in infrastructure requirements when proposing changes to the built environment. This involves the identification of key uncertainties, modelling their effect on infrastructure requirements and assessing how changes in future needs and the environment may affect future decisions. The second tool is a methodology to systematically estimate the life cycles of infrastructure assets. This methodology can be used together with the state of the existing infrastructure assets to develop optimal implementation plans.

More specifically, upon completion of the course students will understand how:
• to identify and quantify the service being provided by the built environment
• to construct an objective function to be used in the evaluation of proposed modifications
to estimate changing societal needs and their potential effect on required infrastructure
• to develop concepts for flexible/robust infrastructure alongside traditional infrastructure
• to simulate future scenarios to evaluate the costs and effects on the service provided over time by infrastructure
• to estimate the service provided by existing infrastructure now and in the future
• to determine optimal maintenance strategies for infrastructure
• to convert them into optimal intervention programs, which can be used to build strong arguments as to when system modifications should be implemented.
ContentThe course consists of 9 lectures, 2 projects and 5 help sections. The two hour weekly lecture period is used as follows:
1 Planning infrastructure interventions – This lecture provides an introduction to the course and why it is useful in helping spatial planners propose and evaluate modifications to the built environment. The requirements for successful completion of the course are discussed and the two projects are introduced.
2 Service – Arguments for modifying the built environment are built on meeting the future needs of stakeholders. This week we present how to identify, quantify and value the service provided by the built environment. The measures of service, along with intervention costs are used to construct an objective function to be used in the evaluation of proposed modifications.
3 Changing needs – Trying to modify the built environment to meet future needs, requires estimating them. This week we discuss how to estimate them and their potential effect on required infrastructure.
4 Robust and flexible infrastructure – In the face of large amounts of future uncertainty it is useful to have either robust infrastructure, i.e. infrastructure that meets a large range of possible future needs, or flexible infrastructure, i.e. infrastructure that can be easily modified to meet different possible future needs. This week we discuss the concepts of robustness and flexibility and demonstrate their roles in maximizing the net-benefit of infrastructure.
5 Evaluating robust and flexible infrastructure – Robust and flexible infrastructure sometimes comes with increased costs. Whether or not the costs are worth it depends on a myriad of factors. This week we present a methodology that helps you develop robust and flexible infrastructure and evaluate their costs and benefits over time.
6 Simulating the uncertain future – As a key aspect to evaluating robust and flexible infrastructure is simulating what might happen in the future, this week, we explain how use Monte Carlo simulations and conduct an in class exercise so that you have an enhanced understanding of how it is done.
7 Help sessions 7-9 – We use the lecture periods to answer any questions you might have on project 1.
10 Existing infrastructure – Deciding how to modify infrastructure does not only require thinking about how to meet future needs. It also requires thinking about how the existing infrastructure is likely to provide service in the future. This week, we discuss the connection between provided service and the state of the infrastructure and use a common methodology to predict their evolution over time.
11 Maintenance strategies – It is useful to know the optimal maintenance intervention strategies for infrastructure assets when considering how to modify infrastructure to accommodate future needs, as it is easier to justify expenditures when a maintenance intervention is planned than immediately afterwards, when it is in a like new state. This week we explain how optimal intervention strategies are estimated.
12 Maintenance programs – As planning periods approach, exact decisions need to be made as to which interventions will be executed, taking into consideration network level constraints, such as budgets. This week we demonstrate how the state of assets together with the optimal maintenance strategies and network level constraints can be combined to determine optimal maintenance programs. These programs are used to optimally integrate both maintenance and modification interventions into one intervention program.
13 Help sessions 13 and 14 – We use the lecture periods to answer any questions you might have on project 2.

The course uses a combination of qualitative and quantitative approaches. The quantitative analysis required in the project requires at least the use of Excel. Some students, however, prefer to use Python or R.
Lecture notes• The lecture materials consist of handouts, the slides, and example calculations in Excel.
• The lecture materials will be distributed via Moodle two days before each lecture.
LiteratureAppropriate literature will be handed out when required via Moodle.
Prerequisites / NoticeThis course has no prerequisites.
CompetenciesCompetencies
Subject-specific CompetenciesConcepts and Theoriesassessed
Techniques and Technologiesassessed
Method-specific CompetenciesAnalytical Competenciesassessed
Decision-makingassessed
Problem-solvingassessed
Social CompetenciesCooperation and Teamworkassessed
Personal CompetenciesCritical Thinkingassessed
103-0378-00LIntroduction to the Programming Language R Restricted registration - show details O3 credits2GM. J. Van Strien, A. Grêt-Regamey
AbstractR is one of the most popular programming language in science and practice for data analysis, modelling and visualisation. In this course, you will learn the basics of R and some common applications of R, such as making plots, regression analysis and working with spatial data. The weekly computer labs start with a short lecture followed by exercises that have to be handed in to pass the course.
ObjectiveThe overall objective of this course is to provide an introduction to the programming language R and to build confidence to apply R in other courses. More specifically, the objectives are:
- Understand how to import and export data, and how to work with the most important types of R-objects (e.g. vectors, data frames, matrices and lists).
- Learn how to create meaningful and visually attractive graphics and apply this knowledge to several datasets.
- Learn how to apply several types of important functions (e.g. for- and while-loops, if-else statements, data manipulation).
- Understand descriptive statistics and regression analysis and apply this knowledge to analyse several datasets.
- Understand the possibilities of analysing and plotting spatial data.
- Learn how to write own functions.
ContentThe course has a strong focus on “learning by doing”. During the weekly computer lab sessions, students will be given an introduction to the programming language R. Each lab session will start with a short introductory lecture, after which students work through the script and complete the exercises. During the lab sessions, the lecturers will be available to answer individual questions. The main topics that will be covered in the lab sessions are:
- importing and exporting data
- types of R-objects
- data scraping
- plotting data
- descriptive statistics
- data manipulation
- conditionals and loops
- regression analysis
- plotting and analysing spatial data
- writing own functions

In the 7th and 14th week of the course, students have the time to finish the exercises that should be handed in at the end of those weeks.
Lecture notesA script with theory, examples and exercises will be handed out at the beginning of the course. Data for the exercises will be made available via Moodle.
LiteratureOptional supplementary reading is the book: Venables, Smith & R Core Team (2021) An Introduction to R. This book can be downloaded for free from: Link.
Prerequisites / NoticeNo prior knowledge of R or any other programming language is required for this course.
CompetenciesCompetencies
Subject-specific CompetenciesConcepts and Theoriesfostered
Techniques and Technologiesassessed
Method-specific CompetenciesAnalytical Competenciesassessed
Decision-makingfostered
Media and Digital Technologiesfostered
Problem-solvingassessed
Project Managementfostered
Social CompetenciesCommunicationfostered
Cooperation and Teamworkfostered
Customer Orientationfostered
Leadership and Responsibilityfostered
Self-presentation and Social Influence fostered
Sensitivity to Diversityfostered
Negotiationfostered
Personal CompetenciesAdaptability and Flexibilityfostered
Creative Thinkingassessed
Critical Thinkingassessed
Integrity and Work Ethicsassessed
Self-awareness and Self-reflection fostered
Self-direction and Self-management fostered
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