Abschnittsübersicht

  • General information

    Alles einklappen Alles aufklappen

                                              

                  Intelligent Transport and Traffic Management study module
                              Practical activities - GIS and mobility 3 ECTS

                      

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      Learning outcomes:

      After completing the course, you are able to:

      1. Plan a geographic information project with a team and implement it.
      2. Find human mobility data that are needed for the project,
      3. Use the QGIS program to analyse and manipulate spatial data,
      4. Find out different data analysis techniques that support the project,
      5. Understand the power of visualising your findings,
      6. Use QGIS findings to make a decision where non-motorised traffic streets should be constructed.

       

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      Lecturer:

      Rene Maas, TTK

      rene.maas@tktk.ee

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      Human mobility refers to the ability to move. To make clearer decisions on transport infrastructure, we should understand the needs of human mobility. It is not always straightforward; politics and decision-makers are influenced by various factors. To make better decisions, we should rely on data rather than someone's opinion.

      Where people are potentially going to move indicates their mobility needs, something you will learn in this course. This data is most useful if it is free and up to date. Therefore, we identify datasets that support our decision-making, such as those indicating where non-motorised traffic streets should be constructed. This data should be analysed; in this course, we use QGIS to do so.

      The goal of this course is to understand mobility needs through data analysis and processing.

       

    • Announcements Forum
    • Assessment Textseite
    • Questions Forum
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  • Week 1- Introduction to the course and GIS

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      1. Week Learning Instructions:

      • Start with the video lecture – This provides a brief introduction to the course, grading and assessments, the definition of GIS, and data-driven decision-making. It covers all the basics needed to start the course.
      • Review the slide materials to recall the content – the information on the slides may differ slightly from the videos because the subject matter evolves over time.
      • Submit the task "What is GIS and mobility" to Moodle. This is the first assessment in this course. Therefore, you need to watch the video lecture and read the materials to answer this question. I encourage you to use your own words to describe the terms.
    • Lecture slides Datei
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    • What is GIS and Mobility (ind) Aufgabe
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    • Extra material (what is GIS)- video Link/URL
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    • Extra material (GIS in transportation)- video Link/URL
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  • Week 2- installing QGIS and software interface

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      2. Week learning instructions:

      • This week is about the software we are gonna use throughout the course to analyse mobility data.
      • First, installing QGIS from the following link (LINK)- when any questions arise, ask through the forum;
      • Watch a video lecture about the basics of QGIS to help you understand the program more deeply and support project implementation;
      • There are many data types in GIS; pay attention to them, as they are needed in future work;
      • There are tasks that are performed in video, try out all the tasks that are on the slides and in the video, which give you experience to work with QGIS;
      • Do a self-test to assess your knowledge. They are not gonna assess, but it will give you feedback on how you understood the subject this week.
    • Lecture slides- slides Datei
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    • self-test
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  • Week 3- open datasets for mobility

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      3. Weekly learning instruction:

      • This week will focus on mobility datasets, especially those that are open to everyone. One of the goals is to find what data is needed for the project.
      • Start by watching a video lecture, which will cover the main theoretical parts of the topic;
      • In addition to the video, read the lecture slides- more topics are covered in there and the task description;
      • Form teams or make a project a one-man project. You will find the project descriptions and instructions under the assignment. In teams, you do all the assignments for the project. Teams distinguish themselves from one another by their data. One project topic will use one data set, and the other will use something else;
      • Register project topic- add max 3 participants and also include the topic number (which you will find under registration) to the group name. Add the group name and project topic number in the registration. Teams are distinguished by the topic number;
      • Download QGIS files from the Drive; the link is under the project registration topic. Find the data set from the Drive that matches the topic number;
      • Do a self-test to assess your knowledge. Find out what you understand and what part should be retrieved.
    • Lecture slides- slides Datei
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    • One mobility project overview- task (ind) Aufgabe
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    • Extra reading (how Google collects data)- reading Link/URL
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    • extra reading (pros and cons of open data)- link Link/URL
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    • Extra reading (analysis on open data)- reading Datei
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  • Week 4- framework of mobility forecasting

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      4. week lecture instruction:

      • This week's topic is about mobility forecasting. To understand the mobility, you use a dataset on a framework model. It should provide the mobility results. This week's goal is to provide data on the model to forecast potential mobility and understand it.
      • First, watch a lecture video. I will explain the model and how to implement it in QGIS;
      • Read the lecture slides, it covers more than in the video, and due to the information compression for the video, the slides include more topics;
      • Submit the task answer under group work- only one team member should submit it. But that means you all should do your part of the project assignment.

    • Lecture slides- slides Datei
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    • Traffic forecasting framework steps (group) Aufgabe
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    • Extra reading (4 step transportation planning model)- link Link/URL
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    • Extra material (4 step model for bicycle) - video Link/URL
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  • Week 5- spatial analyzis in QGIS

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      5. week lecture instruction:

      • This week's topic is analyzing the data in QGIS. We do spatial analysis and try to extract the useful information from previous layers in QGIS.
      • Watch video lecture;
      • Read lecture slides, there are more information than in the video;
      • Try out all the tasks on slides, you will need those layers afterward. So save them in the same folder where your other files. Its is good to organize your files, so nothing could be missed;
      • Do self-test to assess your knowledge;

      • Read through special topics and an extra material to get a better understanding with projections in QGIS. It will give extra information on the topic when you want, it makes you understand the QGIS better also.

         

    • Video lecture Link/URL
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    • Lecture slides- slides Datei
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    • Mobility model scetch- task (group) Aufgabe
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    • Self-test
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    • Extra reading (projections in QGIS)- link Link/URL
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    • Special topic: projections in QGIS- PDF Datei
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  • Week 6- apply mobility forecasting framework in QGIS

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      6. week lecture instruction:

      • This week we try to apply the framework in QGIS. It is bringing the theoretical formulas into the real life application. This week's goal is to use the mobility forecasting framework model on your data in the QGIS.
      • Watch video lecture;
      • Read lecture slides, there are more information than in the video;
      • Communicate with team members and start making layers that are needed for a final project.
      • It is important to share workload between team members. Communication is very important as it give a change to share information and everyone want to be informed. When others do not communicate, communicate by yourself, someone has to start the chain.
      • Do a self-test to assess your knowledge.
    • Video lecture Link/URL
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    • Lecture slides- slides Datei
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    • Self-test
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  • Week 7- mobility zones in QGIS

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      7. week lecture instructions:

      • This week's topic is mobility zones. As we have understood there are areas where potentially more students will go to a particular school than from some other area. So we have to extract those areas using the threshold and connect those areas spatially with schools. Output is areas where the most mobility should take place. Those areas  covers the potential paths for students to go to school;

      • To revise information from video lecture read the lecture slides in your own phase ;

      • Communicate with the team and move on with a project. Communication is important on every step to be sure that everyone could understand the phase of the project;

      • It is important to share workload between team members equally;

      • Add 2 new layers: "mobility zones", "non motorized streets" to your project. First one is the spatial zones where the mobility could take the place and the second is for digitizing only those streets that are under the mobility zones;

      • Do a self-test to assess your knowledge.

    • Video lecture Link/URL
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    • Lecture slides- slides Datei
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    • self-test
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  • Week 8- final documentation, course conclusions

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      8. week lecture instructions:

      • Watch out that you have covered all the topics and necessary layers are included in you project. you will find them from the lecture slides;
      • For theory part of the project, take only one team member input or mix them together, choice is yours;
      • Upload final project with QGIS layers;
      • Upload project using Drive (most preferred);
      • You can't add a link directly to assignment, so paste it to notepad or word and submit this way;
      • Upload all the QGIS layers to Drive but separately from the theory section (make two separate folders to drive);
      • Share all folders with public restrictions. So we could get them and assess them.
    • Lecture slides- slides Datei
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    • Final project link submit- task (group) Aufgabe
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