Kursuse/teemade ülevaade
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Learning outcomes:
After completing the course you are able to:
- Plan a geographic information project with a team and implement it,
- Find human mobility data that are needed for the project,
- Use QGIS program to analyze and manipulate spatial data,
- Find out different data analyzing techniques that support the project,
- Understand the power of visualizing your findings,
- Use QGIS findings to make a decision where non motorized traffic streets should be constructed.
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Human mobility is something that refers to ability to move. To make more clear decisions on transport infrastructure we should understand the human mobility needs. It is not always like that- politics and decision makers are biased by a number of different things. To make better decisions we should rely on the data, not someone's opinion.
Where people potentially gonna move, it means what are their mobility needs- that you gonna learn on this course. This data is somewhere and good if it's free and up to date. So we find data sets that support our decision making. where should non motorized traffic streets be constructed. This data should be analyzed somehow, in this course we use the QGIS program for that.
This course's goal is to understand mobility needs through data analysis and processing.
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1. week learning instructions:
- Start with video lecture- This is short introduction to course, grading, assessments, defining the GIS and
what is data driven decision making, everything basics that you need to start a course;
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Watch slide materials to revise the content- Things on the slides could be a little different than on the videos due the subject will change in time;
- Submit the task "What is GIS and mobility" to Moodle. This is the first assessment in this course. So you have to watch video lecture and read materials to answer this question. I hope you use your own words to describe the terms.
- Start with video lecture- This is short introduction to course, grading, assessments, defining the GIS and
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2. week learning instructions:
- This week about the program that we are gonna use through the course to analyze the mobility data.
- First we Install a QGIS from the following link (LINK)- when there is any questions, ask through forum;
- Watch a video lecture about the basics of QGIS to help you understand the program fast and support project implementation;
- There are many data types, pay attention to the data types in GIS, you need them afterward in course;
- There are tasks that I do in video,, try out all the tasks that are on the slides an in the video, they give you a experience to work with QGIS;
- Do a self-test to assess your knowledge. I am not gonna assess them, but it will give you feedback on how you understood the subject of this week.
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3. week learning instruction:
- This week we will talk about mobility datasets and specially on those that are open for everyone, one of goals in here is to find what data we could need for our project.
- Start with watching a video lecture I will cover the main theoretical parts of the topic;
- Addition to video read the lecture slides- more topics are covered in there and task description;
- Form teams or make project as one man project. You will find the description and instructions for the projects under the assignment. In teams you do all the assignments for the project. Teams distinguish from each other by the data samples. 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 topic number (will find under the registration) to group name. So you need to add group name and project topic number in the registration. Teams are distinguished by the topic number;
- Download QGIS files from the Drive, you will find them when registering the project topic. Here you need to use your topic number again. Find the data set that matches with the topic number;
- Do a self-test to assess your knowledge. Find out what you understand and what part should be retrieved.
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4. week lecture instruction:
- This week's topic is mobility forecasting. To understand the mobility we use our data set on some model. This should give us the results of mobility. This week's goal is to provide data on the model to forecast potential mobility and understand it better.
- First watch video a lecture. I will explain the model and how to implement it in the QGIS;
- Read lecture slides, it covers more than in the video and due the information compression for video, slides include more topics;
- Submit task answer under group work- only one team member should submit it. But that means you all should do the part of the project assignment.
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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;
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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.
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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.
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7. week lecture instructions:
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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;
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To revise information from video lecture read the lecture slides in your own phase ;
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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;
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It is important to share workload between team members equally;
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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;
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Do a self-test to assess your knowledge.
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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.
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