Instructor: Bo Zhao, [email protected] | Office Hours: T 5-5:50pm or by appt. @ WLKN 210
Lecture: TR 4-4:50pm @WLKN 210 | Lab: T 6-7:50pm @WLKN 210
Catalog Course Description: GEOVISUALIZATION III: GEOVISUAL ANALYTICS (3). Concepts and techniques underlying the production of maps by computer. Practical experience with a variety of computer mapping packages.
Welcome to GEOG 4/572: Geovisual Analytics! This course introduces geovisual analytical theories, advanced geovisual analytical methodologies, and some popular toolkits. In this course, students work collaboratively to solve a real-world problem using geovisual analytics.
No required textbook 📚. Recommended Papers and online materials will be available on the course website, and some recommended books will be reserved in valley library. Students must complete required reading assignments before attending the corresponding lecture. Quizzes or Homeworks will cover the content of the reading assignments.
Slocum,T. A., McMaster, R. M., Kessler, F. C., Howard, H. H., & Mc Master, R. B.(2008). Thematic cartography and geographic visualization. Pearson; 3rd edition (April 14, 2008). ISBN-13: 978-0132298346
1. Presentation Sequence (4/18/2019)
2. Submit your Project Proposal (:pushpin: Deadline: 4/23/2019)
| WEEK | 📖 LECTURE (T) | 💻 LAB (T) | 📖 LECTURE (R) | 💟 PROJECT |
|---|---|---|---|---|
| Wk 01 | Intro to this course | Lab1: Project Management for GeoViz | no class Geovisual Analytics Basics (reading) |
Introduction, Brainstorm |
| Wk 02 | GeoViz Programming Basics (reading) |
Lab2: Interactive Map Design | Leaflet Interactive Maps (reading) |
Team-up |
| Wk 03 | D3 Fundamentals (reading) |
Lab2 cont’d | Spatial Data Processing (reading) |
Proposal |
| Wk 04 | D3 Graphics (reading) |
Lab2 cont’d; 🐛 Debugging | C3 Charts (reading) |
Data Source, Proposal Revision |
| Wk 05 | Bootstrap Interface Design (reading) |
Lab3: Integrated Geovisualization | Web Design Elements (reading) |
Sketch |
| Wk 06 | Flow maps | Lab3 cont’d | Word Cloud - Ashley | Design Scheme |
| Wk 07 | Heatmap - Michael | Lab3 cont'd | Dealing with Time - Benjamin | Coding |
| Wk 08 | GeoViz Evaluation (reading) |
Studio | Hexagonal Maps - Robert | Coding |
| Wk 09 | ☁️ Point Cloud Viz - Katherine and Bryan | Studio | Fine-tuning | |
| Wk 10 | Studio | Studio | Project Presentations | Presentation |
| Item | Description | % of Final Grade (GEOG 472) | % of Final Grade (GEOG 572) |
|---|---|---|---|
| Participation | Discussion, in-class work and other activities | 5 | 5 |
| Quizzes | no more than 6 in-class or take-home quizzes covering topics from lecture and reading assignments. | 25 | 10 |
| Labs | 3 lab assignments. We understand that many of the programming techniques discussed early in the course will be relatively new. Recognizing this, the first 2 lab assignments will contain more detailed instructions. | 30 | 20 |
| Presentation | Each student is required to present an existing geovisualization project to the class before the lecture. | 10 | 10 |
| Course Contribution | Each graduate student is expected to contribute to this course. It could be leading the course, updating the experiment, or working with the instructor on some related course work. This course contribution is designed to help the graduate student to work closely with the instructor on geoviz related skills. | 0 | 20 |
| Project | Each student is required to collaboratively develop a final project using geovisual analytics. Each project should be no more than four members. Graduate students are encouraged to be the group leader or the project coordinator, and undergraduate students are encouraged to be a principle group member. Each group will make a presentation to demonstrate their work. This final project is mainly evaluated by both the presentation and the quality of the geovisual application. | 30 | 35 |
| Total | 100 | 100 |
Note: to calculate the final grade, we use all the earned points of each item (e.g., lab, quizzes, project development, project) divided by the total points of its item, and then multiply it by the allocated percentage of this item. Take the lab for geog 572 for example, if a student got 45 points for lab 1, 50 for lab 2, 46 for lab 3, the lab portion of the final grade will be (45+50+46) /150 *20% = 18.8%. Accordingly, by adding up the grades of each item, we will get the final grade of the examined student.
Final grades are based on the percentage of maximum points accumulated and assigned according to this table:
| A 93 – 100% | B- 80 – 82% | D+ 68 – 69% |
|---|---|---|
| A- 90 – 92% | C+ 78 – 79% | D 62 – 67% |
| B+ 87 – 89% | C 72 – 77% | D- 60 – 61% |
| B 83 – 86% | C- 70 – 71% | F < 60% |
You are expected to attend lectures twice a week. Attending lectures and labs is important since these times provide you with access to the instructor and to other students. Keep in mind that not all lab assignment will be possible to finish in the allotted class time. Students will be expected to work on assignments outside of class during posted Lab hours. You are welcome to discuss the exercises amongst yourselves, in fact this is encouraged, but the final product you hand in must be your own work.
During the term, there will be three lab assignments. The main purpose of the lab assignments is to learn how to apply and reflect upon the things we cover during the lectures, and to grasp proficient hands-on skills to solve real world problems. If you are having difficulty with these assignments you should ask for assistance, whether from fellow students, or from me. Whatever you do, ask someone but please note the academic integrity policy!
Lab assignments are required to be submitted electronically to Canvas unless stated otherwise. Efforts will be made to have them graded and returned within one week after they are submitted.Lab assignments are expected to be completed by the due date. A late penalty of at least 10 percentage units will be taken off each day after the due date.
If you have a genuine reason(known medical condition, a pile-up of due assignments on other courses, ROTC,athletics teams, job interview, religious obligations etc.) for being unable to complete work on time, then some flexibility is possible. However, if in my judgment you could reasonably have let me know beforehand that there would likely be a delay, and then a late penalty will still be imposed if I don't hear from you until after the deadline has passed. For unforeseeable problems,I can be more flexible. If there are ongoing medical, personal, or other issues that are likely to affect your work all semester, then please arrange to see me to discuss the situation. There will be NO make-up exams except for circumstances like those above.
The final project is a major component of this course. For each group, there should be no more than four students. I recommend a group should be formed by graduate and undergraduate students. Each group will collaboratively work on a final project using geovisual analytics. The instructor will provide several topics for students to choose from. Students can also bring their own topics. Students in a group can work on a project of their common interests. Although the project topic is important, this project is more about how to apply the geovisual skills. So, students who want to team up as a group need to have a consensus that they are interested in using the similar geovisual tools and methods. Regarding the project topics, the instructor will provide a pool of topics to choose from during the first two weeks. In the rest of the term, students will concentrate on developing the project. The instructor and TA will provide necessary guidance in applying the geovisual skills for the projects. Since some of the topics are proposed by other faculty members in the university, a co-advisor/group member will join you to provide extra help.
1. Students work from previous years
2. Storymap.js - a map storytelling library
3. NeoCarto - a geovisual analytical framework
Credits: This course material is maintained by the Cartography and Geovisualization Group at Oregon State University. Some of the material in this course is based on the classes taught at MIT and Penn State University. We have heavily drawn on materials and examples found online and tried our best to give credit by linking to the original source. Please contact us if you find materials where the credit is missing or that you would rather have removed.