Keio University Syllabus and Timetable

THINKING WITH GEOSPATIAL INFORMATION(GIGA/GG/GI)

Lecturer(s)MIYASAKA, TAKAFUMI
Credit(s)2
Academic Year/Semester2026 Spring
Day/PeriodThu.2
CampusSFC
Class FormatFace-to-face classes (conducted mainly in-person)
Registration Number09986
Faculty/Graduate SchoolPOLICY MANAGEMENT / ENVIRONMENT AND INFORMATION STUDIES
Year Level1, 2, 3, 4
FieldFUNDAMENTAL SUBJECTS INTERDISCIPLINARY SUBJECTS
Grade TypeThis item will appear when you log in (Keio ID required).
English SupportWith English Support
LocationSFC
Student Screening
*For conditions regarding "additional permission", please refer to the "Student Screening Details" section. Approval for additional permission is at the lecturer's discretion, and is not guaranteed.
This item will appear when you log in (Keio ID required).
Screening Method
*If selection is by lottery: Complete the course registration process and check your permission status on the course registration screen. If selection is by assignment: Carefully review the "Student Screening Details" section, register for the course via the "Assignment Submission URL," and submit the required assignment.
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Expected Number of AcceptancesThis item will appear when you log in (Keio ID required).
Equipment & SoftwareQGIS
Contact(Mail)This item will appear when you log in (Keio ID required).
Course DescriptionLecture-based teaching and acquisition of the basic knowledge required for research activities. Broadens the range of interests in a particular direction and provides a bridge to cutting-edge topics.
K-Number FPE-CO-03303-212-04
Course AdministratorFaculty/Graduate SchoolFPEPOLICY MANAGEMENT / ENVIRONMENT AND INFORMATION STUDIES
Department/MajorCO
Main Course NumberLevel0Faculty-wide
Major Classification3Fundamental Subjects (Other Than Introductory Subjects, Subjects of Language Communication)
Minor Classification30Interdisciplinary Subjects
Subject Type3Elective subject
Supplemental Course InformationClass Classification2Lecture
Class Format1Face-to-face classes (conducted mainly in-person)
Language of Instruction2English
Academic Discipline04Geography, cultural anthropology, folklore, and related fields

Course Summary

This course aims to provide students with the spatial perspective needed to tackle environmental and social challenges through hands-on training on fundamental methods of geospatial information analysis. The first half covers foundational concepts and technical skills of Geographic Information Systems (GIS). In the second half, students engage in group work to manage a project from planning and data collection to analysis, concluding with a final presentation of their findings.

Course Description/Objectives/Teaching Method/Intended Learning Outcome

In this course, students will install QGIS, a leading open-source GIS software, on their own computers to engage in both practical exercises and group work.

Course Taught by Faculty Member with Professional Experience

Not applicable

Active Learning MethodsDescription

Lab / Skill-development / On-site training
Fieldwork
Presentations
Group work
Problem-based learning

Preparatory Study

At least one hour of self-study is required each week for preparation, review, and group work.

Course Plan

Lesson 1
Title
Introduction
Overview
Overview of geospatial information and GIS
Faculty Member/Instructor in Charge
Takafumi Miyasaka
Class Format
Same as the whole Class Format
Lesson 2
Title
Vector Data
Overview
GIS Exercise: Points, lines, and polygons
Faculty Member/Instructor in Charge
Takafumi Miyasaka
Class Format
Same as the whole Class Format
Lesson 3
Title
Raster Data
Overview
GIS Exercise: Raster data including satellite imagery
Faculty Member/Instructor in Charge
Takafumi Miyasaka
Class Format
Same as the whole Class Format
Lesson 4
Title
Drones
Overview
GIS Exercise: Drone operation
Faculty Member/Instructor in Charge
Takafumi Miyasaka
Class Format
Same as the whole Class Format
Lesson 5
Title
Coordinate Systems
Overview
GIS Exercise: Datums, geographic coordinate systems, and projected coordinate systems
Faculty Member/Instructor in Charge
Takafumi Miyasaka
Class Format
Same as the whole Class Format
Lesson 6
Title
Open Data
Overview
GIS Exercise: Open data sources (e.g., National Land Numerical Information, e-Stat, and EarthExplorer)
Faculty Member/Instructor in Charge
Takafumi Miyasaka
Class Format
Same as the whole Class Format
Lesson 7
Title
Spatial Operations
Overview
GIS Exercise: Buffer creation, spatial joins, and overlay analysis
Faculty Member/Instructor in Charge
Takafumi Miyasaka
Class Format
Same as the whole Class Format
Lesson 8
Title
Thematic Maps
Overview
GIS Exercise: Thematic map design
Faculty Member/Instructor in Charge
Takafumi Miyasaka
Class Format
Same as the whole Class Format
Lesson 9
Title
Group Work 1
Overview
Group formation and project planning
Faculty Member/Instructor in Charge
Takafumi Miyasaka
Class Format
Same as the whole Class Format
Lesson 10
Title
Group Work 2
Overview
Project implementation, including literature review, data collection, and analysis
Faculty Member/Instructor in Charge
Takafumi Miyasaka
Class Format
Same as the whole Class Format
Lesson 11
Title
Group Work 3
Overview
Project implementation, including literature review, data collection, and analysis.
Faculty Member/Instructor in Charge
Takafumi Miyasaka
Class Format
Same as the whole Class Format
Lesson 12
Title
Group Work 4
Overview
Project implementation, including literature review, data collection, and analysis.
Faculty Member/Instructor in Charge
Takafumi Miyasaka
Class Format
Same as the whole Class Format
Lesson 13
Title
Final Presentation 1
Overview
Presentation of project outcomes
Faculty Member/Instructor in Charge
Takafumi Miyasaka
Class Format
Same as the whole Class Format
Lesson 14
Title
Final Presentation 2
Overview
Presentation of project outcomes
Faculty Member/Instructor in Charge
Takafumi Miyasaka
Class Format
Same as the whole Class Format
Other
Title
Summary & Conclusion
Overview
Overall review of the course
Faculty Member/Instructor in Charge
Takafumi Miyasaka
Class Format
Same as the whole Class Format

Method of Evaluation

Evaluation will be based on weekly reports (50%), a final presentation (25%), and a final report (25%). Please note that submission of the final report is a prerequisite for receiving credit.

Generative AI Policy for Classes

In this course, the use of generative AI tools (e.g., Gemini, NotebookLM, etc.) is actively encouraged. Leveraging AI can help you gather information, develop assignment structures, and improve your writing, thereby enhancing your learning outcomes.

When using AI, please follow these rules:
• Always verify and, if necessary, revise the content generated by AI yourself. (In both reports and presentations, clearly cite the referable sources used for verification as references.)
• Clearly state the name of the AI tool used and the purpose of its use in your submissions.
• Do not use prompts containing personal information.