2020 Faculty Courses School of Environment and Society Department of Transdisciplinary Science and Engineering Graduate major in Global Engineering for Development, Environment and Society
Geospatial data analysis for environment studies
- Academic unit or major
- Graduate major in Global Engineering for Development, Environment and Society
- Instructor(s)
- Alvin Christopher Galang Varquez
- Class Format
- Lecture (Zoom)
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - 3-4 Mon
- Class
- -
- Course Code
- GEG.E413
- Number of credits
- 100
- Course offered
- 2020
- Offered quarter
- 1Q
- Syllabus updated
- Jul 10, 2025
- Language
- English
Syllabus
Course overview and goals
With increasing resources for geospatial dataset and advances in computing technology, conducting environmental-related research can now be accelerated. In this course, students will learn the importance and advanced yet simple methods to conduct geospatial analysis. Using GIS tools and programming, students can explore environmental and socio-demographic conditions such as land reclamation, population growth, and even the monitoring of spread of diseases such as COVID-19.
Course description and aims
By the end of this course, students will be able to:
(1) Learn the basic concepts and modern techniques of geospatial analysis.
(2) Investigate and visualize an issue using GIS and programming.
(3) Be more aware and resourceful of up-to-date widely available information.
Keywords
Geographic Information System (GIS); Geospatial Analysis; Cloud Computing; Programming; Visualization
Competencies
- Specialist skills
- Intercultural skills
- Communication skills
- Critical thinking skills
- Practical and/or problem-solving skills
Class flow
Online hands-on lecture with discussion.
Course schedule/Objectives
| Course schedule | Objectives | |
|---|---|---|
| Class 1 | Course Introduction: Overview, purpose, and definitions | Students will understand the importance of acquiring the skill of conducting geospatial analyses in both their researches and future career. The purpose of geospatial analyses and basic definitions and terminology will be discussed. |
| Class 2 | GIS mapping: Vectors and Rasters | Students will experience QGIS and its features for visualizing geospatial datasets. QGIS is an open-source tool for visualizing and analyzing geospatial data. |
| Class 3 | Quantifying urban population and changes from raster data. | Students will learn how to acquire geospatial information from multiple raster files using QGIS and python programming. |
| Class 4 | Visualizing, resampling, and processing DEMs through QGIS and programming. | Students will learn how to visualize and process Digital Elevation Model (DEM) dataset and learn the importance of DEM in urban planning and environmental studies. |
| Class 5 | Geospatial analyses using Google Earth Engine: reclamation trends in Jakarta | Students will explore the Google Earth Engine framework and learn how to process satellite information to display changes of the land surface. |
| Class 6 | Visualizing tabular data through Pandas: day-to-day cases of COVID-19 by country | Students will learn how to use Pandas, a powerful module for processing tabular data. They will learn how to automatically construct time-series from table and publicly available online dataset, such as the daily cases of COVID-19. |
| Class 7 | Global mapping of COVID-19 cases and other tabular data | Continuing from the previous lecture, students will learn how to map the day-to-day changes in COVID-19 globally. |
Study advice (preparation and review)
To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to textbooks and other course material.
Textbook(s)
Handouts will be distributed online.
Reference books, course materials, etc.
Manuals:
QGIS: https://docs.qgis.org/2.18/en/docs/user_manual/
Python: https://www.python.org/about/gettingstarted/
Conda: https://docs.conda.io/projects/conda/en/latest/user-guide/getting-started.html
Evaluation methods and criteria
Individual report submissions after each class. (100%)
Related courses
- GEG.S412 ： Methods of Analysis for Socioeconomic and Environmental Data
Prerequisites
None
Other
Students must utilize Windows 10 OS PC, MACOS Computer, or Ubuntu Computer during the lecture.
Additional instructions for set-up may be provided outside of lecture on consultation basis. All meetings will be conducted via Zoom.