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Course Contents

Undergraduate Courses

ESS4104: Satellite Geosciences and Laboratory

This course introduces basic theories and principles of remote sensing, types of sensors, and analysis of remote sensing data along with specific applications. This course provides a comprehensive introduction to satellite geoscience, examining how remote sensing technologies enable the study of Earth's diverse natural systems and processes. Students will progress through fundamental principles of remote sensing to specialized applications in multispectral, thermal, and microwave imaging across both terrestrial and marine environments. The curriculum balances theoretical concepts with practical laboratory exercises, including hands-on experience with image manipulation, classification techniques, and data analysis methods essential for interpreting satellite observations.

Term Enrollment
Spring 2023 19 students
Spring 2024 25 students

Previous Student Feedback

YS
Satellite Geosciences originated from the intuitive idea of observing Earth by mounting sensors, similar to cameras, on satellites. Just as understanding how a camera works requires optical knowledge, we also need optical comprehension of what we're seeing through satellites, how we see it, and what makes certain resolutions better than others. Through the Satellite Geosciences and Laboratory course, you'll learn about different types of satellites, their orbits, and simple geometric theories of observation principles. Ultimately, you'll understand what a single pixel value means through hands-on practical exercises. The purpose of this course is to comprehend the introduction and fundamentals of this technology that observes Earth from the highest vantage point.
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ESS4137: Earth Observation Satellite Data Science and Laboratory

In this course, students will be introduced to Earth observation satellite data collected about the Earth's environment and resources, and they will learn and practice methods and analysis techniques to utilize this data. This course integrates Earth Observation Satellite (EOS) technologies with modern data science approaches, providing students with essential skills to extract meaningful insights from satellite data. Students will explore the principles and applications of various EOS systems, learning how different sensor types —optical, radar, and thermal— capture critical information about Earth's surface, atmosphere, and environmental conditions. The curriculum emphasizes practical data processing techniques, with hands-on analysis using MATLAB programming and satellite image processing software. By connecting satellite remote sensing with data science methodologies, students will develop valuable analytical capabilities for interpreting large-scale environmental datasets, monitoring natural processes, and supporting informed decision-making across scientific, commercial, and policy domains.

Term Enrollment
Fall 2023 23 students
Fall 2025 .

Previous Student Feedback

JS
Earth Observation Satellite Data Science is a course where you learn about the structure and principles of Earth Observation Satellite (EOS) data collected on Earth's environment and resources, while practicing data processing and analysis. The course combines theoretical learning with practical exercises using SNAP and MATLAB, which was beneficial for solidifying theoretical concepts. It's recommended to first take the Satellite Geosciences and Laboratory course, which covers the basic principles of satellites. However, since necessary concepts are re-explained during class, there's no significant difficulty in learning even without prerequisite courses or coding-related subjects. The knowledge I gained through this course greatly influenced my career path. It made me realize that satellite technology is a field where I could combine geology and computer science—which was exactly what I wanted to do—leading me to participate in domestic CanSat competitions and ultimately decide on a career in aerospace. I recommend this course to undergraduate students who are interested in learning about satellite data structures and directly processing and analyzing data.
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Graduate Courses

ESS6207: Satellite Hydrology

Background theories and applications of satellite geosciences for coastal envrionment will be introduced and discussed in this course. This course explores satellite hydrology that leverages remote sensing technologies to monitor and analyze Earth's water resources across global scales. Students will learn how satellite data enables measurement of important hydrological variables including precipitation, soil moisture, evapotranspiration, and surface water bodies —providing valuable insights into water resources. Practical applications ranging from flood and drought forecasting to water resource management in agriculture, urban planning, and ecosystem conservation will be discussed during paper review. Also, lab session using satellite data processing tool will be in progress to understand advanced technological approches for addressing contemporary water challenges and supporting sustainable management decisions.

Term Enrollment
Spring 2023 7 students
Spring 2024 10 students
Spring 2025 13 students

Previous Student Feedback

JH
Satellite Hydrology is a branch of hydrology that studies Earth's water cycle using satellite data. Through this course, I was able to learn theories about observing various hydrological variables (precipitation, evapotranspiration, reservoir storage, water levels, etc.) using satellite imagery. Additionally, I had the opportunity to practically apply these theories through exercises that involved calculating water body areas using satellite images and estimating changes in reservoir storage. Along with this, by reviewing related papers together, I was exposed to various fields within satellite hydrology. This course became a foundation for me to understand satellite hydrology more deeply, and based on this knowledge, I am currently conducting research that calculates river width using satellite imagery and estimates river discharge based on these calculations.
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ESS6206: Satelite Coastography

Background theories and applications of satellite geosciences for coastal envrionment will be introduced and discussed in this course. This course explores satellite coastal science, which employs advanced remote sensing technologies to study the complex interface where land meets sea. Students will discover how various satellite sensors —optical, thermal, microwave, and radar— provide meaningful data on coastal envrionment including shoreline dynamics, ocean circulation, and natural hazards. During paper review, we will discussed about various topics including tidal flat, ocean color, submarine groundwater discharge, and sea surface height, By integrating satellite observations with coastography in lab sessions, students will develop skills to address satellite data to analyze and understand pressing coastal challenges like erosion, tidal effect, climate change impacts for effective coastal planning, disaster mitigation, marine conservation, and environmental policy.

Term Enrollment
Fall 2023 7 students
Fall 2024 13 students

Previous Student Feedback

DJ
Coastal areas are dynamic spaces where complex interactions between land and ocean occur, playing crucial ecological and socioeconomic roles through material cycling, pollutant purification, carbon storage, and providing habitats for marine organisms. Globally, coastal regions are experiencing rapid physical and ecological changes due to climate change and unplanned development, necessitating continuous and wide-area monitoring. Satellite Coastography utilizes various wavelengths of electromagnetic waves—visible light, near-infrared, thermal infrared, and microwaves—to detect sediment particle sizes, tidal flat heights and areas, seawater turbidity, photosynthetic algae concentrations, and sea surface temperatures. Through this course, I studied the methodologies, significance, and limitations of previous research that interpreted coastal environmental changes, gaining insights that I could progressively apply to my own research. In particular, previous research that improved chlorophyll concentration estimation algorithms by comparing ground-measured spectral data with satellite data has structural similarities to my ongoing sediment particle size detection research, serving as a significant reference for more rigorous data refinement and interpretation.
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