ERTH 5530

Environmental Remote Sensing

Lec 01 and Lab B01 selected

This course introduces remote-sensing techniques that provide environmental and geoscience information. The potential and limitations of remotely sensed data are stressed. Lectures discuss the fundamentals with an emphasis on multi-spectral satellite systems. Laboratory exercises include digital image enhancement and thematic information extraction on optical, radar, and hyperspectral data. Remote-sensing information and GIS techniques are integrated throughout the course.

Sections

Lecture
Lab

From the syllabus

From the Fall 2025 syllabus by Christopher Greene. Open the PDF

Grading

20%Small-value lab deliverables200 points
40%Independent lab projectProposal 100 points; final report 300 points
7.5%In-class exercises75 points
15%Midterm150 points
17.5%Final exam175 points

Textbook

  • Introduction to Remote Sensing (6th ed.), James B. Campbell, Randolph H. Wynne, and Valerie A. Thomas (optional, free)

Course rules

Passing
Students must earn at least 70% in both theory and applied categories or receive an F.
Late work
Written work without an accommodation is penalized 20% per calendar day.
Extensions
Students start with five 24-hour extensions for applied assessments and must request one before the deadline.
Missed deliverables
The lowest score is dropped for module exercises and structured workshops.
Missed midterm
For a valid reason, the midterm’s value is added to the final exam.
Missed final
Students who miss the final receive an Incomplete and may write a makeup at the beginning of winter semester.
Attendance
There is no direct attendance penalty, but in-class exercises and exams occur during synchronous sessions.
Generative AI
Generative AI is not permitted in assessment submissions unless the instructor says otherwise.

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