FOR 597 Advanced Remote Sensing (Fall graduate course)


  • Name: Tong Qiu
  • Office: 307 Forest Resources Building

Learning objectives

After taking this class, students should be able to:

  • Recognize: different types of remote sensing sensor/observations/data and limitations of remote sensing data
  • Comprehension of remote sensing applications:
    • Time series analysis (e.g., seasonality, long-term trends)
    • Land cover and land use change (e.g., impacts of urbanization on habitat)
    • Landscape ecology (e.g., landscape metrics)
    • Species distribution models, including LiDAR and Hyperspectral imagery
    • Primary productivity (e.g., forest carbon and food webs)
    • Thermal ecology (e.g., impacts of urban heat island effects)
  • Implementation of multi-source remote sensing:
    • Effective use of R
    • Effective use of Google Earth Engine
    • Acquiring, visualizing, and summarizing remotely sensed dataset
    • Communicating analysis with peers in written and oral format


No formal textbook; Readings assigned will be available on Canvas.


There are no prerequisites for this course.

Class format

This class takes a hybrid format, including seminar discussion and data analysis. Discussions on readings from literature and other resources: each student will present 2-3 papers (using slides) to the class; other students will ask questions and participate in the discussion; grading of the presentation will be based on peer reviews. Data analysis in R and Google Earth Engine (GEE): the instructor (Dr. Qiu) will share code and data in lab formats; students will work on the lab in the classroom and submit lab report by Friday mid-night of the following week; the instructor will grade the lab. Final project (focus on graduate research) includes 1-page proposal, in-class presentation, and 5-page final reports: grading will be based on peer reviews.

Grading and class policies

Final grade for the class is determined based on several elements. Please be extremely careful about plagiarism. Literal copy of another student’s homework (even with superficial modifications) will lead to zero credit for the homework for both students. You are also required to come to class. Participation in the in-class activities is also part of your grade. Please bring computers to the classroom.

Components Percentage
Discussion 30%
Final report 20%
Final presentation 10%
Lab report 30%
Attendance 10%