This course offers a detailed examination and implementation of sophisticated approaches for processing satellite digital images with emphasis on environmental and urban applications.
Upon successful completion of the course students should be able to:
- have an in-depth knowledge of state-of-the-art remote sensing technologies
- have a good hands-on experience with at least one remote sensing software
- apply remote sensing to solve a real research problem at his or her particular interests
Lecture 1: Introduction of Remote Sensing
Lecture 2: Multispectral Image Classification
Lecture 3: Spectral Mixture Analyses
Lecture 4: Spatial and Temporal Remote Sensing
Lecture 5: Lab
Lecture 6: Hyperspectral Remote Sensing
Lecture 7: Remote Sensing of Invasive Species
Lecture 8: Remote Sensing applications in Urban
Lecture 9: Remote Sensing applications in Coastal wetland
The course contents are taught through lectures and practical examples. Students will be required to work out assignments. Students will have the opportunity to discuss and work in teams.
The course grade depends on students’ performance in class activities, assignments, homework, quiz, and final exam.
Handout and copies of PowerPoint slides.