● Course Description:
This course builds on the principles and applications of remote sensing introduced in the introductory course, and focuses on more advanced topics such as hyperspectral image analysis, change detection, and object-based image analysis. Students will learn how to use QGIS to analyze these types of data and to produce more sophisticated products.
● Course Objectives:
Upon completion of this course, students will be able to:
○ Understand the advanced principles of remote sensing
○ Use QGIS software to process and analyze advanced remote sensing data
○ Produce maps and other products from advanced remote sensing data
○ Apply advanced remote sensing to solve real-world problems
● Prerequisites:
○ Introduction to Remote Sensing Using QGIS Software
○ Basic knowledge of computer science
○ Some familiarity with GIS software
● Required Software:
○ QGIS 3.x or higher
● Textbooks:
○ Hyperspectral Remote Sensing, by Michael C. Dobson
○ Change Detection Techniques for Remote Sensing, by David Maidment
○ Object-Based Image Analysis: Spatial Concepts and Applications, by Stefan J. De Jong
● Course Outline:
○ Module 1: Hyperspectral image analysis
○ Module 2: Change detection
○ Module 3: Object-based image analysis
○ Module 4: Case studies
● Course Delivery Method:
○ Lectures: Interactive lectures delivered by experienced remote sensing professionals and experts through presentations, videos, and demonstrations.
○ Homework Assignments: There will be three homework assignments throughout the course. The homework assignments will be graded on correctness and completeness.
○ Project: The project will involve applying machine learning to a remote sensing problem. Students will work in groups of two or three to complete the project. The project will be graded on creativity, originality, and technical quality.
○ Q&A Sessions: Regular question and answer sessions to clarify doubts and address participants' queries related to the course content and practical exercises.
● Course Duration:
4 weeks (can be adjusted as per requirements)
● Note:
The course content and duration can be customized according to the specific requirements and level of expertise of the target audience.