Course Description:
This course introduces cloud computing techniques for remote sensing. The course will cover the fundamentals of cloud computing, including infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS). The course will also cover the application of cloud computing to remote sensing problems, such as data storage, data processing, and data analysis.
Course Objectives:
Upon completion of this course, students will be able to:
○ Understand the fundamentals of cloud computing
○ Apply cloud computing to remote sensing problems
○ Evaluate the performance of cloud computing platforms
○ Use cloud computing to solve real-world problems
Prerequisites:
○ Introduction to Remote Sensing
○ Introduction to Programming
Textbooks:
○ Buyya, Rajkumar, et al. Cloud Computing: Principles and Paradigms. 3rd ed. Springer, 2014.
○ Amini, Bahram, and Saeed Amini. Cloud Computing for Remote Sensing. CRC Press, 2019.
Course Outline:
○ Module 1: Introduction to cloud computing
○ Module 2: Infrastructure as a service (IaaS)
○ Module 3: Platform as a service (PaaS)
○ Module 4: Software as a service (SaaS)
○ Module 5: Remote sensing data storage
○ Module 6: Remote sensing data processing
○ Module 7: Remote sensing data analysis
○ Module 8: 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.