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Remote Sensing Image Acquisition, Analysis and Applications
Explore essential concepts of remote sensing technology while mastering image collection methods and analytical interpretation approaches.
Explore essential concepts of remote sensing technology while mastering image collection methods and analytical interpretation approaches.
This comprehensive course, taught by Professor John Richards, covers the science and technology of acquiring and analyzing images of Earth's surface from spacecraft, aircraft, and drones. It provides an in-depth exploration of remote sensing fundamentals, including platforms, sensor types, and computational algorithms for image understanding. The curriculum spans from basic concepts to advanced techniques like deep learning, offering a breadth of knowledge comparable to a senior undergraduate course in remote sensing. Topics include image acquisition, atmospheric effects, geometric corrections, classification methods, machine learning applications, and radar imaging. Through lectures, quizzes, and practical examples, students will gain skills applicable across various earth and information science disciplines.
4.7
(155 ratings)
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Instructors:
English
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What you'll learn
Understand the fundamental principles of remote sensing and image acquisition
Explain the effects of the atmosphere on remote sensing data and how to correct for them
Apply geometric and radiometric corrections to satellite and aerial imagery
Implement various image classification techniques, from traditional methods to advanced machine learning algorithms
Understand and apply dimensionality reduction techniques like Principal Component Analysis
Evaluate the accuracy of classification results and understand error assessment in remote sensing
Skills you'll gain
This course includes:
15 Hours PreRecorded video
18 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 15 modules in this course
This course provides a comprehensive introduction to remote sensing image acquisition, analysis, and applications. It covers the fundamental principles of remote sensing, including the physics of image acquisition, atmospheric effects, and various sensor types used on satellites, aircraft, and drones. The curriculum delves into advanced image processing techniques, from basic geometric and radiometric corrections to sophisticated classification algorithms and machine learning approaches. Students will learn about traditional classification methods, support vector machines, neural networks, and deep learning techniques applied to remote sensing data. The course also includes a thorough exploration of radar remote sensing, including synthetic aperture radar (SAR) principles and applications. Throughout the modules, practical examples and case studies illustrate the real-world applications of remote sensing in environmental monitoring, urban planning, disaster management, and other fields.
Course Welcome, Instructor, Course Resources, Module 1 Introduction and Week 1 Lectures and Quiz
Module 1 · 1 Hours to complete
Week 2 Lectures and Quiz
Module 2 · 1 Hours to complete
Week 3 Lectures and Quiz
Module 3 · 1 Hours to complete
Week 4 Lectures and Quiz
Module 4 · 1 Hours to complete
Week 5 Lectures and Quiz, Module 1 Test
Module 5 · 2 Hours to complete
Module 2 Introduction, Week 6 lectures and Quiz
Module 6 · 1 Hours to complete
Week 7 Lectures and Quiz
Module 7 · 1 Hours to complete
Week 8 Lectures and Quiz
Module 8 · 57 Minutes to complete
Week 9 Lectures and Quiz
Module 9 · 1 Hours to complete
Week 10 Lectures and Quiz, Module 2 Test
Module 10 · 2 Hours to complete
Module 3 Introduction, Week 11 Lectures and Quiz
Module 11 · 1 Hours to complete
Week 12 Lectures and Quiz
Module 12 · 1 Hours to complete
Week 13 Lectures and Quiz
Module 13 · 1 Hours to complete
Week 14 Lectures and Quiz
Module 14 · 1 Hours to complete
Week 15 Lectures and Quiz, Module 3 Test, Course Conclusion
Module 15 · 2 Hours to complete
Fee Structure
Payment options
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Instructor
Emeritus Professor
John earned his Bachelor of Engineering (Hons 1) in 1968 and Doctor of Philosophy in 1972, both in Electrical Engineering from the University of New South Wales. He most recently served as Master of University House at the Australian National University (ANU), where he was previously Deputy Vice-Chancellor and Vice President, as well as Dean of the College of Engineering and Computer Science. In the 1980s, he was the founding Director of the Centre for Remote Sensing at UNSW. John is a Fellow of the Australian Academy of Technological Sciences and Engineering, a Fellow of Engineers Australia, and a Life Fellow of the IEEE. He is also President of the International Society for Digital Earth, with research interests in image interpretation and imaging radar.
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4.7 course rating
155 ratings
Frequently asked questions
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