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Remote Sensing Image Acquisition, Analysis and Applications

Offered By: University of New South Wales via Coursera

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Remote Sensing Courses Statistics & Probability Courses Deep Learning Courses Earth Science Courses Image Analysis Courses

Course Description

Overview

Welcome to Remote Sensing Image Acquisition, Analysis and Applications, in which we explore the nature of imaging the earth's surface from space or from airborne vehicles. This course covers the fundamental nature of remote sensing and the platforms and sensor types used. It also provides an in-depth treatment of the computational algorithms employed in image understanding, ranging from the earliest historically important techniques to more recent approaches based on deep learning. It assumes no prior knowledge of remote sensing but develops the material to a depth comparable to a senior undergraduate course in remote sensing and image analysis. That requires the use of the mathematics of vector and matrix algebra, and statistics. It is recognised that not all participants will have that background so summaries and hand worked examples are included to illustrate all important material. The course material is extensively illustrated by examples and commentary on the how the technology is applied in practice. It will prepare participants to use the material in their own disciplines and to undertake more detailed study in remote sensing and related topics.

Syllabus

  • Course Welcome, Instructor, Course Resources, Module 1 Introduction and Week 1 Lectures and Quiz
    • Remote sensing is the science and technology of acquiring images of the earth’s surface from spacecraft, aircraft and drones to aid in the monitoring and management of the natural and built environments. Extensive computer-based analysis techniques are used to extract information from the recorded images in support of applications ranging over many earth and information science disciplines. This course covers the fundamental nature of remote sensing and the platforms and sensor types used. It also provides an in-depth treatment of the computational algorithms employed in image understanding, ranging from the earliest historically important techniques to more recent approaches based on deep learning. The course material is extensively illustrated by examples and commentary on the how the technology is applied in practice. While broad in its coverage the 15 hours of instruction, supported by quizzes and tests, will prepare participants to use the material in their own disciplines and to undertake more detailed study in remote sensing and related topics.
  • Week 2 Lectures and Quiz
  • Week 3 Lectures and Quiz
  • Week 4 Lectures and Quiz
  • Week 5 Lectures and Quiz, Module 1 Test
  • Module 2 Introduction, Week 6 lectures and Quiz
  • Week 7 Lectures and Quiz
  • Week 8 Lectures and Quiz
  • Week 9 Lectures and Quiz
  • Week 10 Lectures and Quiz, Module 2 Test
  • Module 3 Introduction, Week 11 Lectures and Quiz
  • Week 12 Lectures and Quiz
  • Week 13 Lectures and Quiz
  • Week 14 Lectures and Quiz
  • Week 15 Lectures and Quiz, Module 3 Test, Course Conclusion

Taught by

John Richards

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