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.
G
Great introduction on the topic of remote sensing! However I think certain topcis are over emphasized.
AS
Very Informative and Comprehensive course abut Remote Sensing and Image Acquisition
HV
Really enjoyed the learning experience and was very concise!
JH
My orientation is mineral remote sensing, but in this course I got to know basic and important issues that I had used before.Thank you Dr. John Richards and Coursera for providing such a great course.
AS
Very Good Course for having insightful knowledge on VArious Algorithm
JS
The contents are great. The slides are hard to follow. The fonts too small. Too many text per slide.
SB
It is an extension and in-depth look at Remote Sensing with the math included. Thank you for the course; make more RS courses, please.
KV
The course should add practice exercise for gaining more understanding to the course
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Very difficult to follow. Material is very technical and the lecturer simply reads from the slides. The volume of the recording is very low as well.
The course contents cover Remote Sensing but since the mentor is just like reading, just show the scripts, it's so boring. It will be better and perfect the practical exercises are added. And the course title should be changed to "Mathematical Calculations and Machine Learning in Remote Sensing". The beginner of Remote Sensing should not choose this course.
Well explained - but I already have an image processing background. Providing a bibliography/list of references at the introduction of each lecture could be helpful (as in reading ahead of the lecture).
This course provides a good base upon which you can build your remote sensing knowledge. It helps if you already have a background in CS or maths (preferably a degree in one of those two fields). Starting in the second third of the course, the lectures fluctuate between very easy going to profound mathematics. Don't be fooled by the week time needed estimations - following this estimations you will get just a basic understanding, which will be enough to complete the quizzes, but for a better understanding of lecture material, be prepared to invest 2x the estimated time.
In my opinion, this course was a bit too mathematical and monotonous, the professor for sure knows what he is talking about but after having finished the course, I am missing a few more examples of how to use the concepts in practice / with a software.
Overall, the modules were very topical and relevant to the subject matter. That said, this is a more or less technical course in Remote Sensing and may not pass for an introductory course to the subject at all. It also requires certain level of mathematical background to be able to grasp a number of concepts. The only reason I could follow is that I have been in the field for a while, and even then, I had to review the course materials multiple times before attempting the quizzes. Sincere thanks for the efforts, Prof. Richard.
The course should add practice exercise for gaining more understanding to the course
Though the course is interesting, it would have been much better if the instructor was present while explaining the concepts which would give a classroom effect.
Very difficult to understand in the online format.
Excellent course! I thoroughly enjoyed the content. The course was well structured and the professor excellently. explained most of the machine learning algorithms in the context of remote sensing applications. I am quite disappointed to see the reviews of my fellow learners rate the course -low. I would like to stress it to the future learners thinking of taking this course to confidently enroll without a doubt. I agree that the concepts are quite hard to understand and may need an active learning mindset.However this course is the ONLY course which has tried to intuitively explain the application of machine learning to remote sensing datasets. Furthermore, the professor (John richards)is a legend in the field and we need to appreciate his passion for the subject and his effort to disseminate knowledge to students!
Cheers!!
The course comprehensively covers the domains of remote sensing and associated machine learning techniques and has aided me significantly in putting those techniques in practice for my startup endeavor.
Professor Richards is an amazing lecturer and the classes are very well structured and presented.
The quizzes are difficult for me. Im just relieved that theres no computations in the quizzes. But i learned a lot. Theres a lots of technical stuff so theres a need to read more about the weekly lectures.
Excelente curso. Introduce los sensores remotos como herramientas en la interpretación de la superficie terrestre de acuerdo al área de aplicación, haciendo énfasis en la geología y la agricultura.
Really enjoyed the learning experience and was very concise!
A bit challenging but very insightful!
I learn more about remote sensing.
The course "Remote Sensing Image Acquisition, Analysis, and Applications" is an outstanding resource for anyone interested in exploring the science and practical applications of remote sensing. It provides a comprehensive overview of key topics, including satellite image acquisition, preprocessing, image classification, and advanced analytical techniques. One of the course's strengths is its balance between theory and application. The content is well-organized, with clear explanations of concepts like spectral signatures, sensor technologies, and the electromagnetic spectrum. The inclusion of real-world applications, such as environmental monitoring, urban planning, and disaster management, showcases the versatility of remote sensing and keeps the course engaging. While the material is robust, beginners might find some of the technical aspects challenging without prior exposure to GIS or programming. Supplemental resources or a preparatory module could help bridge this gap. Overall, this course is an excellent investment for students, professionals, or researchers looking to build or enhance their skills in remote sensing. Highly recommended!
Hi dear, my name is Mekonen Hunde, still I didn’t get the certificate. From the very beginning, I was asked for financial aid to learn the course Sensing Image Acquisition, Analysis, and Applications then my application was approved by financial aid via my email address. Then I completed all the tasks. The only response was congratulations on completion.
Therefore, how can get the certificate?
Very useful, technically rich and advanced learning course content. with very freindly approach. The course instructur and course structure are highly impressive, it made the learning very convenient to understand. All the quizes and assignments made learning objectives very clear.
I really enjoyed this course about satellite/aircraft remote sensing.
The teacher guides you along this complex topic in a progressive way, diving into the technical details when it is only necessary, focusing on what matters.