Hello, my name is John Richards, I am your instructor for this course. Our focus is going to be the field of remote sensing, which is the technology for recording and using images of portions of the Earth surface. By analyzing and interpreting those images we can gain an understanding of how the region is used and managed, how it changes with time, and how natural features are distributed. Remote sensing images are also used for mineral exploration, crop and forest monitoring, and for tracking large scale floods and wildfires. In short, it is a technology with an enormous range of Earth science and related applications. The field commenced with the taking of air photographs in various wavelength ranges back in the 1960s, but progressed very quickly in the 1970s to the recording of images from satellite platforms. Satellites give a greater field of view and can be arranged in orbit such that the whole of the Earth's surface can be imaged in a given time period. This is a first course on remote sensing. It covers how images of the Earth's surface are acquired, and methods that are used to interpret those images. It has an emphasis on how the technology is applied in practice. Although it is in some ways an introduction to remote sensing, it is not just an overview course. It develops and presents the material in sufficient depth so that your understanding on completion should be sufficient for you to enter the field professionally and to undertake more advanced treatments. The course is designed around three five-week modules. Each week will have four or five lectures, requiring about 12 to 15 minutes each of your time. Together this means each module consists of about five hours of lecture time, giving 15 hours total for the course. If you are doing the course for credit, then your total weekly workload should be about 6 hours. At the end of each lecture there is a short self-checking quiz. Answers are provided so that you can monitor your understanding as the course progresses. Those quiz questions do not form part of the course assessment, if you are doing it for credit. At the end of each week there is a multiple choice quiz. And at the end of each of the three modules there is a test. To receive credit for a module you have to perform satisfactorily in the quizzes and the test. In the first of the three modules that make up the course we will examine the physics and technology behind acquiring images from a spacecraft or other platform. This will lead us to understand something about the atmosphere and how substances on the earth surface reflect or emit electromagnetic radiation in different ranges of wavelengths. We will also look at the types of distortions that can occur in the images during the recording process and how we can take steps to correct those errors. Towards the end of the module we will think about how we can analyze images, that will set us up for a more in depth treatment in the next two modules. In the second and third modules, we examine means by which we can analyze and therefore extract information from the corrected recorded image data. This will take us into the field of machine learning. Module two will present the background theory to the various machine learning techniques that have been applied for remote sensing image data. There are two parts for module three, in the first half the module two material is placed in the context of sets of practical considerations. The second half of the third module provides a treatment of the use of radar technology for remote sensing purposes. We will illustrate each of the modules with examples and applications. Remember, the course is designed with a number of self assessments and tests built in so that you can check your understanding as you work through the material to be presented. There are many websites that you may wish to look at to supplement the treatment in this course, particularly to see examples of remote sensing images and their applications. At various stages during the presentation some will be recommended. Although there is no prescribed textbook for the course, much of the material is based on the two books listed here. Please note the permission granted by Springer to use diagrams from the books in this course is gratefully acknowledged. Please note that the diagrams cannot be reused without permission from Springer or other identified copyright owners. This is a serious course in remote sensing involving concepts from physics and mathematics. While we have limited the depth of the mathematics as much as possible, a proper understanding of some topics, particularly in module two, is not possible without a mathematical description. And knowledge of calculus, statistics, and vector, and matrix algebra is especially useful for appreciating much of that material. However, there are no mathematical derivations in the assessable material, although there are a few questions in which some formulas need to be described. If you are not strong mathematically, it should still be possible for you to cope with most of the quizzes and the tests for credit. The material in this course has been used in many ways over a number of years in courses of instruction where many of the participants had been from Earth science backgrounds and not from physics or engineering. The manner in which the material is developed is sensitive to those types of student by ensuring that careful explanations are given, accompanied by hand calculations, examples and summaries. A document is provided for you to use with each module that lists in text form the words spoken at each slide, that should help you with overcoming problems with my accent, which may be very different from your own. It would be good to use that material extensively by watching a slide, pausing the presentation, and reading the text, and rewatching the slide if necessary. I do hope you enjoy the course and it fulfills your expectations. I will have a new message for you at the start of each module, highlighting important matters in preparation for what is to come, and focusing on key messages. Remote sensing is a wonderfully exciting field, combining the best aspects of space technology, computer applications, images, and the natural world. It brings together scientists, geologists, engineers, geographers, hydrologists, foresters, surveyors, agronomists, and just about any professional who is engaged in the environment in one way or another. That's what makes it so good, it is a truly interdisciplinary endeavor.
