Welcome to Remote Sensing

Welcome to this introductory book on Remote Sensing, which is intended to be the equivalent of a textbook for an undergraduate-level university course. You are free to use this book any way you like; it is separated into “chapters” that correspond to the readings my own students should do in preparation for lectures and lab exercises each week.

To navigate the book, click the ‘Contents’ button in the top left corner, then click the ‘+’ sign next to where it says ‘Main Body’. Then click on the chapter you want to read.

Remote sensing is a practical subject – it is something people do, as opposed to something people simply know or think about. To learn it well, you should therefore ideally combine reading a textbook with some practical exercises in which you learn to ‘do’ remote sensing – which typically means use remote sensing data to map something on the Earth’s surface. Nowadays, when there is more than 1000 Earth-orbiting satellites continually collecting remote sensing data, remote sensing is rarely done in the way it was done in the past – by downloading an image from the website of a space agency, and interactively manipulating it in image processing software. Most people these days use programming to have the computer analyze many images together. On my GitHub site you will a series of Python notebooks. You can open these in Google Colab and use them to teach yourself how to do basic Python programming, and how to manipulate spatial data, including remote sensing data, using Python. (If you’re brand new to Python and Google Colab, there’s a gentle introduction here). Just open Colab, upload the file called Chapter_1.ipynb, and go through it step by step. Then go to Chapter_2.ipynb, and so on. You will not regret doing this; Python programming is a very transferable skill, and especially the later labs (e.g. the labs named GEE) really demonstrate the power of automated processing of satellite imagery to understand things about the world that are hard to see without the vantage point from space.

If you are looking for an actual published textbook to complement this document, there are several I can recommend. All of them will have additional information not present in this document, and will also be missing some of the information you will find below. Some are specialized, as you can see from their titles, others are general and could have been used as textbooks for this course. Remote sensing is a field that in some ways develop quickly (new sensors are launched into space all the time), and in other ways develops slowly (many of the basic techniques for digital image processing were developed decades ago and are still used). Keep this in mind if you read through an older textbook. Some books you should consider looking at for complementary information (this is not an exhaustive list!):

In English:

J.B. Campbell and R.H. Wynne: Introduction to Remote Sensing. 5^th edition, 2011.

J.R. Jensen: Introductory Digital Image Processing. 4^th edition, 2015.

J.R. Jensen: Remote Sensing of the Environment: An Earth Resource Perspective. 2^nd edition, 2006.

T. Lillesand, R.W. Kiefer and J.W. Chipman: Remote Sensing and Image Interpretation. 7^th edition, 2015.

E. Chuvieco: Fundamentals of Satellite Remote Sensing: An Environmental Approach. 2^nd edition, 2016.

H.G. Jones and R.A. Vaughan: Remote Sensing of Vegetation: Principles, Techniques, and Applications. 1^st edition, 2010.

I. Woodhouse: Introduction to Microwave Remote Sensing. 1^st edition, 2006.

In French:

M.-C. Girard and C.M. Girard: Traitement des données de télédétection. 2^eme édition, 2010.

In addition, the website of the Canada Centre for Remote Sensing has some easy tutorials that you can access for free. And remember that the Internet is your friend when it comes to learning remote sensing – there are lots of sites where people have already asked the exact questions you will be asking yourself as you go through this course, and other, usually knowledgeable, people have answered them.